Abstract
This paper presents a realistic model of GÉANT, the European Research and Education Network, including its participant national networks. Realistic network models have an important role in network research, however their measurement from actual networks is error-prone, and algorithmic generation remains an ongoing research area.
In previous work we built a global collection of networks, using topology maps and supporting documents provided publicly by network operators. This approach allows us to include hard-to-measure information such as type and location of nodes, link speeds, and critically, external network connections. In this paper we examine using this information to connect the networks in our collection and form a small Internet, and apply it to create an 1,100 node model of GÉANT.
We have extended AutoNetkit – an automated configuration generator – to create the configurations needed to emulate this small Internet using virtual routers on a commodity PC. Emulation is a powerful tool for education and research in networking – allowing flexible networking tests at scale on an affordable budget – however, despite the ability to test large networks using emulation, there are few available as inputs. Our work provides such an input. Our emulation includes simple Quagga routing protocol configuration and DNS name resolution, and provides a starting point for complex network experiments.
One of the key tasks performed in evaluation of a new network protocol is to test it. There are various ways to do so, but it is common that the test must be made in a realistic setting. Many protocols may perform unreasonably poorly, or well, in particular cases, but it is more important to understand how they might perform in practice.
To this end, it is common to analyse a protocol, or simulate it on a particular network. More recently, emulation has become popular due to the increased ability to run multiple fully-functional virtual routers on a single computer. Emulation is more realistic than a typical simulation because the routers have many of the limitations of a hardware device (for instance, software bugs are replicated), but without the cost and inflexibility of real hardware. Examples of emulation toolkits include NetKit [1], JuniperCloud [2], and DynaMIPs [3, 4]. Between these tools, they allow emulation of Cisco and Juniper routers, among others.
Emulation’s advantage over simulation is an increase in realism, but it is not as realistic as hardware. For instance, accurate timing of events is difficult to achieve in a virtual environment, as is high throughput of data traffic. Hardware achieves these features, but the major difficulty with hardware testbeds is their cost. The cost of routers means that few testbeds have more than a dozen routers, and even these have a limited range of routers from any one vendor. So emulation allows us to perform experiments at much larger scale than is achievable in hardware.
However, there are several roadblocks in the way of achieving realistic, large-scale emulation. The foremost is simply the lack of realistic large-scale models on which to base the emulation. Measurement-based models of networks have often been found to be inaccurate, or to lack crucial information (such as link capacities) [7, 8], and the research community is still arguing about the best way to produce synthetic network models that are realistic [9, 10].
An alternative approach is to use real networks as exemplars. In the Internet Topology Zoo [11] we have transcribed a set of such networks, and made them available for use in simulation, emulation, or analysis. However, the networks in the Zoo are presented as individual networks. We do have information about the way they connect though, and in this paper we exploit this information to create a realistic “network of networks” model.
The model we present is based on GÉANT — the European Backbone Research Network — and its associate European NRENs (National Research and Education Networks). We focus on these networks because they form a meaningful subsection of the whole Internet; they have interesting variety and structure; and because these networks’ operators provide, typically, a high-quality information about both their network structure, and in some cases even the design criteria for the network. For instance, Figure 1 shows the high-level structure of GÉANT based on the information provided in [5, 6]. The resulting system comprises more than 40 component networks and over 1000 routers. This is as large, or larger than, many emulation toolkits are capable of supporting on standard hardware.
The model supports a number of features such as automatically configured DNS names and simple routing protocols so that it can serve as a fully functioning skeleton on which to place additional details of, for instance, policy based routing.
The model provides router-level connectivity of the multiple Autonomous Systems that make up the European Research Networks, but the model is just that. It is not GÉANT. We created the model by combining the information about neighbours provided publicly by GÉANT and the NRENs, and transcribed into the Zoo. However, the problems in doing so are not trivial. The publicly available information is not complete, sometimes ambiguous, and often involves translations of different networking conventions into a common framework. For instance, the different NRENs do not even have a common definition of a Point of Presence (PoP). In putting the network into such a common framework we have made approximations, and in a small set of cases we have had to fill in gaps where information was missing. In these cases have supplemented public information with measurements in to improve the quality of the results, but there is no doubt that the model varies from the real European Research Network for some details.
The model is also just one case. One subset of the whole Internet, which has many thousands of component networks. We cannot assert that it is representative of the whole Internet, and so any realistic testing should involve more than just this one case. However, we must start somewhere.
Other work has looked at modeling networks. Quoitin et al [12] use cBGP to simulate routing protocol behaviour, in the GÉANT network. Their network model was derived through access to GÉANT routing information. Liljenstam et al [13] present a model of the Internet Backbone topology, using information from traceroute studies. The model presented in this paper has been obtained from publicly available data sources.
The model from this paper is provided at www.topology-zoo.org/eu_nren.html in a variety of forms. The precise description of the networks and their interconnects is given in the form of GML (Graph Markup Language) [14], which is easily machine readable and translatable, and suitable for input into a simulation or analysis toolkit. We also use AutoNetKit [15] to translate the GML into a specific configuration for NetKit [1] an emulation toolkit. In doing so, however, we note that each router in NetKit requires approximately 32 MB of RAM. The 1000+ node full model therefore requires more RAM than most typical systems. NetKit allows large networks to be split across multiple connected machines, however, to make the model more accessible to users with small machines we have also created cut down emulation models that require memory that is typical of commodity PCs today.
The primary source of data used to create this model is network maps, and other descriptive documents provided by the operators of GÉANT and the European NRENs themselves.
The data was collected into the Internet Topology Zoo [11] www.topology-zoo.org in previous work. The Internet Topology Zoo is a collection of networks, derived from publicly available records, stripped down to a clearly labelled graph form and stored with all of its associated metadata in an on-line repository. It is a collection of networks of different purposes, research and/or commercial, and different types, with small local scale and large continental range. In this collection we have a large amount of information on GÉANT and its component networks, which we use to extract the data that we will use in the rest of this paper. The data in the Zoo is in the form of individual networks, however, the information provided by many network operators includes data on their interconnects with other networks. In this project, we stitched together a group of more than 40 such networks to create a model of the type of interconnected network of networks that comprises the Internet.
The advantage of the Zoo data, as compared to typical measurement studies lies in its relative accuracy, which derives from the fact that the data is provided by the network operator, rather than inferred, and the fact that the data provided by operators contains much meta data information of use in creating a realistic emulation. For instance, the data contains geographic locations (which we have geocoded [16] to latitude and longitude with an approximate accuracy of a metropolitan area) and link capacities.
The data is not complete, and so we have supplemented it by directed traceroutes to ascertain additional details (for instance the location of interconnects). In using these traceroutes to find specific information, we avoid some of the common pitfalls in such measurements. For instance, we do not need to resolve the aliasing problem as we do not need to mesh a set of traceroutes into a full network; and we are not as concerned about missing links because we are using traceroute to resolve the location of links that we know are present. There is still the possibility that some links are missed because neither GÉANT, or any NREN, report them. We also examine the results manually to check them, rather than automatically compiling them through some inference process.
Also, not all network topology maps provide the full location name of each node. Many use abbreviated node names, or names in local languages. For these we refer to supplementary information, such as annual reports or PoP listings on operator websites, and make use of alternate place names in Geonames. We also use routing-registry data, and reverse DNS to help resolve ambiguities, but again we do it in a targeted manner (described later in the paper), and manually parse the results. We also verify network co-ordinates by plotting the network maps and inspecting them.
One final issue is that the network maps and data provided by operators are not all contemporaneous. Table 1 documents the dates of each part of the network. This presents the problem that they may be “out of sync” in the sense that one network may report a recent interconnect that another network has not. We found little evidence for this type of error in the data, but there certainly are some ambiguities in the interconnect data, and we shall describe how we resolve these in the following sections.
The choice of the European Research Network for this study is based on a number of features. Research and education networks are generally non-commercial in nature and, as a result, often less reticent about revealing data. In fact, these networks are often required to provide high-quality, detailed information about their networks — through published maps, annual reports, or at regional conferences — as a result of their funding models.
The non-commercial nature of research and education networks also means they don’t have to expand to meet a growing corporate or individual user clientele. They normally connect Universities, or other educational facilities, and these facilities do not come and go as quickly as businesses do, so NRENs tend to be more stable in their development and add and remove nodes slowly.
The set of networks is also well constrained so we can hope to model it all. The Autonomous System- or AS-level topology is simple, but not trivial, and the NRENs show a remarkable variety ranging from hub-spoke networks, to rings, to much meshier networks.
The starting point for the model was the individual networks in the Zoo, selected according to the GÉANT network partner list [17] shown in Table 1. The most recent map for each was used, with dates given in the table. We were not able to find a network topology for JSSC, the Russian NREN, and the University of Malta, so we add a single node to our model for each of these.
For some networks we have multiple views, for instance, layer 1 and layer 3 maps. In these cases we primarily use the IP level maps, except where the layer 1 map helps resolve ambiguities in the higher level.
For each network, we derived a single ASN (Autonomous System Number) to use in the model for configuring inter-domain routing. Tables such as [18] provide a list of ASNs and their respective network operator. However, many network operators use more than one ASN, e.g., DFN, the German NREN, has AS680, AS1275, AS2123, and AS2124. Selection of a particular ASN for each NREN is non-trivial. Our approach was to select a particular IP address for each operator, usually something central such as their main web page. We check that the IP address so chosen is sensible using traceroute and reverse DNS lookups. We then use registry information to map the IP address to an ASN and cross-reference with [18]. The choice, made this way, may simplify the actual way inter-domain routing is used by the network operator to manage their own network, but at least it assures us the the ASN we choose is being used in the network in a non-trivial manner. The ASNs chosen for each NREN are shown in Table 1.
| Partner | NREN Location | ASN | Date |
| GÉANT | Europe | 20965 | 2010-08 |
| ACOnet | Austria | 1853 | 2009-06 |
| AMRES | Serbia | 13092 | 2011-07 |
| ARNES | Slovenia | 2107 | 2010-10 |
| BELnet | Belgium | 2611 | 2010 |
| BREN | Bulgaria | 6802 | 2010-10 |
| CARNet | Croatia | 2108 | 2010-08 |
| CESNET | Czech Republic | 2852 | 2010-06 |
| CYNET | Cyprus | 3268 | 2011-01 |
| DFN | Germany | 680 | 2011-01 |
| EENet | Estonia | 3221 | 2009-06 |
| FCCN | Portugal | 1930 | 2011-03 |
| GARR | Italy | 137 | 2010-12 |
| GRNET | Greece | 5408 | 2010-10 |
| HEAnet | Ireland | 1213 | 2011-07 |
| IUCC | Israel | 378 | 2008 |
| JANET | United Kingdom | 786 | 2011-03 |
| LITNET | Lithuania | 2847 | 2009 |
| MARNet | Macedonia | 5379 | 2007 |
| MREN | Montenegro | 13092 | 2007 |
| NIIF | Hungary | 1955 | 2009-05 |
| PSNC | Poland | 9112 | 2011-07 |
| RENATER | France | 2200 | 2010-08 |
| RESTENA | Luxembourg | 2602 | 2011-03 |
| RedIris | Spain | 766 | 2011-03 |
| RoEduNet | Romania | 2614 | 2006 |
| SANET | Slovakia | 2607 | 2008 |
| SURFnet | Netherlands | 1103 | 2010-10 |
| SWITCH | Switzerland | 559 | 2011 |
| SigmaNet | Latvia | 5538 | 2007 |
| ULAKBIM | Turkey | 1967 | 2010-10 |
| Uni. of Malta | Malta | 12046 | NA |
| BASNET | Belarus | 21274 | 2008 |
| JSCC | Russia | 3058 | NA |
| RENAM | Moldova | 9199 | 2007 |
| URAN | Ukraine | 12687 | 2010-10 |
| FUNET | Finland | 8624 | 2010-10 |
| NORDUnet | Nordic region | 2603 | 2010-10 |
| RHnet | Iceland | 15474 | 2011-03 |
| SUNET | Sweden | 2603 | 2010-10 |
| Uni-C | Denmark | 1835 | 2010-10 |
| Uninett | Norway | 224 | 2011 |
There is no standard for network topology maps — the information provided differs between network operators. For instance, the definition of PoP varies between NRENS and GÉANT. The latter divides it PoPs into two broad categories [6], those that contain a router and those that are “routerless”. The router containing PoPs in GÉANT can be further grouped based on their connection method: Core PoPs that are on the GÉANT Plus fibre service (AT, CH, CZ, DE, DK, ES, FR, HU, IT, NL, and UK), those directly connected to it through leased connections (GR and PL), and those connected using leased services, but with no access to the GÉANT Plus platform (BG, EE, LT, LV, and RO)1 . Routerless PoPs can be similarly grouped: those that are on the GÉANT Plus network (BE, HR, IE, SK, SL), and those that have direct access via leased circuits (LU, PT, RU). Additionally, some locations (CY, IL, ME, MK, MT, RS, and TR) are listed as PoPs, but have no physical GÉANT presence; these are NREN PoPs, connected to remote GÉANT PoPs through leased circuits.
In a network map of GÉANT, we retain all of the above PoPs, however, the Nordic PoPs (FI, IS, NO, and SE) shown on the GÉANT topology diagram are connected through the NORDUnet network. We remove these GÉANT PoPs from our network model, and create these PoPs in the NORDUnet network instead.
At the router level, we model the network as described, i.e., we only include routers in GÉANT PoPs that have a router, and otherwise connect GÉANT directly to the NREN router across an appropriate WAN link.
GÉANT PoPs are designated by country – we find the location of the PoPs (at the level of the nearest metropolitan area) using reverse DNS using GÉANT’s looking glass tool [19]. For instance, the UK PoP router is rt1.lon.geant.uk.geant2.net, implying it is located in London.
Many of the NRENs also make distinctions between different types of PoP. Unless a PoP is clearly noted as “routerless” or given some other clear notations that indicates it should not be included, we include it in our full router model. However, we do use the differences in types of PoP to help reduce the size of the model for emulation on smaller computers (see Section 6.2).
Unless otherwise indicated by the NREN our model has one router per PoP. There are a number of key PoPs in the larger NRENs that indicate that they have more than one router, and in these cases we create a full mesh between them (though in all but a few cases there are only two routers so the interconnects are simple).
The most difficult task in this project is that of connecting the networks together. At a high level, this is relatively easy – GÉANT show how most of the NRENs are connected, however, this does not take into account the different types of GÉANT PoP (described in the previous section); or the direct interconnections between NRENs themselves; or the actual location of the connection, i.e., which router is connected to which router in two networks. We describe the various processes we have used to resolve these issues in the following.
The first issue to resolve is to determine the links from GÉANT to the NRENs to which it directly connects (for instance, we do not include the NORDUnet links here).
Determining a connection requires both the start and the end of a link. The location of the GÉANT PoPs has been determined (see previous section), but that does not determine the location of the NREN end of the connection. However, most NRENs show where they connect to GÉANT, often more accurately than the GÉANT data. We also consider the type of GÉANT PoP the NREN is connecting to. Router containing GÉANT PoPs are treated differently to non-router PoPs.
This information is additionally supplemented/verified by a limited set of targeted traceroutes, where the matching PoP is determined using reverse DNS. If the GÉANT PoP contains a router, then the exit point will show up in a traceroute. Most of the NRENs have a descriptive reverse DNS scheme, from which node location can be determined. GÉANT PoPs follow a well defined naming scheme, where the router name corresponds to the network topology map shown in Figure 1. For example a traceroute to BASNET in Belarus shows a connection from the Polish GÉANT PoP in Poznan:
In other instances, such as for GARR in Italy, we can also infer the location inside the NREN itself, where we can see the connection from GÉANT’s GARR router to GARR’s Milan PoP (GARR’s network map labels the Milan PoP by mi).
We apply similar logic to RedIris, where the topology map shows the main node to be Nacional in Madrid. Traceroute confirms that the GÉANT PoP in Spain is Madrid:
It has been noted in some research that reverse DNS entries may be unreliable, typically due to ambiguous or inconsistent naming schemes. We manually examined the entries provided here and found no examples of incorrect data. That is not to say there cannot be errors, however, if there are they are quite subtle.
Sometimes there are two NREN PoPs that connect to GÉANT, such as MI-1 and MI-2 in Milan in GARR, and Vienna1 and Vienna2 in ACOnet. As these do not list the remote GÉANT PoP, and traceroute only shows a single link, e.g.,
we are unable to confirm the GÉANT PoP for each of these NREN PoPs. However, in all these cases the GÉANT PoP is in the same city, so we connect both NREN PoPs to the same GÉANT PoP.
The topology map for FCCN in Portugal provides no external connection information, but we can again infer the appropriate PoP from traceroute:
This link is confirmed by the GÉANT Topology map, which shows PT connected to both ES and UK. We assume this is the same node connected to both, and add links from Lisbon (Lisboa) in FCCN to ES and UK in GÉANT.
There are several exceptions that needed to be dealt with separately. The first was SigmaNet in Latvia. Latnet was the Latvian NREN, renamed to SigmaNet in 2007[20]. We were unable to find a topology map for SigmaNet, and so use the most recent topology map in the Zoo for Latnet, from 2007, which shows a connection from the PoP in Riga to GÉANT2. However this is not confirmed by traceroute. We ran a series of traceroutes, from academic networks in both Australia and the UK. The path to SigmaNet followed commercial links rather than academic links. We also ran a traceroute from within SigmaNet to GÉANT, using the looking glass [21]. This shows a path via Telia, a commercial provider, to the DE GÉANT PoP — not to the LT GÉANT PoP as expected. This is likely due to SigmaNet providing both commercial and academic services. In this case, we use use the simple case of the original Latnet connection from Riga, to LT, the GÉANT PoP in Latvia.
The second exception was MREN in Montenegro, which shows no external connections on their topology map, and although it appears in the GÉANT map, it only connects to routerless PoPs. The MREN routers also do not respond to traceroute, however the connection to this network is shown in the Croatian NREN CARNet at Zagreb. Also MREN’s map shows a simple hub-spoke topology with the hub at Podgorica. On that basis we connect Podgorica in MREN to Zagreb in CARNet.
A third exception was CYNET, whose map shows links to GÉANT in Milano and Athens, consistent with the GÉANT topology map showing links from CY to IT and GR. However traceroute shows a link via UK. This is possibly going through an alternative research network, such as SEEREN, though it could result from some type of narrowband VPN connectivity. In this case we use the topology maps as the authoritative source, and ignore the traceroute.
The topology map for IUCC in Israel shows a connection to GÉANT 2 Germany, in contrast to the GÉANT topology map showing connections from IT and UK to IL. We choose the GÉANT topology map as authoritative.
In this section we consider the NREN to NREN links. We already discussed some of these, namely those that GÉANT lists as GÉANT links even though they connect between PoPs where GÉANT has no router. The links below are those which have not already been discussed.
Each of the networks we include here provides some data about its interconnections to the rest of the Internet. We manually group these into the categories, shown in Table 2. Commercial links go to a commercial transit or content provider; inter-NREN refers to links to another NREN; country links are those to another country, presumably to its NREN, though not explicitly stated; IXP means a connection to an Internet eXchange Point; Research links are to research facilities such as CERN; and Misc covers a small number of unclassifiable cases.
As we are only modeling the European research networks, we do not include any external network providers in the model2 . We do capture the inter-NREN links, and the links to another country (typically these also appear at the other NREN and can be resolved this way).
The IXP connections are harder to resolve. Some NRENs only note that they connect to an IXP, but not which. In other cases we know that multiple NRENs connect at the same IXP, but do not have data on whether they peer at those locations. For instance, ACOnet and SANET both connect to SIX, and GARR and SWITCH connect to TIX. These are problematic because the information is incomplete, ambiguous (we don’t know in fact that two connections to “SIX” are actually to the same exchange), and we cannot always be sure that the link is not already explicitly included in a map as well as implied by the connection to the IXP. Due to these ambiguities we leave these potential links out of the model.
The final set of NREN to NREN interconnections is shown in Table 3.
| Classification | Count | Examples |
| Commercial | 19 | Google (Content), Telia (Transit) |
| External NREN | 6 | Syria NREN, SEEREN, Eumed Connect |
| Countries | 8 | Russia |
| IXP | 22 | LINX |
| Research | 3 | CERN, Universities |
| Misc | 4 | Grid |
| NREN 1 | Location 1 | NREN 2 | Location 2 |
| ACOnet | Vienna1 | CESNET | Brno |
| ACOnet | Vienna1 | SANET | Vieden |
| ACOnet | Vienna2 | CESNET | Brno |
| ACOnet | Vienna2 | SANET | Vieden |
| CESNET | Brno | SANET | Brno |
| CESNET | Ostrava | PSNC | Bielsko-Biala |
| PSNC | Poznan | NORDUnet | Hamburg |
| RoEduNet | Iasi | RENAM | Chisinau |
| SANET | Zilina | PSNC | Bielsko-Biala |
| NORDUnet | Copenhagen | Uni-C | Lyngby |
| NORDUnet | Copenhagen | Uni-C | Orestad |
| NORDUnet | Copenhagen | Uninett | UiO St Olavsplass 5 |
| NORDUnet | Hamburg | PSNC | Poznan |
| NORDUnet | Helsinki | FUNET | Espoo |
| NORDUnet | Helsinki | FUNET | Helsinki |
| NORDUnet | Reyjavik | RHnet | Sturlugata |
| NORDUnet | Reyjavik | RHnet | Taeknigarour |
| NORDUnet | Stockholm | SUNET | Stockholm |
| NORDUnet | Stockholm | Uninett | Stockholm |
| NORDUnet | Stockholm | Uninett | UiO |
We make our completed network model available in a variety of graph formats, for download at www.topology-zoo.org/eu_nren.html. We use GML as our main file format. A shortened example of a PoP represented as a GML node is shown below:
The Latitude and Longitude attributes are used in plots, asn is used for configuring inter-domain routing in emulation.
There are a total of 42 networks, including GÉANT and NORDUnet in our model. A summary of the number of nodes and links in each network is shown in Table 4. The condensed node count is the number of nodes present in the condensed network mode, which is explained in Section 6.2. External links are links shown to other networks in the topology map. These are classified as discussed previously.
Visualisation provides a method of verification, allowing our results to be cross-referenced against source network topology maps. Our plotting uses the geographic co-ordinates of nodes, together with the Basemap[22] Python library for Matplotlib[23]. A cropped section of this output is shown in Figure 3, showing both individual NREN topologies and their interconnects.
Figure 2 shows interconnections at the AS level. We can see most networks connect to GÉANT. Others connect to GÉANT through other networks. This is the case for routerless GÉANT PoPs, where the GÉANT PoP is substituted with the NREN PoP. A number of networks also have links to each other, in addition to links back to GÉANT. Finally, we can see the Nordic countries connected through the NORDUnet network.
| Nodes | Links | |||
| NREN | Full Model | Condensed | Internal | External |
| GÉANT | 18 | 18 | 33 | 0 |
| ACOnet | 18 | 12 | 26 | 5 |
| AMRES | 22 | 22 | 21 | 3 |
| ARNES | 34 | 2 | 46 | 0 |
| BELnet | 22 | 19 | 25 | 0 |
| BREN | 34 | 12 | 35 | 3 |
| CARNet | 41 | 7 | 40 | 3 |
| CESNET | 45 | 20 | 56 | 7 |
| CYNET | 24 | 6 | 23 | 6 |
| DFN | 51 | 51 | 80 | 7 |
| EENet | 12 | 12 | 12 | 1 |
| FCCN | 23 | 3 | 25 | 0 |
| GARR | 44 | 19 | 58 | 12 |
| GRNET | 34 | 7 | 39 | 3 |
| HEAnet | 7 | 7 | 11 | 0 |
| IUCC | 10 | 2 | 11 | 4 |
| JANET | 29 | 8 | 45 | 0 |
| LITNET | 42 | 5 | 42 | 1 |
| Malta | 1 | 1 | 0 | 1 |
| MARNet | 17 | 3 | 24 | 3 |
| MREN | 6 | 6 | 5 | 0 |
| NIIF | 35 | 7 | 40 | 1 |
| NORDUnet | 7 | 0 | 6 | 11 |
| PSNC | 27 | 27 | 32 | 11 |
| RENATER | 38 | 38 | 49 | 5 |
| RESTENA | 15 | 15 | 17 | 4 |
| RedIris | 19 | 5 | 31 | 0 |
| RoEduNet | 40 | 7 | 44 | 2 |
| SANET | 35 | 30 | 37 | 8 |
| SURFnet | 50 | 50 | 68 | 0 |
| SWITCH | 30 | 11 | 51 | 12 |
| SigmaNet | 68 | 9 | 73 | 1 |
| ULAKBIM | 79 | 3 | 79 | 3 |
| BASNET | 6 | 6 | 5 | 1 |
| JSCC | 1 | 1 | 0 | 1 |
| RENAM | 3 | 3 | 2 | 2 |
| URAN | 19 | 9 | 19 | 5 |
| FUNET | 24 | 0 | 27 | 2 |
| RHnet | 14 | 0 | 15 | 2 |
| SUNET | 26 | 0 | 32 | 0 |
| Uni-C | 22 | 0 | 24 | 3 |
| Uninett | 66 | 0 | 93 | 3 |
Producing a model is only one part of the process. We must also validate the model to demonstrate that our model is both sufficiently accurate and realistic, as a model is only useful when it meets both of these requirements. The initial stage of our verification is in the capture of the network data from the original maps, where the data is retrieved, derived, checked and then entered into the Zoo. The Zoo is a publicly accessible resource and we welcome feedback and correction, hence our checking body is a group far beyond that of the original production team. However this only verifies the individual components.
The final map that we produce is not constructed from network maps that were all obtained at the same date. There is an obvious limitation in any data derived from live data, such as looking glasses, and even a well-drawn and dated map has an accurate lifespan measured in hours in a constantly evolving network environment. This will, inevitably, lead to some discrepancies in the network data.
However, some operators have provided maps over significant time periods, and it is interesting to note that the changes in topology are very minor over these. While link capacities may change, the locations of nodes, and their interconnections often don’t. The few exceptions we have seen have been noted earlier, and in these cases we take care to place priority upon those links that are known to exist in all maps, and those that clearly show how the network is developing over time — those links in which we have confidence.
We must then address the composition of these elements to form the GÉANT network and, as we have documented in detail here, we have used multiple views of each network to derive a consistent and well justified inter-connect topology, though there are a small set of more dubious connections documented above.
The final stage, plotting the network, allowed us to visually verify the model. Incorrect PoP locations and link connections were often immediately apparent. The final inspection took place across a range of rendered resolutions, as we moved from a verification of coarse structure down to the final validation of individual nodes.
There is no realistic way that we can then mechanically probe our GÉANT model and compare it to a probe of the real GÉANT, as we do not have their detailed BGP configurations, nor would their component networks welcome the flood of traffic required to carry out such verification. This does, however, clearly indicate why models such as this are useful and, ultimately, necessary.
It is rarely feasible to conduct experiments on production networks, especially at the continental scale, so network researchers have three alternatives for laboratory networks: hardware, emulation, or simulation. Hardware networks, while the most realistic, are expensive to construct, as physical devices must be purchased and configured. For most researchers, the cost would be prohibitive for a network of the size presented in this paper.
Simulations restrict the scope to one aspect, such as the routing decision process. Tools such as cBGP[12] enable large-scale networks to be studied, including the core GÉANT network. However limiting the scope also limits the realism of the resulting network, in terms of protocol interactions and experimental flexibility.
Emulation runs real router software in a virtual environment. This allows experiments on realistic networks, within a budget realistic to researchers. Examples include DynaMIPS [3] and GNS3 [4] running Cisco IOS.
We use Netkit[1], which runs the Open-Source Quagga[24] routing software in a User-Mode Linux (UML)[25] environment. Netkit automates the process of creating and starting UML machines, and connecting them together using virtual switching. This allows emulated networks to be easily run on commodity Linux machines. Standard Linux tools, such as BIND for DNS or ping and traceroute for measurement can also be executed, providing experimental flexibility.
While emulated networks are more realistic, they come with the real problem of device configuration. To solve this problem we have developed AutoNetkit, a software package to generate device configurations based on a network topology.
AutoNetkit [15] is a Python[26] software package, which generates configuration files suitable for the Netkit emulated network environment.
AutoNetkit reads a network topology in a graph format consisting of nodes and edges, representing routers and links respectively. These nodes and edges can contain metadata to indicate specific features. For instance a node can contain an ASN attribute, denoting the Autonomous System (AS) to which it belongs. This can be used to determine intra-AS and inter-AS links, which is used to configure routing. Additionally node names can be recorded, allowing the configuration of DNS, and link speeds, which are used to determine the link weights used in routing within an AS.
Based on the input topology, AutoNetkit will automatically allocate resources such as IP addresses to links, configure the OSPF protocol for intra-AS routing, BGP for inter-AS routing, and the BIND DNS service to provide forward and reverse domain name resolution across the network model.
AutoNetkit is based on the NetworkX [27] graph package for Python. NetworkX provides a GML parser which we have extended AutoNetkit to use to read in the network model. Each PoP in the model is represented by a single emulated router. The asn attribute is used to determine which network a router belongs to.
Links in the model are treated as point-to-point connections, with IP addresses automatically allocated. For simplicity we allocate a separate subnet to each network in the model. Links between nodes with the same asn attribute are configured using the OSPF intra-domain routing protocol, with links between nodes with differing asn attributes being configured to use the BGP inter-domain routing protocol.
The label and Network attributes are used to set router hostnames and in both forward and reverse DNS. This greatly improves the user-friendliness of our emulation, especially when studying links crossing multiple networks.
For example, for the node shown in Section 5 AutoNetkit allocates a folder name ACOnet_Salzburg, link IP address <IP_ADDRESS>, identifying loopback <IP_ADDRESS>, OSPF entries
and DNS entries in Vienna1, the ACOnet DNS server:
This is repeated for all routers in the emulated model, generating over 12,000 configuration files, which can run on a Netkit host with the lstart Netkit command.
The traceroute command shows all of IP allocation, intra and inter-domain routing and DNS working correctly:
Even though emulation can be resource efficient, the sheer size of a large-scale network model is demanding of computational resources. At 32Mb of RAM per host, emulating our 1100 node GÉANT model in Netkit would require approximately 37 Gb of RAM.
We need to provide a network model that can be emulated on lower specification machines. How to do so is non-trivial — how do we shrink the model but keep key structural properties?
A simple approach would be to restrict the geographic scope of the model — discard the Eastern European networks, giving a model of West European NRENs. Alternatively these NRENs could be reduced to a single node. This is better — inter-domain routing is more realistic — but we still lose many of the benefits of a large model.
Instead, we use the semantic data in the networks — node types and link speeds — to try and retain the core network topologies. We want to keep the backbone of each network but discard the smaller nodes at the network’s edge.
For networks that have different node types clearly distinguished, we manually group the types into core nodes, which we keep, and edge nodes, which we discard. In GRnet we keep only the nodes marked as part of the IP Backbone Topology.
In networks that do not distinguish between core and edge node, we infer structure from node types. In LITNET we keep the five nodes denoted by the large city symbol and discard the 37 remaining PoPs. We confirm this choice by looking at the link speeds: the large cities are all connected by 1 Gb/s links, while connections to other nodes are between 8 and 60 Mb/s — much lower.
Other networks do not mark different node type, but some have a clear link speed difference between nodes. In these cases, we retain only the nodes which connect to these high-speed backbone links. In GARR, we retain only nodes connected via links of 2.5 Gb/s, 10 Gb/s, or Dark Fibre.
Other networks distinguish node types, however we cannot simply remove them from the network. If optical repeaters are shown on an IP level map, we wish to retain the PoPs, but remove the optical repeaters. Removing the repeaters would disconnect many nodes. Instead, if the repeater is between two nodes, we connect them directly together, and if it has repeater has a degree greater than two, we replace it with a junction node.
Finally, some networks have multiple PoPS in the same city, such as BELnet and ACOnet. If the topology map shows them as closely related, such as grouped together, we replace them with a single node. If in doubt, we retain both nodes.
Some networks are too difficult to condense without drastically altering the network structure. This is the case for Surfnet, where the small number core nodes are connected through a complex series of other nodes. Removing them would disconnect the network. As there is no simple method apparent, we retain all nodes for Surfnet.
We check the condensed network to ensure there are no disconnected nodes, and save it to the appropriate graph format. Applying these methods reduces the network size to 463 from 1157 nodes, shrinking memory requirements from 37Gb to a more modest 15Gb. We successfully ran the condensed emulated model on a 24Gb machine.
In this paper we have presented a realistic model of the European Research Networks and their interconnections, using data made publicly available by network operators. We have applied this model to an emulated environment, allowing research into large-scale networks using commodity hardware. Both the model and emulation are available download from our website.
This paper looked at how connections to GÉANT and between NRENs. Future work will investigate connections through Internet Exchange Points and commercial providers. From this we will automatically generate the appropriate BGP Policy.
We also intend to automatically partitioning the network emulation across multiple machines, enabling both the full and condensed network models to be emulated on a series of lower resource host machines.
Finally, we would like to extend our model past European Research Networks to model a wider section of the Internet.
The authors would like to acknowledge the support of the Australian Research Council through grants DP0985063 and DP110103505, and an Australian Postgraduate Award.
[1] M. Pizzonia and M. Rimondini, “Easy emulation of complex networks on inexpensive hardware,” Proc. TridentCom, Mar 2008.
[2] (2011, 7). [Online]. Available: http://www.juniper.net/us/en/products-services/software/junos-platform/junosphere/
[3] (2011, 7). [Online]. Available: http://www.ipflow.utc.fr/index.php/Cisco_7200_Simulator
[4] (2011, 7). [Online]. Available: http://www.gns3.net/
[5] (2011, 7). [Online]. Available: http://www.geant.net/Media_Centre/Media_Library/Media%20Library/1082%20GEANT%20Topology%20SEPT%2010.pdf
[6] L. Altmanova, T. Breach, M. Campanella, M. Carboni, and M. Enrico, “Deliverable ds1. 1.1, 2: Final géant architecture,” 1 2011.
[7] W. Willinger, D. Alderson, and J. Doyle, “Mathematics and the internet: A source of enormous confusion and great potential.” Notices of the AMS, vol. 56, no. 5, pp. 586–599, 2009, http://www.ams.org/notices/200905/rtx090500586p.pdf.
[8] W. Willinger, “The science of complex networks and the Internet: Lies, damned lies, and statistics,” Feb 2010, http://www.maths.adelaide.edu.au/matthew.roughan/workshops.html.
[9] P. Mahadevan, D. V. Krioukov, K. R. Fall, and A. Vahdat, “Systematic topology analysis and generation using degree correlations.” in ACM Sigcomm, 2006.
[10] B. Krishnamurthy, W. Willinger, P. Gill, and M. Arlitt, “A socratic method for validation of measurement-based networking research,” Computer Communications, vol. 34, pp. 43–53, 2011.
[11] S. Knight, H. X. Nguyen, N. Falkner, R. Bowden, and M. Roughan, “The internet topology zoo,” to appear in IEEE Journal on Selected Areas in Communications (JSAC), 2011.
[12] B. Quoitin and S. Uhlig, “Modeling the routing of an autonomous system with C-BGP,” Network, IEEE, vol. 19, no. 6, pp. 12–19, 2005.
[13] M. Liljenstam, J. Liu, and D. Nicol, “Development of an internet backbone topology for large-scale network simulations,” in Simulation Conference, 2003. Proceedings of the 2003 Winter, vol. 1, dec. 2003, pp. 694 – 702 Vol.1.
[14] M. Himsolt, “GML: A portable Graph File Format,” http://www.fim.uni-passau.de/fileadmin/files/lehrstuhl/brandenburg/projekte/gml/gml-technical-report.pdf, Universitat Passau, Tech. Rep., 2010.
[15] H. Nguyen, M. Roughan, S. Knight, N. Falkner, O. Maennel, and R. Bush, “How to build complex, large-scale emulated networks,” in TridentCom 2010, 6th International ICST Conference on Testbeds and Research Infrastructures for the Development of Networks and Communities, Berlin, Germany, May 18-20, 2010.
[16] GeoNames. [Online]. Available: http://www.geonames.org
[17] (2011, 7). [Online]. Available: http://www.geant.net/About_GEANT/Partners/Pages/home.aspx
[18] [Online]. Available: http://www.cidr-report.org/as2.0/reserved-ases.html
[19] (2011, 7). [Online]. Available: https://tools.geant.net/portal/links/lg/index.jsp
[20] [Online]. Available: http://www.latnet.lv/
[21] [Online]. Available: http://lg.ls.lv/lg/
[22] [Online]. Available: http://matplotlib.sourceforge.net/basemap/doc/html/
[23] [Online]. Available: matplotlib.sourceforge.net
[24] K. Ishiguro, “Quagga routing software,” http://www.quagga.net.
[25] U. M. Linux, “Uml,” http://user-mode-linux.sourceforge.net/.
[26] Python, “Python programming language – official website,” http://www.python.org.
[27] A. Hagberg, P. Swart et al., “Exploring network structure, dynamics, and function using networkx,” Los Alamos National Laboratory (LANL), Tech. Rep., 2008.


They Rejected Us.
Everyone’s been rejected - these are our stories.
To add your own, please
open an issue
or tweet me at
@jkup


As a...
Web Developer/Designer, my goal is to try to come up with web/mobile app ideas that can be meaningful, helpful, and convenient for users.
Creator, I aim to produce art that tell stories and inspire others to learn and master self-expression.
Lifelong Learner, I would like to motivate others to constantly push themselves out of their comfort zone.
Human, I try to find ways to give back to the community and share my experiences in hopes of influencing people to develop their
own set of principles that'll help them navigate through life on this earth.
This website is where you can find examples of my work as a web developer, photographer/videographer, and graphic designer. You'll also see sprinkles of my journey
as a human, lifelong learner, and artist with content that is hopefully informational, inspirational, and insightful for readers and viewers alike.
Browse my
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YouTube
channel for video content, visit my
SoundCloud for music covers, check out my
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projects, and subscribe to my newsletter
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If you would like to grab a cup of (bubble) tea or have an online meeting to discuss your next project, feel free to call me at
770.904.1680 or
email me. Check my
Calendly
to view available times to making a booking.
Human. Lifelong Learner. Artist.
Một Con Người. Học Sinh Của Đời Sống. Nghệ Sĩ.
一个人。学生的生活。艺术家。


Zend Framework
LICENSE
This source file is subject to the new BSD license that is bundled with this package in the file LICENSE.txt. It is also available through the world-wide-web at this URL: http://framework.zend.com/license/new-bsd If you did not receive a copy of the license and are unable to obtain it through the world-wide-web, please send an email to<EMAIL_ADDRESS>so we can send you a copy immediately.
An AMF Message contains information about the actual individual transaction that is to be performed. It specifies the remote operation that is to be performed; a local (client) operation to be invoked upon success; and, the data to be used in the operation.
This Message structure defines how a local client would invoke a method/operation on a remote server. Additionally, the response from the Server is structured identically.
string
$_data= ''
Contains the actual data associated with the operation. It contains the client's parameter data that is passed to the server's operation/method.
When serializing a root level data type or a parameter list array, no name field is included. That is, the data is anonomously represented as "Type Marker"/"Value" pairs. When serializing member data, the data is represented as a series of "Name"/"Type"/"Value" combinations.
For server generated responses, it may contain any ActionScript data/objects that the server was expected to provide.
string
$_responseUri= ''
Universal Resource Identifier that uniquely targets the originator's Object that should receive the server's response. The server will use this path specification to target the "OnResult()" or "onStatus()" handlers within the client. For Flash, it specifies an ActionScript Object path only. The NetResponse object pointed to by the Response Uri contains the connection state information. Passing/specifying this provides a convenient mechanism for the client/server to share access to an object that is managing the state of the shared connection.
Since the server will use this field in the event of an error, this field is required even if a successful server request would not be expected to return a value to the client.
__construct(
string $targetUri, string $responseUri, string $data
)
:
void
Constructor
| Name | Type | Description |
|---|---|---|
| $targetUri | string | |
| $responseUri | string | |
| $data | string |
setReplyMethod(
string $methodName
)
:
\Zend_Amf_Value_MessageBody
Set reply method
| Name | Type | Description |
|---|---|---|
| $methodName | string |
| Type | Description |
|---|---|
| \Zend_Amf_Value_MessageBody |
setResponseUri(
string $responseUri
)
:
\Zend_Amf_Value_MessageBody
Set response Uri
| Name | Type | Description |
|---|---|---|
| $responseUri | string |
| Type | Description |
|---|---|
| \Zend_Amf_Value_MessageBody |
setTargetUri(
string $targetUri
)
:
\Zend_Amf_Value_MessageBody
Set target Uri
| Name | Type | Description |
|---|---|---|
| $targetUri | string |
| Type | Description |
|---|---|
| \Zend_Amf_Value_MessageBody |


Cloning vs Immutable
var myself = { name: 'Tom' };
var someoneElse = JSON.parse(JSON.stringify(myself));
myself.name = 'Thomas';
Immutable improves upon this hack with a guarantee and an optimization:
- Immutable's methods like .set() can be more efficient than
cloning because they let the new object reference data in the old object:
only the changed properties differ.
This way you can save memory and performance versus constantly deep-cloning everything.
-
It's nearly impossible to accidentally mutate an Immutable object, and remarkably easy to accidentally forget to clone a normal object.
Immutable objects give a strong guarantee that nowhere does anyone mutate data in-place.


Inter Milan Coach, Conte, Tutors Lukaku, Others How To Have Sex During Season
The former Italy and Chelsea boss told his players that while having sex in the course of the season, they must not last long and also ensure that they stay under their partners.
by SaharaReporters, New York
Head coach of Inter Milan, Antonio Conte, has taught his players how to have sex with their partners in order to stay at their best form on the field of play during the season.
The former Italy and Chelsea boss told his players that while having sex in the course of the season, they must not last long and also ensure that they stay under their partners.
Speaking to L'Equipe in a recent interview, the 50-year-old Italian said, “During the season, I advise my players to have sex for short periods and with the minimum of effort, and better use positions where they are under their partners.
“And preferably, with their wives, because if with others, well, that needs extra action.”


June 2011, five friends and I began our long-weekend holiday of partying for three days. Luckily we all wanted the same experience, and so all had the same pills and powder, MDMA and cocaine.
Fri night: 2 lines of cocaine and alcohol
Sat daytime: 1 MDMA
Sat nighttime: 1 MDMA
Sun nighttime: 1 MDMA
This report is about the after-effects, but wanted to insert a note that I am very experienced with most amphetamines, having partied for 10 years with pills and powder. Accumulated total within the ten years I have probably had between 400-450 extacy pills, and about 20 MDMA capsules that always claimed to be “PURE”. Until this experience I rarely thought about negative impact of MDMA on my body.
Recovery:
Monday all five of us were tired and had very little appetite, which I have come to expect over the years.
Tuesday, we suddenly had feelings of extreme nausea [3 of us puked over 4 times], and what caught us off guard was our dizziness, and “off-balance” feeling. I would describe it as a feeling in my stomach and brain, similar to a fast spot in a rollercoaster at the top of the biggest hill, where your body goes up in the air and your legs are keeping you inside the ride. My stomach went up into my throat and it felt as though gravity was pulling my brain out of the top of my head.
Wednesday, same as Tuesday, and at night I had violent nightmares.
Thursday, most intense day of recovery [day 4] and I took it off work. Worst night of mood, violent nightmares again and soaked sheets when awoke. Visions of devils, ants and bats when I closed my eyes.
Friday, small subsiding of effects: no more nausea, but dizziness and balance still weird.
Saturday, finally felt like my brain was going to recover, and I no longer felt the fear of
Sunday, tried going to the gym and still a bit off balance in heavy lifting so I went back to jog on treadmill.
Monday, today I feel like I’m about 98%, and have sworn off hard core and feeling lucky to have survived this week of hell. This is by far the LONGEST and most violent body recovery from MDMA, and I read about Serotonin poisoning / MDMA overdose and think this might be it. Very little else found on this, so that’s why I’m writing.
Urgent Note: Attempting to “heal” my brain with 5-HTP only made my anxiousness worse and nightmares more intense. Not sure if this was the reason I was unable to sleep.  I slept [tried] for about 9hrs each of the recovery days [Mon-Sat], so the whole week was a write-off. Luckily, all five of us felt the same and so it was comforting that we knew it was the capsules and not something else like environmental factors. I also wanted to say that I got the MDMA from a very reliable source that I had been buying from for 7 years. This post is to encourage readers that if you feel the above – HANG IN THERE, and sleep as much as you can. This was the only thing that seemed to work.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


Scripting language is fun. Right!!
Welcome to my world of programming!
Programming is the simplest thing to do,cool.


Looking for a value in a tree
Consider the following type:
Require Import ZArith.
Inductive Z_btree : Set :=
| Z_leaf : Z_btree
| Z_bnode : Z->Z_btree->Z_btree->Z_btree.
Define a function taking as argument an integer z
and a tree t:Z_btree and returning true iff t
has (at least) an occurrence of z.
Hint
Use the function Zeq_bool to compare two intergers wrt equality.
formula.
Solution
This file
Note: this solution contains also an infix notation
for these formulae.
Suggestion: add propositional variables !


Qpid employs revision control to track and manage changes to its source code.
The Dashboard page provides links to the repository for each individual component. The repositories are all directly viewable, and GitHub mirrors are additionally provided for each.
To access code from one of the Git repositories, use the git clone
command
with its URL, e.g for Qpid JMS:
Qpid JMS
% git clone https://gitbox.apache.org/repos/asf/qpid-jms.git qpid-jms
Alternatively, you can use the mirror repositories available on GitHub to create your own fork.
Consult the install documentation below, or see the respective component documentation for more details.
The traffic on these lists is automatically generated. Please do not post any messages to them.
To subscribe, send an email with subject "subscribe" to the subscribe address. To unsubscribe, send "unsubscribe" to the unsubscribe address.
Alerts for changes committed to the Qpid source.
Alerts for build and test failures from our continuous integration servers.
Apache Qpid, Messaging built on AMQP; Copyright © 2015 The Apache Software Foundation; Licensed under the Apache License, Version 2.0; Apache Qpid, Qpid, Qpid Proton, Proton, Apache, the Apache feather logo, and the Apache Qpid project logo are trademarks of The Apache Software Foundation; All other marks mentioned may be trademarks or registered trademarks of their respective owners


U.S. extends narrow Huawei licences 90 days for remote areas
by Margaret CollinsThe U.S. is extending for another 90 days a limited set of exemptions that lets some American companies continue doing business with Huawei Technologies Co., despite a ban on the Chinese firm.
“The temporary general license extension will allow carriers to continue to service customers in some of the most remote areas of the United States who would otherwise be left in the dark,” Secretary of Commerce Wilbur Ross said in a statement Monday. “The department will continue to rigorously monitor sensitive technology exports to ensure that our innovations are not harnessed by those who would threaten our national security.”
The Commerce Department blacklisted Huawei in May, adding it to what’s known as an entity list. That move was an effort to block U.S. companies from selling components to China’s largest technology firm, which the White House accuses of being a threat to America’s national security. Huawei has denied those claims. The entity listing requires American firms to obtain a government license in order to sell to blacklisted businesses.


My House
$80
3 Guests
1 Bedroom
1 Bathroom
Owner: Robert Downey Jr.
This is a lovely 1 bedroom and 1 bathroom apartment that can accomodate 3 people, it locates at the south side of Central Park, near the subway line.
$80
This is a lovely 1 bedroom and 1 bathroom apartment that can accomodate 3 people, it locates at the south side of Central Park, near the subway line.
$880
This is a 1 bedroom and 1 bathroom house that can accomodate 1 guest, it is a few meters away the Malibu Pier, no subway line near.
$380
This is a cozy 1 bedroom and 1 bathroom apartment that can accomodate 2 people, it is located in the Los Angeles Arts district, near the subway line.


Routines for symmetric eigenvalue problems. Based on the "Meschach Library", available at the anonymous ftp site thrain.anu.edu.au in the directory pub/meschach.
Based on the "Meschach Library", available at the anonymous ftp site thrain.anu.edu.au in the directory pub/meschach.
Alphabetic index HTML hierarchy of classes or Java


I'm A Celebrity fans 'teary' as Ant McPartlin makes his return
He's back!
by Carena CrawfordViewers of I'm A Celebrity...Get Me Out Of Here! were thrilled as Ant and Dec were reunited on this year's show.
Ant took a year off after being arrested for drink driving and going to rehab, so he missed presenting last year's series.
Holly Willoughby made the trip to Australia alongside Dec Donnelly to present in Ant's absence.
But depsite the fact she was hit with fans, it was made very clear it was just temporary and Ant would be returning.
And return he has.
Read more: I'm A Celeb's five most hilarious Bushtucker Trials
Within minutes of the opening title sequence, Ant and Dec were cracking jokes like they'd never been separated - and fans loved it!
Some were even in tears that he was back and looking so well.
Read more: I'm A Celebrity's Nadine Coyle in tears on launch show
The series kicked off tonight with half of the celebs arriving on board a luxury yacht, while the other half were taken by speedboat to a beach.
Viewers at home were most shocked to see Caitlyn Jenner heading into the jungle.
The teams were stunned when the gang on the yacht - Nadine Coyle, Ian Wright, James Haskell, Kate Garraway, and Myles Stephenson - were told they had to swim to the beach in the clothes they were wearing to partner up with someone else.
Those waiting on the beach were Caitlyn, Roman Kemp, Adele Roberts, Jacqueline Jossa, and Andrew Maxwell.
Leave us a comment on our Facebook page @EntertainmentDailyFix and let us know what you think!


County-By-County: The Breakdown Of Where Our International Players Come From
by Gary ConnaughtonIn the past few years, the FAI have made a concerted effort to tap into the wealth of footballing talent that exists around the island of Ireland. The 'FAI Player Development Plan' was published in 2015 with the stated goal of producing elite players from every part of the country, introducing National Development Leagues so top prospects could compete with and against each other on a consistent basis.
Youth football in Ireland had previously centred around Dublin, with the Dublin District Schoolboy League the crown jewel of youth leagues. Talented young players would flock to the capital in order to maximise their potential, with this being seen as the only semi-reliable route to a professional career.
Prior to this, there had been no national youth league in Ireland. The best players from outside Dublin could play in their local area, but their development often stagnated due to a lack of top level coaching and competition.
Considering this, it is not surprising that Dublin natives made up lion's share of our international squads in the past.
However, with the National Development Leagues now offering a genuine path to underage international squads, and eventually first team football at senior level, how has that affected the makeup of the current teams at various age levels?
We have looked at the origins of players in five current international squads, from senior down to U15 level. It paints a very interesting picture.
These players are not only categorised by where they were born, but where they are from and lived most of their lives. It is also worth noting that we are not questioning the 'Irishness' of any players born outside this country.
We broke the players down county-by-county, as well as those who were born in England or other countries. There certainly seems to be a trend developing.
(The players included are based on the most recent squads named at each level.)
Senior Squad
There are a surprising number of English-born players in the senior squad, although most of these would not be considered first choice. David McGoldrick was the only one to start against Denmark. Callum O'Dowda, and Scott Hogan were not even part of the matchday squad.
Dublin still dominates amongst the Irish counties, with the likes of Jeff Hendrick, Matt Doherty, and Troy Parrott hailing from the capital.
John Egan, Alan Browne and co. have contributed to a Cork renaissance. Darren Randolph, Mark Travers, Sean Maguire, and Aaron Connolly were the only representatives from their county.
Seamus Coleman would have ensured Donegal's inclusion if not for his suspension.
U21 Squad
Stephen Kenny recently preached about the diversity within his U21 squad, but it is still largely based around players born in Dublin and England.
Some key members of the team hail from Munster, with Caoimhin Kelleher and Adam Idah from Cork, while Lee O'Connor and Jayson Molumby came through the ranks at Waterford.
Aidan Keena is the only Westmeath man to be part of any of the five squads.
U19 Squad
The U19 squad is the only one in which English-born players are the most well represented group. There are also a number of players from elite English clubs, with Arsenal, Manchester City, and Spurs present.
There are two youngsters who ply their trade outside Ireland or England, with Dublin native Armstrong Okoflex at Celtic and German-born Conor Noss a part of the Borussia Monchengladbach setup.
U17 Squad
Is the makeup of the U17 squad an indication of the impact of the National Development Plan? While Dublin and England are still the best represented, they are less dominant than in other teams.
There is a massive spread of players, seven other counties having a player included, as well as the Spanish born Anselmo Garcia McNulty. Garcia McNulty, who's mother hails from Clare, came through the Real Beits academy before joining Wolfsburg last summer.
U15 Squad
If the U17 team is a nod towards the future, the U15 squad is a return to the norm. Dublin dominate, but it is notable that no English-born players make the cut.
Caden McLaughlin of Malaga was born in Spain, while Rocco Vata was born in Scotland and plays for Celtic. Vata is the son of former Albania and Celtic star Rudi Vata, qualifying through his Irish mother.
Summary
It seems that while the new strategy set forward by the FAI seems to be making an impact, Dublin still produces more players than any other county. It is also worth mentioning that the younger teams tend to have less players born outside of Ireland, and those numbers will likely rise as they progress through the age groups.
In all 17 counties are represented, while our players have been born in four countries apart from Ireland.
Still, it seems we are producing more of our own players than in previous eras. That is certainly something to be encouraged by.


quick conversion of text to templar format
just click on the button below and away you go!
the templar formatted output will appear below:


DfE enquiries
Central newsdesk 020 7783 8300
General enquiries 0370 000 2288
Press release
New baseline designs for new schools are published today, which will see them built more efficiently, sustainably and cheaply.
Every new primary and secondary school to be built more efficiently, sustainably and cheaply in line with new baseline designs announced today, delivering a 30% cost reduction and saving up to £6 million per school compared to Building Schools for the Future (BSF) schools.
The new designs will provide a light, bright and airy learning environment for students and teachers and were drawn up with the advice of environmental, architectural and teaching experts to address problems such as dark corridors, poor ventilation and inadequate classrooms and to make the very best use of space.
Compared to BSF these designs represent a reduction in wasted space - 15% for secondary and five per cent for primary schools - whilst maintaining the same size teaching space, classrooms, staff rooms, sport, and art and design facilities. These new schools will still be bigger than secondary schools built in 2004 and primaries built in 2006.
The BSF programme saw each school designed separately costing unnecessary millions in consultancy fees and often resulting in buildings which overheated and had high energy bills.
Mike Green, Director of Capital at the Education Funding Agency, said:
These designs will ensure that new schools can be built to effective designs and specifications, be simple to maintain and energy efficient. And they can be built far faster than many have previously and for far less money.
Ultimately they will enable as many schools as possible to receive investment from the funding available and deliver an excellent environment for the children and communities they serve.
Advisory groups for the teaching of science, art, design and technology, the performing arts, ICT and libraries advised the Education Funding Agency (EFA) on the design of classrooms and facilities that work best for schools.
Charles Johnston, Property Director at Sport England, said:
Our experts on facilities have been working closely with the Education Funding Agency on the development of these designs. Getting the design right is essential in securing maximum value out of indoor school sports facilities, both for pupils and the local community.
Mhora Samuel, Director at the Theatres Trust, said:
We commend the placing of the theatre at the heart of the new school designs. These are a positive step forward in the planning of theatrical facilities in schools.
Mrs Janet Wilson, head teacher at Ian Ramsey Church of England School, said:
I’m pleased we had the opportunity to work with the proposed designs. They have challenged us to think deeply about our own needs, and helped to clarify our vision for the school we aspire to. We are excited about making the designs a reality.
The designs were commissioned in response to the James Review which called for a set of standardised plans. Contractors can choose to develop these into detailed schemes or propose alternatives; giving schools the freedom to adjust the internal layout to meet the needs of their pupils.
The plans:
The designs have been produced using the same area as new academies and free schools. The majority of BSF schools had much more space than they needed by increasing their intake beyond capacity. Area reductions have been achieved by ensuring that all breakout space - social space, generous corridors and ICT storage - is used to full effect without comprising on teaching space or school organisation.
Initially these examples will be used to finalise briefs for new PFI schools through the Priority Schools Building Programme (PSBP). The first group of schools to be procured through this programme will go out to market shortly.
Each design has been illustrated in a set of plans, sections and internal perspectives, there is accompanying technical reports on environmental design and fire safety. The materials can be found on the Department for Education’s website.
The designs have been tested on a range of school sizes. Following feedback they will be developed further.
Harry Darby, Capital Projects Director at E-ACT, said:
E-ACT is pleased to have seen the initial proposals for the baseline designs and is very supportive of the proposals. This will provide a useful tool for heads planning a new building and considering different options for their academy or school. We are satisfied that the designs offer a clear and uncomplicated approach to providing effective teaching and learning environments. The designs offer many aspects of best practice and we particularly welcome the quality of the ventilation, acoustics and lighting in all of the teaching spaces.
Tricia Adams, Director at the School Library Association, said:
We are delighted that the library is seen as an important part of the new designs.
Richard Green, Chief Executive, Design and Technology Association and Geoff Howard, National Association of Advisers and Inspectors in D&T, said:
Whilst recognising the financial constraints on these designs, they define a minimum baseline provision for design and technology education as an essential component of a 21st century curriculum for all.
Stephen Hockaday, Director of Education Infrastructure at Laing O’Rourke, said:
Laing O’Rourke is pleased that the EFA have clarified their expectations for new schools. We are targeting the new funding rates and are confident in achieving them, making every effort to drive efficiencies through the use of Building Information Modelling (BIM) technology and Design for Manufacture and Assembly to produce schools that perform to the new environmental standards.
John Lawrence, Duty CEO at the Association of Science Education, said:
The ASE welcomes the opportunity to work with the EFA on these designs and endorses them with regards to science labs as a minimum specification for new build schools. The success of such designs in practice will depend on the detailed design of individual projects.
Central newsdesk 020 7783 8300
General enquiries 0370 000 2288
Website: www.education.gov.uk/help/contactus
Published: 2 October 2012


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Week 9
My Webiste
12/21/2015
This week we were supposed to retool our websites a little bit to make them more "professional". Well I still don't have a good picture of myself so I'm keeping my MS paint portrait up on the index page for now. Maybe one day I WILL invest in a professional photographer to make me look dyanamic and competetant. For now it will have to do.
If you've been following my site you probably don't notice much difference between last week and this week. I've gotten pretty attached to my little site design and I didn't want to make any major changes. I'm far from a designer so if someone was to tell me yellow was a bad choice well... I don't know what I would say.It's my favorite color, after all! I did make a few changes "under the hood", especially as to the blog pages, that won't make any difference to the viewer but which makes my pages more consistent and hopefully more readable by assistive technologies.
The process of making a website has obviously taught me a lot about HTML and CSS as well as made me think about what kinds of ways I want to present myself to the world. It's going to continue to be a work in progress.


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@* * Copyright 2023 HM Revenue & Customs * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. *@ @import config.AppConfig @import views.html.helpers.injected.ButtonHelper @this( buttonHelper: ButtonHelper, appConfig: AppConfig ) @(isIndividual: Boolean, saveAndContinueText: Option[String] = None, saveAndReturnReference: Option[String], disabled: Boolean = false)(implicit messages: Messages) @href = @{ if(isIndividual) { controllers.individual.business.routes.ProgressSavedController.show(saveAndReturnReference).url } else { controllers.agent.business.routes.ProgressSavedController.show(saveAndReturnReference).url } }


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Percocet Is Friendly...
As a full-fledged pothead and psychonaut, I am used to experimenting with substances. Altering my consciousness is something that I save for special occasions, however, and before my love affair with percocet I had never really considered trying 'hard' drugs. At this point I had done only the basics: Nicotine, alcohol, psylocibin, THC.
About a year ago I developed multiple kidney stones over the course of a few months.  Passing a kidney stone has been described as 'some of the worst pain the human body can endure and survive.') I was prescribed percocet to take as needed. I didn't like the idea of taking an opiate-because of potential addictiveness--but after passing two stones in three days I was ready for a morphine drip if I could get a hold of it. My prescription said to take one tablet every 6 hours as needed. As I woke with a third stone in the middle of the night (3am) I crawled to the kitchen and retrieved the bottle. Immediately, I downed four (the amount I would have taken in 24 hours).
I didn't feel the percocet hit me at all--it snuck up from behind and crawled into my body with no warning. One minute I was in immense pain, and the next I was blissful and calm, the pain still there but somehow unimportant. I think that I was fully 'high' (though 'dreamy' is a better word) by about 30-45 minutes after I took the pills. I don't really remember the transition very well--my thoughts were jumbled and irrelevant.
I find codeine is a lovely drug (provided you're not allergic, which many people are), and the feelings I felt that night were less of a dulling of pain than a total forgetfulness of any bodily sensation. My speech became slurred, and when my mother woke up to get ready for work at 6am (I was home from college for the summer), three hours after I had taken the pills, I was giggling happily while watching the cartoon network. She told me later that there was a small trail of drool streaming from my chin, but I don't remember this.
I started to come down around noon, and as I felt the drug wear off my body was exhausted and I felt sweaty and itchy (codeine makes me really really itchy all over). Also, the pain was returning, and nausea was on its way. I was home alone at this point, and the stabbing agony in my back--which was traveling slowly down to my bladder--was nearly unbearable. I sat on the floor of my bathroom, my legs wobbly and cold on the tiles, my head resting miserably on the toilet seat. It occurred to me that I still had 8 more percocet in the bottle, and I thought, what the hell, I don't have to work today. The come-down was getting more and more intense, and I started to think I might throw up. Also, I was starting to cry, for no apparent reason. Panicked, I went into the kitchen and took two more.
I should note here that even as I took the second dose of pills I felt the percocet coming back on...I found the drug's effects comes in waves, and this is one reason it's so dangerous.
By 1pm I was stoned out of my mind; I remember going to make food in the kitchen and laughing hysterically at the fact that I was nauseated and that my back hurt. There was no real euphoria, just a calm, tranquil, wise feeling. I felt like a jolly old gnome. I felt untouchable. I thought I was an angel and could save the world. I vowed on the spot to get my prescription re-filled (though the bottle said in huge letters no refills), inventing more kidney stones if necessary. Life was grand and I was queen.
I got addicted--I really did have several more kidney stones that summer (one kidney is almost entirely useless now), and getting my prescription filled again and again was easy because my physician was a friend of the family and my ivp's (intravenous pigmentation--iodine dye is shot into your veins and your urinary tract is x-rayed) showed that I did indeed have more stones on the way. By the end of the summer (2 months after my first percocet adventure), I was fully hooked. I took percocet to work, popping pills throughout the day as I tended bar and in the car on the way home. My standard routine was: 2 Pills upon waking, 2 pills by noon, 2 pills after dinner, 2 pills before bed.
I was functional--surprisingly so--but my health was in shambles. I couldn't escape the fact that if I didn't get my constant percocet fixes, I was so nauseated that eating was unthinkable and sleep wouldn't come for hours. The stones hurt, yeah, but they didn't hurt that badly. I knew I shouldn't be taking so much percocet. Finally, one night I caught myself wishing for the drugs to work faster and actually chewing a pill whole (it was so bitter) right before a party. At that moment I realized that the drug was controlling my life. My mother was getting very suspicious, and my friends didn't really like to hang out anymore because all I wanted to do was take percocet and watch tv or listen to quiet music. I stopped going out, forgot to shower, and eventually lost my job. I woke up one day--broke, alone, and feeling like shit--and realized that if I didn't quit soon I wouldn't make it out alive.
So, I stopped. The stones were agony, but I smoked a lot of weed, and in a way it seemed to help more than the codeine because the come-down wasn't nearly as rough. The withdrawal symptoms were awful--I wouldn't wish them on anyone...Constant nausea, headaches, tremors, cold sweats, diarrhea, intense disorientation, irregular heart beat, trouble breathing. Eventually they went away, though, and now I can say that since I quit cold turkey I haven't gone back. It's tempting sometimes, but I find that cannabis and an after-bowl cigarette really help curb the urge.
One last thing: Never drive while or after taking percocet, and don't ever mix it with alcohol. I learned this the hard way when I woke up vomiting in my friend's car after having a glass of wine in a restaurant. The drug is nice, it's friendly, but it's also very possessive and likes to win. Don't let it--it's just an addiction, and if you want to badly enough, you will get through it. Friends, light foods, lots of cool water to drink, and calming music in a dark room are a great way to get through withdrawal.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


James Salamonsen
GitHub
Medium
Linkd-in
Prepare to Fight
LAMMA
Self Destruct
Unicorn
Defend Castle
Marioish
[a = punch]
[s = block]
[d = kick]
[arrows to move]


Skills/Programs I've Learned From This Course
Git Hub: GitHub, a subsidiary of Microsoft, is a web-based hosting service for version control using Git. It is mostly used for computer code. Through this service, we learned the basic fundamentals of github to know what its like to work on coding projects as a team. Some of the skills I learned are; Making repositories Commits Pushes. Git is also a version control systems which helps with the tracking of code changes.
Linux: Linux is a family of open source Unix-like operating systems based on the Linux kernel, an operating system kernel first released on September 17, 1991 by Linus Torvalds. Linux is typically packaged in a Linux distribution.


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