Internet Topology

Traceroute is one of the most famous and widely adopted diagnostic  tool for
omputer networks. Although tra
eroute is often used
to infer links between Autonomous Systems (ASes), the presen
e of the
so-
alled third-party (TP) addresses may indu
e the inferen
e of false
AS-level links. In this paper, we propose a novel a
tive probing te
hnique based on the IP timestamp option able to identify TP addresses.
For evaluating both the appli
ability and the utility of the proposed
te
hnique, we perform a large-s
ale measurement
ampaign targeting 
from multiple vantage points  more than 327K destinations belonging
to about 14K ASes. The results show how TP addresses are very
ommon and ae
t about 17% of AS-level links extra
ted from tra
eroute
tra
es. Compared to a previously proposed heuristi
method, our te
hnique allows to identify many more TP addresses and to re-interpret part
of its results.

The study of network topology has attracted a great deal of attention in the last decade, but has been hampered by a lack of accurate data. Existing methods for measuring topology have flaws, and arguments about the importance of these have overshadowed the more interesting questions about network structure. The Internet Topology Zoo is a store of network data created from the information that network operators make public. As such it is the most accurate large-scale collection of network topologies available, and includes meta-data that couldn't have been measured. With this data we can answer questions about network structure with more certainty than ever before -we illustrate its power through a preliminary analysis of the PoP-level topology of over 140 networks. We find a wide range of network designs not conforming as a whole to any obvious model.

The Internet's layered architecture and organizational structure give rise to a number of different topologies, with the lower layers defining more physical and the higher layers more virtual/logical types of connectivity structures. These structures are very different, and successful Internet topology modeling requires annotating the nodes and edges of the corresponding graphs with information that reflects their network-intrinsic meaning. These structures also give rise to different representations of the traffic that traverses the heterogeneous Internet, and a traffic matrix is a compact and succinct description of the traffic exchanges between the nodes in a given connectivity structure. In this paper, we summarize recent advances in Internet research related to (i) inferring and modeling the router-level topologies of individual service providers (i.e., the physical connectivity structure of an ISP, where nodes are routers/switches and links represent physical connections), (ii) estimating the intra-AS traffic matrix when the AS's router-level topology and routing configuration are known, (iii) inferring and modeling the Internet's AS-level topology, and (iv) estimating the inter-AS traffic matrix. We will also discuss recent work on Internet connectivity structures that arise at the higher layers in the IP/TCP protocol stack and are more virtual and dynamic; e.g., overlay networks like the WWW graph, where nodes are web pages and edges represent existing hyperlinks, or P2P networks like Gnutella, where nodes represent peers and two peers are connected if they have an active network connection. Here, an autonomous system (AS) or autonomous domain is a group of routers and networks managed by a single organization. In turn, an Internet Service Provider (ISP) can consist of a single AS or of a group of ASes, but for simplicity, we will use the terms AS and ISP indistinguishably throughout this paper. The TCP/IP protocol stack as a whole and IP in particular are able to hide from the user much of the enormous complexity associated with controlling this diverse set of networked resources and coordinating the actions among the many competing ISPs. By providing the mechanisms necessary to knit together diverse networking technologies and ASes into a single virtual network (i.e., a network of networks, or "Internet"), they ultimately guarantee seamless connectivity and reliable communication between sending and receiving hosts, irrespective of where in the network they are.

Studies of the Internet have typically focused either on the routing system, i.e. the paths chosen to reach a given destination, or on the evolution of traffic on a physical link. In this paper, we combine routing and traffic, and study for the first time the evolution of the traffic on the Internet topology. We rely on the traffic and routing data of a large transit provider, spanning almost a month. We compute distances between the traffic graph over small and large timescales. We find that the global traffic distribution on the AS graph largely differs from traffic observed at small timescales. However, variations between consecutive time periods are relatively limited, i.e. the topology spanned by the traffic from one time period to the next is small. This difference between local and global traffic distribution is found in the timescales at which traffic dynamics occurs on AS-level links. Small timescales, i.e. less than a few hours, do not account for a significant fraction of the traffic dynamics. Most of the traffic variability is concentrated at timescales of days. Models of Internet traffic on its topology should thus focus on capturing the long-term changes in the global traffic pattern.

Characterizing the evolution of Internet topology is important to our understanding of the Internet architecture and its interplay with technical, economic and social forces. A major challenge in obtaining empirical data on topology evolution is to identify real topology changes from the observed topology changes, since the latter can be due to either topology changes or transient routing dynamics. In this paper, we formulate the topology liveness problem and propose a solution based on the analysis of BGP data. We find that the ...

Abstract: Internet scale DoS attack is a new evolution of conventional flooding DoS attack with the inspiration of shutting down the Internet due to its vulnerable infrastructure. Past DoS attacks directly attacked the victim, usually a single host. Consequently, defences were designed to identify the excessive traffic or filter illegitimate traffic. From the early two thousand, Internet scale DoS attacks started to appear. They aimed to disable highly connected routers or large links with a legitimate action in the form of low-rate traffic or high-rate wanted traffic with protocol messages that are unfiltered by congestion control. The latter can be more devastating due to its global impact therefore attracts the attention of researchers and some applications are now available. The goal of this paper is to introduce Internet scale DoS attack and to survey its theoretical underpinnings and experimental applications. Several attacking techniques will be presented, as well as their ef...

One of the challenging problems related with network topology discovery in Internet is the process of IP address alias identification. Topology information is usually obtained from a set of traceroutes that provide IP addresses of routers in the path from a source to a destination. If these traceroutes are repeated between several source/destination pairs we can get a sampling of all IP addresses for crossed routers. In order to generate the topology graph in which each router is a node, it is needed to identify all IP addresses that belong to the same router. In this work we propose improvements over existing methods to obtain alias identification related mainly with the types and options in probing packets.

Recent works on modeling the Internet topology (8, 9) have highlighted how the complexity of relationships be- tween Autonomous Systems (ASes) can not be oversimpli- fied without sacrificing accuracy in capturing route selec- tion. Such a shortcoming can mislead the understanding, hence the prediction, of the BGP (Border Gateway Proto- col) behavior. In particular, models that assume an AS to

We show that random graphs in the preferential connectivity model have constant conductance, and hence have worst-case routing congestion that scales logarithmically with the number of nodes. Another immediate implication is constant spectral gap between the first and second eigenvalues of the random walk matrix associated with these graphs. We also show that the expected frugality (overpayment in the Vickrey-Clarke-Groves mechanism for shortest paths) of a random graph is bounded by a small constant.

In last years new procedures to generate Internet-like topologies have been proposed, stemming from the evidence of a power-law behavior of real networks. Realistic networks generators are necessary for simulation and performance evaluation of data communication systems. Assuming a simple loss model for the links, the present investigation shows that the adoption of a specific topological model for the Internet graph (here, the Waxman or the Barabási-Albert model) may affect, to a certain extent, the estimates of the loss probabilities for end-to-end communications obtained by simulation (e.g. via NS-2 package).

The expansion of the Internet routing system results in a number of research challenges, in particular, the Border Gateway Protocol (BGP) starts to show its limits a.o. in terms of the number of routing table entries it can dynamically process and control. Dynamic routing protocols showing better scaling properties are thus under investigation. However, because deploying under-development routing protocols on the Internet is not practicable at a largescale (due to the size of the Internet topology), simulation is an unavoidable step to validate the properties of a newly proposed routing scheme. Unfortunately, the simulation of inter-domain routing protocols over large networks (order of tens of thousands of nodes) poses real challenges due to the limited memory and computational power that computers impose. This paper presents the Dynamic Routing Model simulator DRMsim which addresses the specific problem of large-scale simulations of (inter-domain) routing models on large networks. The motivation for developing a new simulator lies in the limitation of existing simulation tools in terms of the number of nodes they can handle and in the models they propose.

This paper proposes a novel non-parametric technique for clustering networks based on their structure. Many topological measures have been introduced in the literature to characterize topological properties of networks. These measures provide meaningful information about the structural properties of a network, but many networks share similar values of a given measure . Furthermore, strong correlation between these measures occur on real-world graphs [2], so that using them to distinguish arbitrary graphs is difficult in practice .

In the past few years numerous peer to peer file sharing, or, more generally, content distribution, systems have been designed, implemented, and evaluated via simulations, real world measurements or even mathematical analysis. Yet, only a few of them have stood the test of time, managing to gain wide user acceptance. BitTorrent is not just one such system; it holds the lion's share among them. The reasons behind its success have been studied to a great extent with interesting results. Nevertheless, even though peer to peer content distribution remains one of the most active research areas, little progress has been made towards the study of the Bit-Torrent protocol and its possible variations in a fully controllable but realistic simulation environment. In this paper we present a full featured and extensible implementation of BitTorrent for the OMNeT++ simulation environment. Moreover, since we aim to establish a realistic simulation platform, we present our conversion tool for a popular Internet topology generator and a churn generator module based on the analysis of real BitTorrent traces.

The Internet topology data collected through traceroute exploration has been extensively studied in the past. In particular, a remarkable property of the Internet, the power-law shape of node degree distribution, drew the attention of the research community. Several studies have since questioned this property. In this paper, based on a large dataset collected using mrinfo, we show that the node degree distribution is strongly impacted by the presence of layer-2 (L2) networks, such as switches. L2 devices interconnect a large number of routers, themselves being also involved in multiple L2 interconnections. Such a situation induces nodes with very high degree when analyzing the layer-3 (L3) graph with traceroute probing. Considering the physical design of a network, our analysis provides a lower bound on the bias generated by using only an L3 view. We also provide a model that can be a first step towards L2 aware topology generation.

We consider the Internet at the level of its sub-networks (called Autonomous Systems, or ASes). Most previous studies have used the connection degree as the indicator variable to decompose the network into what one hopes will be nodes with distinct functions

A growing number of applications create overlays on top of the Internet. Several unsolved issues at the network layer can explain this trend to implement network services such as multicast, mobility and security at the application layer. However overlays require some form of internal addressing, routing and naming. Therefore their topologies are usually kept simple but this limits their flexibility and scalability. Our aim is to design an efficient and robust addressing, routing and naming framework for complex overlays. Our only assumption is that they are constrained by the Internet topology. Applications using our framework will be relieved from managing their own overlay topologies. This paper presents our framework in detail as well as some performance results concerning its routing efficiency, its reliability to network dynamics and its naming scalability.

The study of the Internet topology allows us to discover properties that can be exploited in order to improve the performance of network protocols and applications. Thus, Internet mapping is very useful to simulation software focusing on network protocols. Unfortunately Internet mapping has two major drawbacks. First it takes a lot of time to be carried out and secondly it is often incomplete. To solve these two problems, we have developed a mapping software whose aim is to map the heart of the Internet as fast as possible with the highest possible accuracy. In this paper, we describe our software and evaluate its performance compared to an existing and freely available mapping software. We assess the completeness of the router level maps by creating overlays with an autonomous system topology. We also study the scalability of the mapping techniques of our software by carrying out an extensive data collection. We show that some limitations concerning the amount of useful information do appear when we try to carry out an exhaustive mapping. Finally, we study the path inflation phenomenon caused by the routing protocols. q 2004 Published by Elsevier B.V.

Internet measurement studies require availability of representative topology maps. Depending on the map resolution (e.g., autonomous system level or router level), the procedure of collecting and processing an Internet topology map involves different tasks. In this paper, we present a new task, i.e., subnet inference, to advance the current state of the art in topology collection studies. Utilizing a technique to infer the subnet relations among the routers in the resulting topology map, we identify IP addresses that are connected over the same connection medium. We believe that the successful inclusion of subnet relations among the routers will yield topology maps that are closer, at the network layer, to the sampled segments of the Internet in router level topology measurement studies.

Formally, the Internet inter-domain routing system is a collection of networks, their policies, peering relationships and organizational affiliations, and the addresses they advertize. It also includes components like Internet exchange points. By its very definition, each and every aspect of this system is impacted by BGP, the de-facto standard inter-domain routing protocol.

It has been observed that the degrees of the topologies of several communication networks follow heavy tailed statistics. What is the impact of such heavy tailed statistics on the performance of basic communication tasks that a network is presumed to support? How does performance scale with the size of the network? We study routing in families of sparse random graphs whose degrees follow heavy tailed distributions. Instantiations of such random graphs have been proposed as models for the topology of the Internet at the level of Autonomous Systems as well as at the level of routers. Let n be the number of nodes. Suppose that for each pair of nodes with degrees du and dv we have O(dudv) units of demand. Thus the total demand is O(n 2 ). We argue analytically and experimentally that in the considered random graph model such demand patterns can be routed so that the flow through each link is at most O n log 2 n . This is to be compared with a bound Ω n 2 that holds for arbitrary graphs. Similar results were previously known for sparse random regular graphs, a.k.a. "expander graphs." The significance is that Internet-like topologies, which grow in a dynamic, decentralized fashion and appear highly inhomogeneous, can support routing with performance characteristics comparable to those of their regular counterparts, at least under the assumption of uniform demand and capacities. Our proof uses approximation algorithms for multicommodity flow and establishes strong bounds of a generalization of "expansion," namely "conductance." Besides routing, our bounds on conductance have further implications, most notably on the gap between first and second eigenvalues of the stochastic normalization of the adjacency matrix of the graph.

We introduce and use k-shell decomposition to investigate the topology of the Internet at the AS level. Our analysis separates the Internet into three sub-components: (a) a nucleus which is a small (≈ 100 nodes) very well connected globally distributed subgraph; (b) a fractal sub-component that is able to connect the bulk of the Internet without congesting the nucleus, with self similar properties and critical exponents; and (c) dendrite-like structures, usually isolated nodes that are connected to the rest of the network through the nucleus only. This unique decomposition is robust, and provides insight into the underlying structure of the Internet and its functional consequences. Our approach is general and useful also when studying other complex networks.

A significant challenge for researchers analysing the Internet AS-level topology graph is how to interpret the global organization of the graph as the coexistence of its structural blocks (communities) associated with more highly interconnected parts. While a huge number of papers have already been published on the issue of community detection, very little attention has so far been devoted to the discovery and interpretation of Internet communities at the various levels of abstractions. We believe that by discovering and interpreting a priori these unknown building blocks (i.e. communities), this will then pave the way for new types of analysis which are crucial in understanding of the structural and functional properties of the Internet at least at the AS level of abstraction. We thus propose a novel type of analysis of the Internet AS-level topology graph by exploiting the k-clique community definition. First, we show that detected communities can be described by a tree representation. Then we show the presence of two classes of k-clique communities: those that are strictly affected by the nesting process which is embedded in the k-clique community definition, and, on the other hand, those that appear as branches in the tree. We conclude our analysis by highlighting the properties that characterize k-clique communities with different k values by exploiting both geographical data and information related to IXPs.

Since the nineties, the Internet has seen an impressive growth, in terms of users, intermediate systems (such as routers), autonomous systems, or applications. In parallel to this growth, the research community has been looking for obtaining and modeling the Internet topology, i.e., how the various elements of the network interconnect between themselves. An impressive amount of work has been done regarding how to collect data and how to analyse and model it. This chapter reviews main approaches for gathering Internet topology data. We first focus on hop limited probing, i.e., traceroute-like probing. We review large-scale tracerouting projects and discuss traceroute limitations and how they are mitigated by new techniques or extensions. Hop limited probing can reveal an IP interface vision of the Internet. We next focus on techniques for aggregating several IP interfaces of a given router into a single identifier. This leads to a router level vision of the topology. The aggregation can be done through a process called alias resolution. We also review a technique based on IGMP probing that silently collect all multicast interfaces of a router into a single probe. We next refine the router level topology by adding subnet information. We finish this chapter by discussing the AS level topology, in particular the relationships between ASes and the induced hierarchy.

Traceroute is widely used, from the diagnosis of network problems to the assemblage of internet maps. Unfortunately, there are a number of problems with traceroute methodology, which lead to the inference of erroneous routes. This paper studies particular structures arising in ...

One of the primary challenges facing scalable network emulation and simulation is the overhead of storing network-wide routing tables or computing appropriate routes on a per-packet basis. We present an approach to routing table calculation and storage based on spanning tree construction that provides an order of magnitude reduction in routing table size for Internet-like topologies. In our approach, we maintain a variable number of spanning trees for a given topology and choose the path between two hosts in each tree, choosing the shortest. We also populate offline a negative cache of actual shortest paths for source-destination pairs-typically a few percent of the total-where the lookups result in sub-optimal routes. We have implemented our technique in a popular network emulator, ModelNet, and show that our enhanced version can emulate Internet topologies 10-100 times larger than previously possible.

Internet worm spread is a phenomenon involving millions of hosts, who interact in complex and diverse environment. Scanning speed of each infected host depends on its resources and the defenses at work in its network. Aggressive worms further interact with the underlying Internet topology − the dynamics of the spread is constrained by the limited bandwidth of network links, and high-volume scan traffic leads to BGP router failure thus affecting global routing. Worm traffic also interacts with legitimate background traffic competing for (and often winning) the limited bandwidth resources. To faithfully simulate worm spread and other Internet-wide events such as DDoS, flash crowds and spam we need a detailed Internet model, a packet-level simulation of relevant event features, and a realistic model of background traffic on the whole Internet. The memory and CPU requirements of such simulation exceed a single machine's resources, creating a need for distributed simulation. We propose a design and present implementation of a distributed worm simulator, called PAWS. PAWS runs on Emulab testbed, which facilitates its use by other researchers. We validate PAWS in a variety of scenarios, and evaluate costs and benefits of distributed worm simulation.

Effective engineering of the Internet is predicated upon a detailed understanding of issues such as the large-scale structure of its underlying physical topology, the manner in which it evolves over time, and the way in which its constituent components contribute to its overall function. Unfortunately, developing a deep understanding of these issues has proven to be a challenging task, since it in turn involves solving difficult problems such as mapping the actual topology, characterizing it, and developing models that capture its emergent behavior. Consequently, even though there are a number of topology models, it is an open question as to how representative the topologies they generate are of the actual Internet. Our goal is to produce a topology generation framework which improves the state of the art and is based on design principles which include representativeness, inclusiveness, and interoperability. Representativeness leads to synthetic topologies that accurately reflect many aspects of the actual Internet topology (e.g. hierarchical structure, degree distribution, etc.). Inclusiveness combines the strengths of as many generation models as possible in a single generation tool. Interoperability provides interfaces to widely-used simulation and visualization applications such as ns and SSF. We call such a tool a universal topology generator.

Despite the apparent randomness of the Internet, we discover some surprisingly simple power-laws of the Internet topology. These power-laws hold for three snapshots of the Internet, between November 1997 and December 1998, despite a 45% growth of its size during that period. We show that our power-laws fit the real data very well resulting in correlation coefficients of 96% or higher.

In this paper, we perform the first comprehensive study of the multicast address allocation problem. We analyze this problem both within its context as a classic resource allocation problem and with respect to its practical use for multicast address assignment. We define a framework for the problem, introduce complexity results, and formulate several new allocation algorithms. Despite the theoretical superiority of these algorithms, our performance evaluation demonstrates that a common, prefix-based algorithm is better under a range of workloads. We conclude by illustrating the conditions under which dynamic address allocation should be used and provide insight into how to further improve the performance of prefix-based allocation.

The paper presents the research results of multicast heuristic algorithms. The paper is an extension of previous publications presented in [14, 15] that discussed small network structures reflecting real Internet topology. It approaches basic methods of generating the Internet topology - Waxman method and the Barabasi-Albert method. A performance study of multicast trees constructed by the algorithms is carried out and analysed, also with the heuristic network generator - Inet.

Overlay networks among cooperating hosts have recently emerged as a viable solution to several challenging problems, including multicasting, routing, content distribution, and peer-topeer services. Application-level overlays, however, incur a performance penalty over router-level solutions. This paper quantifies and explains this performance penalty for overlay multicast trees via: 1) Internet experimental data; 2) simulations; and 3) theoretical models. We compare a number of overlay multicast protocols with respect to overlay tree structure, and underlying network characteristics. Experimental data and simulations illustrate that the mean number of hops and mean per-hop delay between parent and child hosts in overlay trees generally decrease as the level of the host in the overlay tree increases. Overlay multicast routing strategies, overlay host distribution, and Internet topology characteristics are identified as three primary causes of the observed phenomenon. We show that this phenomenon yields overlay tree cost savings: Our results reveal that the normalized cost ( ) ( ) is 0 9 for small , where ( ) is the total number of hops in all overlay links, ( ) is the average number of hops on the source to receiver unicast paths, and is the number of members in the overlay multicast session. This can be compared to an IP multicast cost proportional to 0 6 to 0 8 . Index Terms-Economies of scale, group communication, Internet multicast, overlay multicast, overlay networks.

This paper investigates the assignment of audio mixing operations to a geographically distributed set of servers to provide an immersive audio communication environment for massively multiplayer online games. The immersive audio communication service enables each avatar to hear a realistic audio mix of the conversations in its audible range. There are three primary delivery architectures for this service, namely, peer-to-peer, central server and distributed servers. We focus on the distributed server architecture, which partitions the virtual world into regions or locales and then assigns the computation associated with the creation of audio scenes for all avatars in each locale to a server. Our aim is to find the optimal way to partition the virtual world into locales and then choose the locale servers in such a way that reduces the total delay perceived by all avatars. We have produced a mathematical formulation for the optimal partitioning and server assignment and developed a heuristics approach based on a graph algorithm. We have developed a simulation environment that creates both the physical world (geographic distribution of participants and the Internet topology model) and the virtual world (distribution of avatars based on different avatar aggregation behaviors). We have solved the problem exactly as well as using the heuristics algorithm for a range of simulated virtual and physical worlds. In many cases, the heuristics results were within 5% of the optimal. Our algorithms and simulation study will be of benefit to future immersive audio communication service providers in the design of a cost effective delivery architecture for this service.

Several emerging large-scale Internet applications such as Content Distribution Networks, and Peer-to-Peer networks could potentially benefit from knowing the underlying Internet topology and the distances (i.e., round-trip-time) between different hosts. Most existing techniques for distance estimation either use a dedicated infrastructure or use on-line measurements in which probe packets are injected into the network during estimation. Our goal in this paper is to study off-line techniques for distance estimation that do not require a dedicated infrastructure. To this end, we propose a metric termed ''depth'' and we observe that together with a quadratic function on the geographic distance, it can predict the network distance with high accuracy using multi-variable regression. When used for closest server selection, our approach performs much better than random server selection, and similar to the on-line metrics. Our approach incurs low overhead and can be deployed easily with some DNS extensions.

This paper proposes several clustering algorithms to explore the topology of the AS-graph. Using these algorithms, we are able to view the Internet topology, as encapsulated by the AS-graph, at three levels of abstraction: (1) a low-resolution view, which shows a coarse cluster cover of the whole AS-graph, (2) a mid-resolution view, showing the relationships between dense cores inside the coarse clusters, and (3) a high-resolution view of individual highdensity cores.

In the past few years numerous peer to peer file sharing, or, more generally, content distribution, systems have been designed, implemented, and evaluated via simulations, real world measurements or even mathematical analysis. Yet, only a few of them have stood the test of time, managing to gain wide user acceptance. BitTorrent is not just one such system; it holds the lion's share among them. The reasons behind its success have been studied to a great extent with interesting results. Nevertheless, even though peer to peer content distribution remains one of the most active research areas, little progress has been made towards the study of the Bit-Torrent protocol and its possible variations in a fully controllable but realistic simulation environment. In this paper we present a full featured and extensible implementation of BitTorrent for the OMNeT++ simulation environment. Moreover, since we aim to establish a realistic simulation platform, we present our conversion tool for a popular Internet topology generator and a churn generator module based on the analysis of real BitTorrent traces.

Hermes is a system for exploring and visualizing Autonomous Systems and their interconnections. It relies on a three-tiers architecture, on a large repository of routing information coming from heterogeneous sources, and on sophisticated graph drawing engine. Such an engine exploits static and dynamic graph drawing techniques.

As the Internet evolves, and new bandwidth-consuming multimedia applications become more common, it becomes necessary to provide quality of service (QoS) in the Internet. QoS provides a basis for network providers to offer a variety of services to customers with different cost, bandwidth, latency, and jitter requirements, which makes the network resources more valuable. To utilize valuable network resources efficiently, service providers need to engineer intra-domain and inter-domain traffic. In this dissertation we are addressing the inter-domain traffic engineering problem with emphasis on inter-domain QoS routing, which is the most important component of traffic engineering. This dissertation introduces a novel inter-domain QoS routing scheme that can scale over large networks. Our scheme is based on the notion of regions, which are collections of autonomous systems, and we represent the overall Internet topology as a collection of regions. Without introducing a hierarchy, we emp...

The expansion of the Internet routing system results in a number of research challenges, in particular, the Border Gateway Protocol (BGP) starts to show its limits a.o. in terms of the number of routing table entries it can dynamically process and control. Dynamic routing protocols showing better scaling properties are thus under investigation. However, because deploying under-development routing protocols on the Internet is not practicable at a largescale (due to the size of the Internet topology), simulation is an unavoidable step to validate the properties of a newly proposed routing scheme. Unfortunately, the simulation of inter-domain routing protocols over large networks (order of tens of thousands of nodes) poses real challenges due to the limited memory and computational power that computers impose. This paper presents the Dynamic Routing Model simulator DRMsim which addresses the specific problem of large-scale simulations of (inter-domain) routing models on large networks. The motivation for developing a new simulator lies in the limitation of existing simulation tools in terms of the number of nodes they can handle and in the models they propose.

We present a general model of interdomain route selection to study interdomain traffic engineering. In this model, the routing of multiple destinations can be coordinated. Thus the model can capture general traffic engineering behaviors such as load balancing and link capacity constraints. We first identify potential routing instability and inefficiency of interdomain traffic engineering. We then derive a sufficient condition to guarantee convergence. We also show that the constraints on local policies imposed by business considerations in the Internet can guarantee stability without global coordination. Using realistic Internet topology, we evaluate the extent to which routing instability of interdomain traffic engineering can happen when the constraints are violated

Many contributions rely on the degree distribution of the Internet topology. However, current knowledge of this property is based on biased and erroneous measurements and is subject to much debate. Recently, in [7], a new approach, referred to as the Neighborhood Flooding method, was proposed to avoid issues raised by classical measurements. It aims at measuring the neighborhood of Internet core routers by sending traceroute probes from many monitors distributed in the Internet towards a given target router. In this paper, we investigate the accuracy of this method with simulations. Our results show that Neighborhood Flooding is free from the bias highlighted in the classical approach and is able to observe properly the exact degree of a vast majority of nodes in the core of the network. We show how the quality of the estimation depends on the number of monitors used and we carefully examine the influence of parameters of the simulations on our results. We also point out some limitations of the Neighborhood Flooding method and discuss their impact on the observed distribution.

Overlay networks among cooperating hosts have recently emerged as a viable solution to several challenging problems, including multicasting, routing, content distribution, and peer-to-peer services. Application-level overlays, however, incur a performance penalty over router-level solutions. This paper characterizes this performance penalty for overlay multicast trees via experimental data, simulations, and theoretical models. Experimental data and simulations illustrate that (i) the average delay and the number of hops between parent and child hosts in overlay trees generally decrease, and (ii) the degree of hosts generally decreases, as the level of the host in the overlay tree increases. Overlay multicast routing strategies, together with powerlaw and small-world Internet topology characteristics, are causes of the observed phenomena. We compare three overlay multicast protocols with respect to latency, bandwidth, router degrees, and host degrees. We also quantify the overlay tree cost. Results reveal that Ä´Òµ

Existing empirical studies of Internet structure and path properties indicate that the Internet is tree-like. This work quantifies the degree to which at least two important Internet measures-latency and bandwidth-approximate tree metrics. We evaluate our ability to model end-to-end measures using tree embeddings by actually building tree representations. In addition to being simple and intuitive models, these trees provide a range of commonly-required functionality beyond serving as an analytical tool.

We show that random graphs in the preferential connectivity model have constant conductance, and hence have worst-case routing congestion that scales logarithmically with the number of nodes. Another immediate implication is constant spectral gap between the first and second eigenvalues of the random walk matrix associated with these graphs. We also show that the expected frugality (overpayment in the Vickrey-Clarke-Groves mechanism for shortest paths) of a random graph is bounded by a small constant.

This paper investigates the assignment of audio mixing operations to a geographically distributed set of servers to provide an immersive voice communication environment for massively multi-player online games. The immersive voice communication service enables each avatar to hear a spatially accurate audio mix of the conversations in its hearing range. There are three primary delivery architectures for this service, namely, peerto-peer, central server, and distributed servers. We focus on a distributed server architecture, which partitions the virtual world into regions or locales and then assigns the computation associated with the creation of audio scenes for all avatars in each locale to a server. Our aim is to find the optimal way to partition the virtual world into locales and then choose the locale servers in such a way that reduces the total delay perceived by all avatars.

Despite recent excitement generated by the peer-to-peer (P2P) paradigm and the surprisingly rapid deployment of some P2P applications, there are few quantitative evaluations of P2P systems behavior. The open architecture, achieved scale, and self-organizing structure of the Gnutella network make it an interesting P2P architecture to study. Like most other P2P applications, Gnutella builds, at the application level, a virtual network with its own routing mechanisms. The topology of this virtual network and the routing mechanisms used have a significant influence on application properties such as performance, reliability, and scalability. We have built a "crawler" to extract the topology of Gnutella's application level network. In this paper we analyze the topology graph and evaluate generated network traffic. Our two major findings are that: (1) although Gnutella is not a pure power-law network, its current configuration has the benefits and drawbacks of a power-law structure, and (2) the Gnutella virtual network topology does not match well the underlying Internet topology, hence leading to ineffective use of the physical networking infrastructure. These findings guide us to propose changes to the Gnutella protocol and implementations that may bring significant performance and scalability improvements. We believe that our findings as well as our measurement and analysis techniques have broad applicability to P2P systems and provide unique insights into P2P system design tradeoffs.