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11
Network Topology Generators: DegreeBased vs. Structural
, 2002
"... Following the longheld belief that the Internet is hierarchical, the network topology generators most widely used by the Internet research community, TransitStub and Tiers, create networks with a deliberately hierarchical structure. However, in 1999 a seminal paper by Faloutsos et al. revealed tha ..."
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Cited by 207 (17 self)
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Following the longheld belief that the Internet is hierarchical, the network topology generators most widely used by the Internet research community, TransitStub and Tiers, create networks with a deliberately hierarchical structure. However, in 1999 a seminal paper by Faloutsos et al. revealed that the Internet's degree distribution is a powerlaw. Because the degree distributions produced by the TransitStub and Tiers generators are not powerlaws, the research community has largely dismissed them as inadequate and proposed new network generators that attempt to generate graphs with powerlaw degree distributions.
Using the SmallWorld Model to Improve Freenet Performance
, 2002
"... Efficient data retrieval in a peertopeer system like Freenet is a challenging problem. In this paper we study the impact of cache replacement policy on the performance of Freenet. We find that, with Freenet's LRU cache replacement, there is a steep reduction in the hit ratio with increasing ..."
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Cited by 97 (0 self)
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Efficient data retrieval in a peertopeer system like Freenet is a challenging problem. In this paper we study the impact of cache replacement policy on the performance of Freenet. We find that, with Freenet's LRU cache replacement, there is a steep reduction in the hit ratio with increasing load. Based on intuition from the smallworld models and the recent theoretical results by Kleinberg, we propose an enhancedclustering cache replacement scheme for use in place of LRU. Such a replacement scheme forces the routing tables to resemble neighbor relationships in a smallworld acquaintance graph  clustering with light randomness. In our simulation this new scheme improved the request hit ratio dramatically while keeping the small average hops per successful request comparable to LRU. A simple, highly idealized model of Freenet under clustering with light randomness proves that the expected message delivery time in Freenet is O(1Og 2 / ) if the routing tables satisfy the smallworld model and have the size 0(log 2 n).
CostDistance: Two Metric Network Design
 In Proceedings of the 41st Annual IEEE Symposium on Foundations of Computer Science
, 2000
"... Abstract We present the CostDistance problem: finding a Steiner tree which optimizes the sum of edge costs along one metric and the sum of sourcesink distances along an unrelated second metric. We give the first known O(log k) randomized approximation scheme for CostDistance, where k is the numbe ..."
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Cited by 68 (7 self)
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Abstract We present the CostDistance problem: finding a Steiner tree which optimizes the sum of edge costs along one metric and the sum of sourcesink distances along an unrelated second metric. We give the first known O(log k) randomized approximation scheme for CostDistance, where k is the number of sources. We reduce many common network design problems to CostDistance, obtaining (in some cases) the first known logarithmic approximation for them. These problems include singlesink buyatbulk with variable pipe types between different sets of nodes, facility location with buyatbulk type costs on edges, and maybecast with combind cost and distance metrics. Our algorithm is also the algorithm of choice for several previous network design problems, due to its ease of implementation and fast running time. 1 Introduction Consider designing a network from the ground up. We are given a set of customers, and need to place various servers and network links in order to cheaply provide sufficient service. If we only need to place the servers, this becomes the facility location problem and constantapproximations are known. If a single server handles all customers, and we impose the additional constraint that the set of available network link types is the same for every pair of nodes (subject to constant scaling factors on cost) then this is the single sink buyatbulk problem. We give the first known approximation for the general version of this problem with both servers and network links. We reduce the network design problem to an elegant theoretical framework: the CostDistance problem. We are given a graph with a single distinguished sink node (server). Every edge in this graph can be measured along two metrics; the first will be called cost and the second will be length. Note that the two metrics are entirely independent, and that there may be any number of parallel edges in the graph. We are given a set of sources (customers). Our objective is to construct a Steiner tree connecting the sources to the sink while minimizing the combined sum of the cost of the edges in the tree and sum over sources of the weighted length from source to sink.
On Characterizing Network Topologies and Analyzing Their Impact on Protocol Design
, 2000
"... Recently there have been several papers examining aspects of the Internet topology. This paper follows in that tradition and addresses two issues related to Internet topology. First, we use three properties  expansion, resilience, and distortion  to characterize real and generated networks. For ..."
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Cited by 45 (4 self)
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Recently there have been several papers examining aspects of the Internet topology. This paper follows in that tradition and addresses two issues related to Internet topology. First, we use three properties  expansion, resilience, and distortion  to characterize real and generated networks. For these metrics, we find that existing network topology generators differ qualitatively from most real networks. Second, we ask what impact topology has on four different multicast design questions. We find that, for many of these questions, a single topology metric appears to influence the answer.
Network Topologies, Power Laws, and Hierarchy
"... It has long been thought that the Internet, and its constituent networks, are hierarchical in nature. Consequently, the network topology generators most widely used by the Internet research community, GTITM [7] and Tiers [11], create networks with a deliberately hierarchical structure. However, r ..."
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Cited by 35 (5 self)
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It has long been thought that the Internet, and its constituent networks, are hierarchical in nature. Consequently, the network topology generators most widely used by the Internet research community, GTITM [7] and Tiers [11], create networks with a deliberately hierarchical structure. However, recent work by Faloutsos et al. [13] revealed that the Internet's degree distribution  the distribution of the number of connections routers or Autonomous Systems (ASs) have  is a powerlaw. The degree distributions produced by the GTITM and Tiers generators are not powerlaws. To rectify this problem, several new network generators have recently been proposed that produce more realistic degree distributions; these new generators do not attempt to create a hierarchical structure but instead focus solely on the degree distribution. There are thus two families of network generators, structural generators that treat hierarchy as fundamental and degreebased generators that treat the degree distribution as fundamental. In this paper we use several topology metrics to compare the networks produced by these two families of generators to current measurements of the Internet graph. We find that the degreebased generators produce better models, at least according to our topology metrics, of both the ASlevel and routerlevel Internet graphs. We then seek to resolve the seeming paradox that while the Internet certainly has hierarchy, it appears that the Internet graphs are better modeled by generators that do not explicitly construct hierarchies. We conclude our paper with a brief study of other network structures, such as the pointer structure in the web and the set of airline routes, some of which turn out to have metric properties similar to that of the Interne...
An optimal rebuilding strategy for an incremental tree problem
 In Journal of Interconnexion Networks, accepted
, 2006
"... This paper is devoted to the following incremental problem. Initially, a graph and a distinguished subset of vertices, called initial group, are given. This group is connected by an initial tree. The incremental part of the input is given by an online sequence of vertices of the graph, not yet in t ..."
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Cited by 4 (4 self)
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This paper is devoted to the following incremental problem. Initially, a graph and a distinguished subset of vertices, called initial group, are given. This group is connected by an initial tree. The incremental part of the input is given by an online sequence of vertices of the graph, not yet in the current group, revealed online one after one. The goal is to connect each new member to the current tree, while satisfying a quality constraint: the average distance between members in each constructed tree must be kept in a given range compared to the best possible one. Under this quality constraint, our objectives are to minimize the number of critical stages and the number of elementary changes of the sequence of constructed trees. We call ”critical ” a stage where the inclusion of a new member implies heavy changes in the current tree. Otherwise, the new member is just added by connecting it with a (well chosen) path to the current tree. In both cases, updating a tree implies a certain number of elementary changes (that we define). We propose a strategy leading to at most O(log i) critical stages (i is the number of new members) and to at most a constant average number of elementary changes per stage. We also
PowerAware OnDemand Routing Protocols for Mobile Ad Hoc Networks
"... Introduction 32.2 MANET Routing Protocols Proactive (TableDriven) Routing Protocols, Reactive (OnDemand) Protocols, Hybrid Routing Protocols 32.3 Low Power Routing Protocols Minimum Power Routing, BatteryCost LifetimeAware Routing, Energy Conserving Techniques for Multihop Ad Hoc Networks, ..."
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Cited by 4 (0 self)
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Introduction 32.2 MANET Routing Protocols Proactive (TableDriven) Routing Protocols, Reactive (OnDemand) Protocols, Hybrid Routing Protocols 32.3 Low Power Routing Protocols Minimum Power Routing, BatteryCost LifetimeAware Routing, Energy Conserving Techniques for Multihop Ad Hoc Networks, EnergyAware Multicast Routing Algorithms 32.4 PowerAware Source Routing Cost Function, Route Discovery, Route Maintenance 32.5 Lifetime Prediction Routing Basic Mechanism, Route Discovery, Route Expiration Error! Reference source not found. Quantitative Evaluation of Source Routing Algorithms Simulation Setup, Simulation Results 32.7 Conclusion Morteza Maleki and Massoud Pedram University of Southern California, Los Angeles, CA Wireless mobile networks may be classified into these two general categories: Infrastructurebased Networks: Wireless networks often extend, rather than replace, wired networks, and are referred to as infrastructure networks. A hierarchy of wide area and
Network topology generators: . . .
, 2002
"... Following the longheld belief that the Internet is hierarchical, the network topology generators most widely used by the Internet research community, TransitStub and Tiers, create networks with a deliberately hierarchical structure. However, in 1999 a seminal paper by Faloutsos et al. revealed tha ..."
Abstract
 Add to MetaCart
Following the longheld belief that the Internet is hierarchical, the network topology generators most widely used by the Internet research community, TransitStub and Tiers, create networks with a deliberately hierarchical structure. However, in 1999 a seminal paper by Faloutsos et al. revealed that the Internet’s degree distribution is a powerlaw. Because the degree distributions produced by the TransitStub and Tiers generators are not powerlaws, the research community has largely dismissed them as inadequate and proposed new network generators that attempt to generate graphs with powerlaw degree distributions. Contrary to much of the current literature on network topology generators, this paper starts with the assumption that it is more important for network generators to accurately model the largescale structure of the Internet (such as its hierarchical structure) than to faithfully imitate its local properties (such as the degree distribution). The purpose of this paper is to determine, using various topology metrics, which network generators better represent this largescale structure. We find, much to our surprise, that network generators based on the degree distribution more accurately capture the largescale structure of measured topologies. We then seek an explanation for this result by examining the nature of hierarchy
A Distributed Routing Method for Dynamic Multicasting DEBASISH CHAKRABORTY
"... Single point, sender based control does not scale well for multicast delivery. For applications, such as group video or teleconferencing a low total cost multicast tree is required. In this article we present a destination driven algorithm to minimize the total tree cost of multicast tree in a dynam ..."
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Single point, sender based control does not scale well for multicast delivery. For applications, such as group video or teleconferencing a low total cost multicast tree is required. In this article we present a destination driven algorithm to minimize the total tree cost of multicast tree in a dynamic situation for the whole session duration. In this heuristic approach we considered the staying duration of participants are available at the time of joining. The performance of our algorithm is analyzed through extensive simulation and evaluated against several other existing dynamic multicast routing and also against one well known near optimum heuristic algorithm used for solving Steiner tree problem. We have further tested our algorithm using erroneous information given by the joining participants. Simulation results show that its performance does not degrade that much even when the range of error is considerably high, which proves the robustness of our algorithm.
Using the SmallWorld Model to Improve Freenet Performance
"... Abstract – Efficient data retrieval in a peertopeer system like Freenet is a challenging problem. In this paper we study the impact of cache replacement policy on the performance of Freenet. We find that, with Freenet’s LRU cache replacement, there is a steep reduction in the hit ratio with increa ..."
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Abstract – Efficient data retrieval in a peertopeer system like Freenet is a challenging problem. In this paper we study the impact of cache replacement policy on the performance of Freenet. We find that, with Freenet’s LRU cache replacement, there is a steep reduction in the hit ratio with increasing load. Based on intuition from the smallworld models and the recent theoretical results by Kleinberg, we propose an enhancedclustering cache replacement scheme for use in place of LRU. Such a replacement scheme forces the routing tables to resemble neighbor relationships in a smallworld acquaintance graph clustering with light randomness. In our simulation this new scheme improved the request hit ratio dramatically while keeping the small average hops per successful request comparable to LRU. A simple, highly idealized model of Freenet under clustering with light randomness proves that the 2 expected message delivery time in Freenet is O ( log n) if the routing tables satisfy the smallworld model and have the size (log) 2 θ n.