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117
BRITE: An Approach to Universal Topology Generation
, 2001
"... Effective engineering of the Internet is predicated upon a detailed understanding of issues such as the largescale 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. Unfortunate ..."
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Cited by 344 (8 self)
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Effective engineering of the Internet is predicated upon a detailed understanding of issues such as the largescale 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 generated 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 the design principles of representativeness, inclusiveness, and interoperability. Representativeness leads to synthetic topologies that accurately reflect many aspects of the actual Internet topology (e.g. hierarchical structure, node degree distribution, etc.). Inclusiveness combines the strengths of as many generation models as possible in a single generation tool. Interoperability provides interfaces to widelyused simulation applications such as ns and SSF and visualization tools like otter. We call such a tool a universal topology generator. Keywords: topology generation, graph models, network topology, growth models, annotated topologies, simulation environments. 1
Scheduling Distributed Applications: The SimGrid Simulation Framework
 In Proceedings of the Third IEEE International Symposium on Cluster Computing and the Grid (CCGrid’03
, 2003
"... Abstract — Since the advent of distributed computer systems an active field of research has been the investigation of scheduling strategies for parallel applications. The common approach is to employ scheduling heuristics that approximate an optimal schedule. Unfortunately, it is often impossible to ..."
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Cited by 114 (29 self)
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Abstract — Since the advent of distributed computer systems an active field of research has been the investigation of scheduling strategies for parallel applications. The common approach is to employ scheduling heuristics that approximate an optimal schedule. Unfortunately, it is often impossible to obtain analytical results to compare the efficacy of these heuristics. One possibility is to conducts large numbers of backtoback experiments on real platforms. While this is possible on tightlycoupled platforms, it is infeasible on modern distributed platforms (i.e. Grids) as it is laborintensive and does not enable repeatable results. The solution is to resort to simulations. Simulations not only enables repeatable results but also make it possible to explore wide ranges of platform and application scenarios. In this paper we present the SimGrid framework which enables the simulation of distributed applications in distributed computing environments for the specific purpose of developing and evaluating scheduling algorithms. This paper focuses on SimGrid v2, which greatly improves on the first version of the software with more realistic networkmodels and topologies. SimGrid v2 also enables the simulation of distributed scheduling agents, which has become critical for current scheduling research in largescale platforms. After describing and validating these features, we present a case study by which we demonstrate the usefulness of SimGrid for conducting scheduling research. I.
Epidemic Spreading in Real Networks: An Eigenvalue Viewpoint
 In SRDS
, 2003
"... Abstract How will a virus propagate in a real network?Does an epidemic threshold exist for a finite powerlaw graph, or any finite graph? How long does ittake to disinfect a network given particular values of infection rate and virus death rate? We answer the first question by providing equations th ..."
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Cited by 81 (18 self)
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Abstract How will a virus propagate in a real network?Does an epidemic threshold exist for a finite powerlaw graph, or any finite graph? How long does ittake to disinfect a network given particular values of infection rate and virus death rate? We answer the first question by providing equations that accurately model virus propagation in any network including real and synthesized networkgraphs. We propose a general epidemic threshold condition that applies to arbitrary graphs: weprove that, under reasonable approximations, the epidemic threshold for a network is closely relatedto the largest eigenvalue of its adjacency matrix. Finally, for the last question, we show that infections tend to zero exponentially below the epidemic threshold. We show that our epidemic threshold modelsubsumes many known thresholds for specialcase graphs (e.g., Erd&quot;osR'enyi, BA powerlaw, homogeneous); we show that the threshold tends to zero for infinite powerlaw graphs. Finally, we illustrate thepredictive power of our model with extensive experiments on real and synthesized graphs. We show thatour threshold condition holds for arbitrary graphs.
Building topologyaware overlays using global softstate
, 2002
"... Recent peertopeer (P2P) networks, represented by CAN, Chord, and Pastry, offer an administrationfree and faulttolerant applicationlevel overlay network. For these systems to function efficiently, they must make effective use of the underlying network topology. Existing ..."
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Cited by 76 (8 self)
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Recent peertopeer (P2P) networks, represented by CAN, Chord, and Pastry, offer an administrationfree and faulttolerant applicationlevel overlay network. For these systems to function efficiently, they must make effective use of the underlying network topology. Existing
On the eigenvalue power law
 In International Workshop on Randomization and Approximation Techniques in Computer Science
"... ..."
Selfish Caching in Distributed Systems: A GameTheoretic Analysis
 in Proc. ACM Symposium on Principles of Distributed Computing (ACM PODC
, 2004
"... We analyze replication of resources by server nodes that act selfishly, using a gametheoretic approach. We refer to this as the selfish caching problem. In our model, nodes incur either cost for replicating resources or cost for access to a remote replica. We show the existence of pure strategy Nas ..."
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Cited by 47 (2 self)
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We analyze replication of resources by server nodes that act selfishly, using a gametheoretic approach. We refer to this as the selfish caching problem. In our model, nodes incur either cost for replicating resources or cost for access to a remote replica. We show the existence of pure strategy Nash equilibria and investigate the price of anarchy, which is the relative cost of the lack of coordination. The price of anarchy can be high due to undersupply problems, but with certain network topologies it has better bounds. With a payment scheme the game can always implement the social optimum in the best case by giving servers incentive to replicate.
Epidemic Thresholds in Real Networks
"... How will a virus propagate in a real network? How long does it take to disinfect a network given particular values of infection rate and virus death rate? What is the single best node to immunize? Answering these questions is essential for devising networkwide strategies to counter viruses. In addi ..."
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Cited by 43 (9 self)
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How will a virus propagate in a real network? How long does it take to disinfect a network given particular values of infection rate and virus death rate? What is the single best node to immunize? Answering these questions is essential for devising networkwide strategies to counter viruses. In addition, viral propagation is very similar in principle to the spread of rumors, information, and “fads, ” implying that the solutions for viral propagation would also offer insights into these other problem settings. We answer these questions by developing a nonlinear dynamical system (NLDS) that accurately models viral propagation in any arbitrary network, including real and synthesized network graphs. We propose a general epidemic threshold condition for the NLDS system: we prove that the epidemic threshold for a network is exactly the inverse of the largest eigenvalue of its adjacency matrix. Finally, we show that below the epidemic threshold, infections die out at an exponential rate. Our epidemic threshold model subsumes many known thresholds for specialcase graphs (e.g., Erdös–Rényi, BA powerlaw, homogeneous). We demonstrate the predictive power of our model with extensive experiments on real and synthesized graphs, and show that our threshold condition holds for arbitrary graphs. Finally, we show how to utilize our threshold condition for practical uses: It can dictate which nodes to immunize; it can assess the effects of a throttling
Indexing and Mining Free Trees
 Proceedings of the 2003 IEEE International Conference on Data Mining (ICDM’03
, 2003
"... Tree structures are used extensively in domains such as computational biology, pattern recognition, computer networks, and so on. In this paper, we present an indexing technique for free trees and apply this indexing technique to the problem of mining frequent subtrees. We first define a novel re ..."
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Cited by 41 (7 self)
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Tree structures are used extensively in domains such as computational biology, pattern recognition, computer networks, and so on. In this paper, we present an indexing technique for free trees and apply this indexing technique to the problem of mining frequent subtrees. We first define a novel representation, the canonical form, for rooted trees and extend the definition to free trees. We also introduce another concept, the canonical string, as a simpler representation for free trees in their canonical forms. We then apply our tree indexing technique to the frequent subtree mining problem and present FreeTreeMiner, a computationally e#cient algorithm that discovers all frequently occurring subtrees in a database of free trees. Our mining algorithm is a variation of the traditional a priori method for mining frequent itemsets. We study the performance and the scalability of our algorithms through extensive experiments based on both synthetic data and datasets from two real applications: a dataset of chemical compounds and a dataset of Internet multicast trees. The experiments show that our algorithm scales linearly in the cardinality of the database.
Building Lowmaintenance Expressways for P2P Systems
, 2002
"... Recent P2P systems, represented by Oceanstore and PAST, offer an administrationfree and faulttolerant storage utility. Nodes in these systems collectively contribute towards a storage space, in a selforganizing fashion. While elegant from a theoretical perspective, they can be improved in thr ..."
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Cited by 40 (7 self)
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Recent P2P systems, represented by Oceanstore and PAST, offer an administrationfree and faulttolerant storage utility. Nodes in these systems collectively contribute towards a storage space, in a selforganizing fashion. While elegant from a theoretical perspective, they can be improved in three important areas: (i) low maintenance cost; (ii) the ability to make discriminative use of the nodes in the system that has different capacity and resource constraints; (iii) the ability to adapt to the underlying network conditions and the applications' needs. In this
The Markov Chain Simulation Method for Generating Connected Power Law Random Graphs
 In Proc. 5th Workshop on Algorithm Engineering and Experiments (ALENEX). SIAM
, 2003
"... Graph models for realworld complex networks such as the Internet, the WWW and biological networks are necessary for analytic and simulationbased studies of network protocols, algorithms, engineering and evolution. To date, all available data for such networks suggest heavy tailed statistics, most ..."
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Cited by 32 (6 self)
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Graph models for realworld complex networks such as the Internet, the WWW and biological networks are necessary for analytic and simulationbased studies of network protocols, algorithms, engineering and evolution. To date, all available data for such networks suggest heavy tailed statistics, most notably on the degrees of the underlying graphs. A practical way to generate network topologies that meet the observed data is the following degreedriven approach: First predict the degrees of the graph by extrapolation from the available data, and then construct a graph meeting the degree sequence and additional constraints, such as connectivity and randomness. Within the networking community, this is currently accepted as the most successful approach for modeling the interdomain topology of the Internet.