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107
Faulttolerant Routing in Peertopeer Systems
, 2003
"... We consider the problem of designing an overlay network and routing mechanism that permits finding resources efficiently in a peertopeer system. We argue that many existing approaches to this problem can be modeled as the construction of a random graph embedded in a metric space whose points repre ..."
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Cited by 60 (1 self)
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We consider the problem of designing an overlay network and routing mechanism that permits finding resources efficiently in a peertopeer system. We argue that many existing approaches to this problem can be modeled as the construction of a random graph embedded in a metric space whose points represent resource identifiers, where the probability of a connection between two nodes depends only on the distance between them in the metric space. We study the performance of a peertopeer system where nodes are embedded at grid points in a simple metric space: a onedimensional real line. We prove upper and lower bounds on the message complexity of locating particular resources in such a system, under a variety of assumptions about failures of either nodes or the connections between them. Our lower bounds in particular show that the use of inverse powerlaw distributions in routing, as suggested by Kleinberg [5], is close to optimal. We also give efficient heuristics to dynamically maintain such a system as new nodes arrive and old nodes depart. Finally, we give experimental results that suggest promising directions for future work.
Analyzing Kleinberg’s (and other) smallworld models
 in Proc. of ACM Symp. on Princ. of Dist. Comp. (PODC
, 2004
"... We analyze the properties of SmallWorld networks, where links are much more likely to connect “neighbor nodes ” than distant nodes. In particular, our analysis provides new results for Kleinberg’s SmallWorld model and its extensions. Kleinberg adds a number of directed longrange random links to a ..."
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Cited by 58 (6 self)
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We analyze the properties of SmallWorld networks, where links are much more likely to connect “neighbor nodes ” than distant nodes. In particular, our analysis provides new results for Kleinberg’s SmallWorld model and its extensions. Kleinberg adds a number of directed longrange random links to an n × n lattice network (vertices as nodes of a grid, undirected edges between any two adjacent nodes). Links have a nonuniform distribution that favors arcs to close nodes over more distant ones. He shows that the following phenomenon occurs: between any two nodes a path with expected length O(log 2 n) can be found using a simple greedy algorithm which has no global knowledge of longrange links. We show that Kleinberg’s analysis is tight: his algorithm achieves θ(log 2 n) delivery time. Moreover, we show that the expected diameter of the graph is θ(log n), a log n factor
SmartTag Based Data Dissemination
, 2002
"... Monitoring wide, hostile areas requires disseminating data between fixed, disconnected clusters of sensor nodes. It is not always possible to install longrange radios in order to cover the whole area. We propose to leverage the movement of mobile individuals, equipped with smarttags, to disseminat ..."
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Cited by 56 (5 self)
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Monitoring wide, hostile areas requires disseminating data between fixed, disconnected clusters of sensor nodes. It is not always possible to install longrange radios in order to cover the whole area. We propose to leverage the movement of mobile individuals, equipped with smarttags, to disseminate data across disconnected static nodes spread across a wide area. Static nodes and mobile smarttags exchange data when they are in the vicinity of each other; smarttags disseminate data as they move around. In this paper, we propose an algorithm for update propagation and a model for smarttag based data dissemination. We use simulation to study the characteristics of the model we propose. Finally, we present an implementation based on bluetooth smarttags.
Protocols and impossibility results for gossipbased communication mechanisms
, 2002
"... In recent years, gossipbased algorithms have gained prominence as a methodology for designing robust and scalable communication schemes in large distributed systems. The premise underlying distributed gossip is very simple: in each time step, each node v in the system selects some other node w as a ..."
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Cited by 56 (3 self)
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In recent years, gossipbased algorithms have gained prominence as a methodology for designing robust and scalable communication schemes in large distributed systems. The premise underlying distributed gossip is very simple: in each time step, each node v in the system selects some other node w as a communication partner — generally by a simple randomized rule — and exchanges information with w; over a period of time, information spreads through the system in an “epidemic fashion”. A fundamental issue which is not well understood is the following: how does the underlying lowlevel gossip mechanism — the means by which communication partners are chosen — affect one’s ability to design efficient highlevel gossipbased protocols? We establish one of the first concrete results addressing this question, by showing a fundamental limitation on the power of the commonly used uniform gossip mechanism for solving nearestresource location problems. In contrast, very efficient protocols for this problem can be designed using a nonuniform spatial gossip mechanism, as established in earlier work with Alan Demers. We go on to consider the design of protocols for more complex problems, providing an efficient distributed gossipbased protocol for a set of nodes in Euclidean space to construct an approximate minimum spanning tree. Here too, we establish a contrasting limitation on the power of uniform gossip for solving this problem. Finally, we investigate gossipbased packet routing as a primitive that underpins the communication patterns in many protocols, and as a way to understand the capabilities of different gossip mechanisms at a general level.
Computing separable functions via gossip
 In Proceedings of the TwentyFifth Annual ACM Symposium on Principles of Distributed Computing (PODC
, 2006
"... Motivated by applications to sensor, peertopeer, and adhoc networks, we study the problem of computing functions of values at the nodes in a network in a totally distributed manner. In particular, we consider separable functions, which can be written as linear combinations or products of function ..."
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Cited by 48 (6 self)
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Motivated by applications to sensor, peertopeer, and adhoc networks, we study the problem of computing functions of values at the nodes in a network in a totally distributed manner. In particular, we consider separable functions, which can be written as linear combinations or products of functions of individual variables. The main contribution of this paper is the design of a distributed algorithm for computing separable functions based on properties of exponential random variables. We bound the running time of our algorithm in terms of the running time of an information spreading algorithm used as a subroutine by the algorithm. Since we are interested in totally distributed algorithms, we consider a randomized gossip mechanism for information spreading as the subroutine. Combining these algorithms yields a complete and simple distributed algorithm for computing separable functions. The second contribution of this paper is a characterization of the information spreading time of the gossip algorithm, and therefore the computation time for separable functions, in terms of the conductance of an appropriate stochastic matrix. Specifically, we find that for a class of graphs with small spectral gap, this time is of a smaller order than the time required to compute averages for a known iterative gossip scheme [4]. 1
Cooperative downloading in vehicular adhocwireless networks
 in IEEE WONS
, 2005
"... Increasing need for people to be “connected”; while at the same time remain as mobile as ever poses several interesting issues in wireless networks. It is conceivable in the nearfuture that wireless “hotspots ” experience flash crowdslike traffic arrival pattern. A common phenomena in the Internet ..."
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Cited by 48 (11 self)
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Increasing need for people to be “connected”; while at the same time remain as mobile as ever poses several interesting issues in wireless networks. It is conceivable in the nearfuture that wireless “hotspots ” experience flash crowdslike traffic arrival pattern. A common phenomena in the Internet today characterized by sudden and unpredicted increase in popularity of online content. In this paper, we propose SPAWN, a cooperative strategy for content delivery and sharing in future vehicular networks. We study the issues involved in using such a strategy from the standpoint of Vehicular AdHoc networks. In particular, we show that not only content server but also wireless access network load reduction is critical. We propose a “communication efficient ” swarming protocol which uses a gossip mechanism that leverages the inherent broadcast nature of the wireless medium, and a pieceselection strategy that takes proximity into account in decisions to exchange pieces. We show through simulation that gossip incorporates locationawareness into peer selection, while incurring low messaging overhead, and consequently enhancing the swarming protocol performance. We develop an analytical model to characterize the performance of SPAWN. 1.
Correctness of a gossip based membership protocol
 in Proceedings of the twentyfourth annual ACM symposium on Principles of distributed computing, ser. PODC ’05
, 1990
"... The importance of scalability and faulttolerance in modern distributed systems has led to considerable research in multicast protocols using gossip. In a gossip protocol, each node forwards messages to a small set of “gossip partners ” chosen at random from the entire group membership. By discardin ..."
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Cited by 45 (0 self)
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The importance of scalability and faulttolerance in modern distributed systems has led to considerable research in multicast protocols using gossip. In a gossip protocol, each node forwards messages to a small set of “gossip partners ” chosen at random from the entire group membership. By discarding the strong reliability guarantees of traditional protocols in favour of probabilistic guarantees, gossip protocols can deliver greater scalability and fault tolerance. In early gossip algorithms, partners were chosen uniformly at random from the entire membership, limiting scalability because of the resources required to store and maintain complete membership views at each node. Later protocols avoided this issue by storing much smaller random subsets of the membership at each node, and choosing gossip partners only from these local views. Such protocols are subtle: at least some local views must change in response to group membership changes in order to preserve connectivity and performance guarantees. While these protocols have been the subject of much simulation and analysis, formal proofs of key properties – in particular the probability of partitioning – have remained elusive. In this paper we give a new scalable gossipbased algorithm for local view maintenance, together with a proof that the expected time until a network partition is at least exponential in the square of the view size. We also develop probabilistic bounds on the indegree (hence the load) of individual nodes, and argue that protocols lacking our reinforcement component eventually converge to starlike networks, whose connectivity depends on a small set of overloaded nodes. We also argue that the undirected connectivity graph is an expander, for which applicationlevel gossip multicast protocols will converge rapidly. Our theoretical results are supported by simulations.
Fractionally cascaded information in a sensor network
, 2004
"... We address the problem of distributed information aggregation and storage in a sensor network, where queries can be injected anywhere in the network. The principle we propose is that a sensor should know a “fraction ” of the information from distant parts of the network, in an exponentially decaying ..."
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Cited by 41 (9 self)
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We address the problem of distributed information aggregation and storage in a sensor network, where queries can be injected anywhere in the network. The principle we propose is that a sensor should know a “fraction ” of the information from distant parts of the network, in an exponentially decaying fashion by distance. We show how a sampled scalar field can be stored in this distributed fashion, with only a modest amount of additional storage and network traffic. Our storage scheme makes neighboring sensors have highly correlated world views; this allows smooth information gradients and enables local search algorithms to work well. We study in particular how this principle of fractionally cascaded information can be exploited to answer range queries about the sampled field efficiently. Using local decisions only we are able to route the query to exactly the portions of the field where the sought information is stored. We provide a rigorous theoretical analysis showing that our scheme is close to optimal. Categories and Subject Descriptors H.3.3 [Information Systems]: information storage and retrieval—information search and retrieval; F.2.2 [Theory of Computation]: analysis of algorithms and problem complexity—nonnumerical algorithms and problems
Araneola: A Scalable Reliable Multicast System for Dynamic Environments
 In IEEE NCA
, 2004
"... This paper presents Araneola 1, a scalable reliable applicationlevel multicast system for highly dynamic widearea environments. Araneola supports multipoint to multipoint reliable communication in a fully distributed manner while incurring constant load (in terms of message and space complexity) ..."
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Cited by 28 (8 self)
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This paper presents Araneola 1, a scalable reliable applicationlevel multicast system for highly dynamic widearea environments. Araneola supports multipoint to multipoint reliable communication in a fully distributed manner while incurring constant load (in terms of message and space complexity) on each node. For a tunable parameter k ≥ 3, Araneola constructs and dynamically maintains a basic overlay structure in which each node’s degree is either k or k +1, and roughly 90 % of the nodes have degree k. Empirical evaluation shows that Araneola’s basic overlay achieves three important mathematical properties of kregular random graphs (i.e., random graphs in which each node has exactly k neighbors) with N nodes: (i) its diameter grows logarithmically with N; (ii) it is generally kconnected; and (iii) it remains highly connected following random removal of linearsize subsets of edges or nodes. The overlay is constructed and maintained at a low cost: each join, leave, or failure is handled locally, and entails the sending of only about 3k messages in total, independent of N. Moreover, this cost decreases as the churn rate increases. The low degree of Araneola’s basic overlay structure allows for allocating plenty of additional bandwidth for specific application needs. In this paper, we give an example for such a need — communicating with nearby nodes; we enhance the basic overlay with additional links chosen according to geographic
Fast distributed algorithms for computing separable functions
 IEEE Trans. Inform. Theory
"... Abstract—The problem of computing functions of values at the nodes in a network in a fully distributed manner, where nodes do not have unique identities and make decisions based only on local information, has applications in sensor, peertopeer, and adhoc networks. The task of computing separable f ..."
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Cited by 27 (5 self)
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Abstract—The problem of computing functions of values at the nodes in a network in a fully distributed manner, where nodes do not have unique identities and make decisions based only on local information, has applications in sensor, peertopeer, and adhoc networks. The task of computing separable functions, which can be written as linear combinations of functions of individual variables, is studied in this context. Known iterative algorithms for averaging can be used to compute the normalized values of such functions, but these algorithms do not extend in general to the computation of the actual values of separable functions. The main contribution of this paper is the design of a distributed randomized algorithm for computing separable functions. The running time of the algorithm is shown to depend on the running time of a minimum computation algorithm used as a subroutine. Using a randomized gossip mechanism for minimum computation as the subroutine yields a complete fully distributed algorithm for computing separable functions. For a class of graphs with small spectral gap, such as grid graphs, the time used by the algorithm to compute averages is of a smaller order than the time required by a known iterative averaging scheme. Index Terms—Data aggregation, distributed algorithms, gossip algorithms, randomized algorithms. I.