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167
GossipBased Computation of Aggregate Information
, 2003
"... between computers, and a resulting paradigm shift from centralized to highly distributed systems. With massive scale also comes massive instability, as node and link failures become the norm rather than the exception. For such highly volatile systems, decentralized gossipbased protocols are emergin ..."
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Cited by 301 (1 self)
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between computers, and a resulting paradigm shift from centralized to highly distributed systems. With massive scale also comes massive instability, as node and link failures become the norm rather than the exception. For such highly volatile systems, decentralized gossipbased protocols are emerging as an approach to maintaining simplicity and scalability while achieving faulttolerant information dissemination.
Randomized Gossip Algorithms
 IEEE TRANSACTIONS ON INFORMATION THEORY
, 2006
"... Motivated by applications to sensor, peertopeer, and ad hoc networks, we study distributed algorithms, also known as gossip algorithms, for exchanging information and for computing in an arbitrarily connected network of nodes. The topology of such networks changes continuously as new nodes join a ..."
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Cited by 209 (5 self)
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Motivated by applications to sensor, peertopeer, and ad hoc networks, we study distributed algorithms, also known as gossip algorithms, for exchanging information and for computing in an arbitrarily connected network of nodes. The topology of such networks changes continuously as new nodes join and old nodes leave the network. Algorithms for such networks need to be robust against changes in topology. Additionally, nodes in sensor networks operate under limited computational, communication, and energy resources. These constraints have motivated the design of “gossip ” algorithms: schemes which distribute the computational burden and in which a node communicates with a randomly chosen neighbor. We analyze the averaging problem under the gossip constraint for an arbitrary network graph, and find that the averaging time of a gossip algorithm depends on the second largest eigenvalue of a doubly stochastic matrix characterizing the algorithm. Designing the fastest gossip algorithm corresponds to minimizing this eigenvalue, which is a semidefinite program (SDP). In general, SDPs cannot be solved in a distributed fashion; however, exploiting problem structure, we propose a distributed subgradient method that solves the optimization problem over the network. The relation of averaging time to the second largest eigenvalue naturally relates it to the mixing time of a random walk with transition probabilities derived from the gossip algorithm. We use this connection to study the performance and scaling of gossip algorithms on two popular networks: Wireless Sensor Networks, which are modeled as Geometric Random Graphs, and the Internet graph under the socalled Preferential Connectivity (PC) model.
Spatial gossip and resource location protocols
, 2001
"... The dynamic behavior of a network in which information is changing continuously over time requires robust and efficient mechanisms for keeping nodes updated about new information. Gossip protocols are mechanisms for this task in which nodes communicate with one another according to some underlying d ..."
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Cited by 141 (7 self)
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The dynamic behavior of a network in which information is changing continuously over time requires robust and efficient mechanisms for keeping nodes updated about new information. Gossip protocols are mechanisms for this task in which nodes communicate with one another according to some underlying deterministic or randomized algorithm, exchanging information in each communication step. In a variety of contexts, the use of randomization to propagate information has been found to provide better reliability and scalability than more regimented deterministic approaches. In many settings, such as a cluster of distributed computing hosts, new information is generated at individual nodes, and is most “interesting ” to nodes that are nearby. Thus, we propose distancebased propagation bounds as a performance measure for gossip mechanisms: a node at distance d from the origin of a new piece of information should be able to learn about this information with a delay that grows slowly with d, and is independent of the size of the network. For nodes arranged with uniform density in Euclidean space, we present natural gossip mechanisms, called spatial gossip, that satisfy such a guarantee: new information is spread to
PGrid: A Selforganizing Structured P2P System
, 2003
"... this paper was supported in part by the National Competence Center in Research on Mobile Information and Communication Systems (NCCRMICS), a center supported by the Swiss National Science Foundation under grant number 500567322 and by SNSF grant 2100064994, "PeertoPeer Information Systems." ..."
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Cited by 108 (16 self)
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this paper was supported in part by the National Competence Center in Research on Mobile Information and Communication Systems (NCCRMICS), a center supported by the Swiss National Science Foundation under grant number 500567322 and by SNSF grant 2100064994, "PeertoPeer Information Systems." messages. From the responses it (randomly) selects certain peers to which direct network links are established
Performance Modeling of Epidemic Routing
 In Proceedings of IFIP Networking
, 2006
"... Abstract. In this paper, we develop a rigorous, unified framework based on Ordinary Differential Equations (ODEs) to study epidemic routing and its variations. These ODEs can be derived as limits of Markovian models under a natural scaling as the number of nodes increases. While an analytical study ..."
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Cited by 106 (9 self)
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Abstract. In this paper, we develop a rigorous, unified framework based on Ordinary Differential Equations (ODEs) to study epidemic routing and its variations. These ODEs can be derived as limits of Markovian models under a natural scaling as the number of nodes increases. While an analytical study of Markovian models is quite complex and numerical solution impractical for large networks, the corresponding ODE models yield closedform expressions for several performance metrics of interest, and a numerical solution complexity that does not increase with the number of nodes. Using this ODE approach, we investigate how resources such as buffer space and power can be traded for faster delivery, illustrating the differences among the various epidemic schemes considered. Finally we consider the effect of buffer management by complementing the forwarding models with Markovian and fluid buffer models.
A lightweight, robust p2p system to handle flash crowds
, 2002
"... Internet flash crowds (a.k.a. hot spots) are a phenomenon that result from a sudden, unpredicted increase in an online object’s popularity. Currently, there is no efficient means within the Internet to scalably deliver web objects under hot spot conditions to all clients that desire the object. We ..."
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Cited by 89 (4 self)
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Internet flash crowds (a.k.a. hot spots) are a phenomenon that result from a sudden, unpredicted increase in an online object’s popularity. Currently, there is no efficient means within the Internet to scalably deliver web objects under hot spot conditions to all clients that desire the object. We present PROOFS: a simple, lightweight, peertopeer (P2P) approach that uses randomized overlay construction and randomized, scoped searches to efficiently locate and deliver objects under heavy demand to all users that desire them. We evaluate PROOFS ’ robustness in environments in which clients join and leave the P2P network as well as in environments in which clients are not always fully cooperative. Through a mix of analytical modeling, simulation, and prototype experimentation in the Internet, we show that randomized approaches like PROOFS should effectively relieve flash crowd symptoms in dynamic, limitedparticipation environments. 1
Geographic Gossip: Efficient Aggregation for Sensor Networks
 in Proc. Information Processing in Sensor Networks (IPSN
, 2006
"... Gossip algorithms for aggregation have recently received significant attention for sensor network applications because of their simplicity and robustness in noisy and uncertain environments. However, gossip algorithms can waste significant energy by essentially passing around redundant information m ..."
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Cited by 82 (4 self)
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Gossip algorithms for aggregation have recently received significant attention for sensor network applications because of their simplicity and robustness in noisy and uncertain environments. However, gossip algorithms can waste significant energy by essentially passing around redundant information multiple times. For realistic sensor network model topologies like grids and random geometric graphs, the inefficiency of gossip schemes is caused by slow mixing times of random walks on those graphs. We propose and analyze an alternative gossiping scheme that exploits geographic information. By utilizing a simple resampling method, we can demonstrate substantial gains over previously proposed gossip protocols. In particular, for random geometric graphs, our algorithm computes the true average to accuracy 1/n a using O(n 1.5 √ log n) radio transmissions, which reduces the energy consumption by a algorithms. q n factor over standard gossip log n
Updates in Highly Unreliable, Replicated PeertoPeer Systems
 In Proceedings of the 23rd International Conference on Distributed Computing Systems
, 2003
"... This paper studies the problem of updates in decentralised and selforganising P2P systems in which peers have low online probabilities and only local knowledge. The update strategy we propose for this environment is based on a hybrid push/pull rumor spreading algorithm and provides a fully decentra ..."
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Cited by 79 (26 self)
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This paper studies the problem of updates in decentralised and selforganising P2P systems in which peers have low online probabilities and only local knowledge. The update strategy we propose for this environment is based on a hybrid push/pull rumor spreading algorithm and provides a fully decentralised, efficient and robust communication scheme which offers probabilistic guarantees rather than ensuring strict consistency. We describe a generic analytical model to investigate the utility of our hybrid update propagation scheme from the perspective of communication overhead.
Algebraic gossip: A network coding approach to optimal multiple rumor mongering
 IEEE Transactions on Information Theory
, 2004
"... We study the problem of simultaneously disseminating multiple messages in a large network in a decentralized and distributed manner. We consider a network with n nodes and k (k = O(n)) messages spread throughout the network to start with, but not all nodes have all the messages. Our communication mo ..."
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Cited by 78 (11 self)
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We study the problem of simultaneously disseminating multiple messages in a large network in a decentralized and distributed manner. We consider a network with n nodes and k (k = O(n)) messages spread throughout the network to start with, but not all nodes have all the messages. Our communication model is such that the nodes communicate in discretetime steps, and in every timestep, each node communicates with a random communication partner chosen uniformly from all the nodes (known as the random phone call model). The system is bandwidth limited and in each timestep, only one message can be transmitted. The goal is to disseminate rapidly all the messages among all the nodes. We study the time required for this dissemination to occur with high probability, and also in expectation. We present a protocol based on random linear coding (RLC) that disseminates all the messages among all the nodes in O(n) time, which is order optimal, if we ignore the small overhead associated with each transmission. The overhead does not depend on the size of the messages and is less than 1 % for k = 100 and messages of size 100 KB. We also consider a store and forward mechanism without coding, which is a natural extension of gossipbased dissemination with one message in the network. We show that, such an uncoded scheme can do no better than a sequential approach (instead of doing it simultaneously) of disseminating the messages which takes Θ(n ln(n)) time, since disseminating a single message in a gossip network takes Θ(ln(n)) time. 1
From Epidemics to Distributed Computing
 IEEE Computer
"... Abstract — Epidemic algorithms have been recently recognized as robust and scalable means to disseminate information in largescale settings. Information is disseminated reliably in a distributed system the same way an epidemic would be propagated throughout a group of individuals: each process of t ..."
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Cited by 72 (4 self)
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Abstract — Epidemic algorithms have been recently recognized as robust and scalable means to disseminate information in largescale settings. Information is disseminated reliably in a distributed system the same way an epidemic would be propagated throughout a group of individuals: each process of the system chooses random peers to whom it relays the information it has received. The underlying peertopeer communication paradigm is the key to the scalability of the dissemination scheme. Epidemic algorithms have been studied theoretically and their analysis is built on sound mathematical foundations. Although promising, their general applicability to large scale distributed systems has yet to go through addressing many issues. These constitute an exciting research agenda. Index Terms — Scalability, peertopeer, epidemics, information