In this tutorial paper, we study three specific applications: opinion formation in social networks, centrality measures in complex networks and estimation problems in large-scale power systems. These applications fall...
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In this tutorial paper, we study three specific applications: opinion formation in social networks, centrality measures in complex networks and estimation problems in large-scale power systems. These applications fall under a general framework which aims at the construction of algorithms for distributed computation over a network. The two key ingredients of randomization and time-averaging are used, together with a local gossip communication protocol, to obtain convergence of these distributedalgorithms to the global synchronous dynamics. (c) 2015 European Control Association. Published by Elsevier Ltd. All rights reserved.
In this tutorial paper, we study three specific applications: opinion formation in social networks, centrality measures in complex networks and estimation problems in large-scale power systems. These applications fall...
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In this tutorial paper, we study three specific applications: opinion formation in social networks, centrality measures in complex networks and estimation problems in large-scale power systems. These applications fall under a general framework which aims at the construction of algorithms for distributed computation over a network. The two key ingredients of randomization and time-averaging are used, together with a local gossip communication protocol, to obtain convergence of these distributedalgorithms to the global synchronous dynamics. (c) 2015 European Control Association. Published by Elsevier Ltd. All rights reserved.
This paper studies a few randomizedalgorithms (e.g., random walks, gossip) in peer-to-peer networks. We leverage the Docker virtual container technology to develop implementations of the peer-to-peer networks and of ...
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This paper studies a few randomizedalgorithms (e.g., random walks, gossip) in peer-to-peer networks. We leverage the Docker virtual container technology to develop implementations of the peer-to-peer networks and of these distributed randomized algorithms executing on top of them. We can thus analyze their behavior and performance in realistic settings. We further consider the problem of identifying high-risk bottleneck links in the network with the objective of improving the resilience and reliability of peer-to-peer networks. We propose a randomized algorithm to solve this problem and evaluate its performance by simulations.
Broadcasting is a fundamental problem for wireless multi-hop networks such as wireless ad hoc and sensor networks. In this paper, we study distributed robust time-efficient global broadcasting for SINR-based (i.e., Si...
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Broadcasting is a fundamental problem for wireless multi-hop networks such as wireless ad hoc and sensor networks. In this paper, we study distributed robust time-efficient global broadcasting for SINR-based (i.e., Signal-to-Interference-plus-Noise-Ratio-based) multi-channel wireless multihop networks subject to channel disruption. In this study, we make the following assumptions: i) for successful packet reception, the SINR at receivers must exceed a certain threshold;ii) an adversary exists in the network, which uniformly and randomly chooses t > 0 channels to disrupt from total F > 1 available channels in every round. To address the broadcasting issue in such networks, we first propose a degree-aware broadcasting algorithm and then propose a degree-independent broadcasting algorithm. The proposed algorithms elaborately integrate distributed channel selection and transmission scheduling at different nodes while considering the following factors: the impact of SINR constraint, availability of channels, sending probability on selected channel, presnce of adversary, with and without node degree information. We present the detailed design of the two algorithms. We deduce their worst-case time performance to accomplish the task of global broadcasting with high probability. We further prove that both algorithms can still preserve the same time performance under more powerful oblivious adversary and weakly adaptive adversary. Simulation results show that the proposed algorithms have satisfactory average-case time performance.
We study a plurality-consensus process in which each of n anonymous agents of a communication network initially supports a color chosen from the set [k]. Then, in every round, each agent can revise his color according...
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We study a plurality-consensus process in which each of n anonymous agents of a communication network initially supports a color chosen from the set [k]. Then, in every round, each agent can revise his color according to the colors currently held by a random sample of his neighbors. It is assumed that the initial color configuration exhibits a sufficiently large bias s towards a fixed plurality color, that is, the number of nodes supporting the plurality color exceeds the number of nodes supporting any other color by s additional nodes. The goal is having the process to converge to the stable configuration in which all nodes support the initial plurality. We consider a basic model in which the network is a clique and the update rule (called here the 3-majority dynamics) of the process is the following: each agent looks at the colors of three random neighbors and then applies the majority rule (breaking ties uniformly). We prove that the process converges in time O(min{k, (n/log n)(1/3)} log n) with high probability, provided that s >= c root min{2k, (n/log n)(1/3)} n log n. We then prove that our upper bound above is tight as long as k <= (n/log n)(1/4). This fact implies an exponential time-gap between the plurality-consensus process and the median process (see Doerr et al. in Proceedings of the 23rd annual ACM symposium on parallelism in algorithms and architectures (SPAA' 11), pp 149-158. ACM, 2011). A natural question is whether looking at more (than three) random neighbors can significantly speed up the process. We provide a negative answer to this question: in particular, we show that samples of polylogarithmic size can speed up the process by a polylogarithmic factor only.
We consider distributed plurality consensus on a complete graph of size n with k initial opinions in the following asynchronous communication model. Each node is equipped with a random Poisson clock with parameter lam...
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ISBN:
(纸本)9781450349925
We consider distributed plurality consensus on a complete graph of size n with k initial opinions in the following asynchronous communication model. Each node is equipped with a random Poisson clock with parameter lambda = 1. Whenever a node's clock ticks, it samples some neighbors uniformly at random and adjusts its opinion according to the sample. distributed plurality consensus has been deeply studied in the synchronous communication model. A prominent example is the so-called Two-Choices protocol, where in each round, every node chooses two neighbors uniformly at random, and if the two sampled opinions coincide, then that opinion is adopted. This protocol is very efficient when k = 2. If k = O(n(epsilon)) for some small epsilon, we show that it converges to the initial plurality opinion within O(k . logn) rounds, w.h.p., as long as the initial difference between the largest and second largest opinion is Omega(root nlogn). On the negative side, we show that there are cases in which Omega(k) rounds are needed, w.h.p. To beat this lower bound, we combine the Two-Choices protocol with push-pull broadcasting. We divide the process into several phases, where each phase consists of a two-choices round followed by several broadcasting rounds. Our main contribution is a non-trivial adaptation of this approach to the above asynchronous model. If the support of the most frequent opinion is at least (1 + epsilon) times that of the second-most frequent one and k = O(exp(logn/log logn)), then our protocol achieves the best possible run time of O(logn), w.h.p. Key to our adaptation is that we relax full synchronicity by allowing o(n) nodes to be poorly synchronized, and the well synchronized nodes are only required to be within a certain time difference from one another. We enforce this "sufficient" synchronicity by introducing a novel gadget into the protocol. Other parts of the adaptation are made to work using arguments and techniques based on a Polya urn model.
In this study, the decentralized common reference frame estimation problem for multiagent systems in the absence of any common coordinate system is investigated. Each agent is deployed in a 2-D space and can only meas...
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In this study, the decentralized common reference frame estimation problem for multiagent systems in the absence of any common coordinate system is investigated. Each agent is deployed in a 2-D space and can only measure the relative distance of neighboring agents and the angle of their line of sight in its local reference frame;no relative attitude measurement is available. Only asynchronous and random pairwise communications are allowed between neighboring agents. The convergence properties of the proposed algorithm are characterized, and its sensitiveness against additive noise on the relative distance measurements is investigated. An experimental validation of the effectiveness of the proposed algorithm is provided.
Motivated by the needs and success of projects such as SETI@home and genome@home, we propose an architecture for a sustainable large-scale peer-to-peer environment for distributed cycle sharing among Internet hosts. S...
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Motivated by the needs and success of projects such as SETI@home and genome@home, we propose an architecture for a sustainable large-scale peer-to-peer environment for distributed cycle sharing among Internet hosts. Such networks are characterized by highly dynamic state due to high arrival and departure rates. This makes it difficult to build and maintain structured networks and to use state-based resource allocation techniques. We build our system to work in an environment similar to Current file-sharing networks such as Gnutella and Freenet. In doing so, we are able to leverage vast network resources while providing resilience to random failures, low network overhead, and an open architecture for resource brokering. This paper describes the underlying analytical and algorithmic substrates based on randomization for job distribution, replication, monitoring, aggregation and oblivious resource sharing and communication between participating hosts. We support our claims of robustness and scalability analytically with high probabilistic guarantees. Our algorithms do not introduce any state dependencies, and hence Lire resilient to dynamic node arrivals, departures, and failures. We Support all analytical claims with a detailed simulation-based evaluation of our distributed framework. (c) 2005 Elsevier B.V. All rights reserved.
Motivated by the needs and success of projects such as SETI@home and genome@home, we propose an architecture for a sustainable large-scale peer-to-peer environment for distributed cycle sharing among Internet hosts. S...
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Motivated by the needs and success of projects such as SETI@home and genome@home, we propose an architecture for a sustainable large-scale peer-to-peer environment for distributed cycle sharing among Internet hosts. Such networks are characterized by highly dynamic state due to high arrival and departure rates. This makes it difficult to build and maintain structured networks and to use state-based resource allocation techniques. We build our system to work in an environment similar to Current file-sharing networks such as Gnutella and Freenet. In doing so, we are able to leverage vast network resources while providing resilience to random failures, low network overhead, and an open architecture for resource brokering. This paper describes the underlying analytical and algorithmic substrates based on randomization for job distribution, replication, monitoring, aggregation and oblivious resource sharing and communication between participating hosts. We support our claims of robustness and scalability analytically with high probabilistic guarantees. Our algorithms do not introduce any state dependencies, and hence Lire resilient to dynamic node arrivals, departures, and failures. We Support all analytical claims with a detailed simulation-based evaluation of our distributed framework. (c) 2005 Elsevier B.V. All rights reserved.
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