The Experts below are selected from a list of 145410 Experts worldwide ranked by ideXlab platform
Devavrat Shah - One of the best experts on this subject based on the ideXlab platform.
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Information Dissemination via network coding
International Symposium on Information Theory, 2006Co-Authors: Damon Moskaoyama, Devavrat ShahAbstract:We study distributed algorithms, also known as gossip algorithms, for Information Dissemination in an arbitrary connected network of nodes. Distributed algorithms have applications to peer-to-peer, sensor, and ad hoc networks, in which nodes operate under limited computational, communication, and energy resources. These constraints naturally give rise to "gossip? algorithms: schemes in which nodes repeatedly communicate with randomly chosen neighbors, thus distributing the computational burden across all the nodes in the network and making the computation robust against node failures. Information Dissemination based on network coding was introduced by Deb and Medard. They showed the virtue of coding by analyzing a coding algorithm for a complete graph. Although their scheme generalizes to arbitrary graphs, the analysis does not. We present analysis of this algorithm for arbitrary graphs. Specifically, we find that the Information Dissemination time is naturally related to the spectral properties of the underlying network graph. Our results provide insight into how the graph topology affects the performance of the coding-based Information Dissemination algorithm.
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ISIT - Information Dissemination via Network Coding
2006 IEEE International Symposium on Information Theory, 2006Co-Authors: Damon Mosk-aoyama, Devavrat ShahAbstract:We study distributed algorithms, also known as gossip algorithms, for Information Dissemination in an arbitrary connected network of nodes. Distributed algorithms have applications to peer-to-peer, sensor, and ad hoc networks, in which nodes operate under limited computational, communication, and energy resources. These constraints naturally give rise to "gossip? algorithms: schemes in which nodes repeatedly communicate with randomly chosen neighbors, thus distributing the computational burden across all the nodes in the network and making the computation robust against node failures. Information Dissemination based on network coding was introduced by Deb and Medard. They showed the virtue of coding by analyzing a coding algorithm for a complete graph. Although their scheme generalizes to arbitrary graphs, the analysis does not. We present analysis of this algorithm for arbitrary graphs. Specifically, we find that the Information Dissemination time is naturally related to the spectral properties of the underlying network graph. Our results provide insight into how the graph topology affects the performance of the coding-based Information Dissemination algorithm.
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Information Dissemination via Gossip: Applications to Averaging and Coding
arXiv: Networking and Internet Architecture, 2005Co-Authors: Damon Mosk-aoyama, Devavrat ShahAbstract:We study distributed algorithms, also known as {\em gossip} algorithms, for Information Dissemination in an arbitrary connected network of nodes. Distributed algorithms have applications to peer-to-peer, sensor, and ad hoc networks, in which nodes operate under limited computational, communication, and energy resources. These constraints naturally give rise to ``gossip'' algorithms: schemes in which nodes repeatedly communicate with randomly chosen neighbors, thus distributing the computational burden across all the nodes in the network. We analyze the Information Dissemination problem under the gossip constraint for arbitrary networks, and find that the Information Dissemination time of a gossip algorithm is strongly related to the isoperimetric properties of the underlying graph. As an application of these results, we study two seemingly unrelated important questions: {\em distributed averaging} and {\em coding based Information Dissemination}. Finally, we apply our results to several classes of graphs: grid graph, expander graphs, and complete graphs.
Zhang Jun - One of the best experts on this subject based on the ideXlab platform.
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The Application of Information Dissemination in Rural Areas Based on Social Networks
Information Sciences, 2012Co-Authors: Zhang JunAbstract:This paper analyzes the meanings and characteristics of Information Dissemination under the modern Information technology,proposed to use social networks in Information Dissemination in rural areas;this paper discusses the role of social networks in rural Information Dissemination in theory,then introduces the successful experience of SoRuraLL,which is an Information Dissemination and learning platform in rural areas based on social networks in European,hoping to bring inspiration for Information technology use in rural in our country,thus make full use of modern Information technologies and social networks,disseminate Information to rural areas,so that farmers can participate in the Information Dissemination and exchange of Information fully.
Hu Ji-min - One of the best experts on this subject based on the ideXlab platform.
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Mechanism of Information Dissemination under Socialization Networking Environment
Information Sciences, 2015Co-Authors: Hu Ji-minAbstract:The study of Information Dissemination based on users' relationship under socialization net-working environment is of important significance. This article started with the analysis of development ofInformation Dissemination mode, including non-linear Dissemination based on users' relationship, dissem-ination of low threshold and equalization, and Dissemination of cascade and value-added of Information.Based on the network Information Dissemination mode, a socialization Information Dissemination modewas proposed, and was interpreted from the aspects of users' relationship and socialization media.
Xuemin Sherman Shen - One of the best experts on this subject based on the ideXlab platform.
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Epidemic Information Dissemination in Mobile Social Networks With Opportunistic Links
IEEE Transactions on Emerging Topics in Computing, 2015Co-Authors: Qichao Xu, Kuan Zhang, Zhou Su, Pinyi Ren, Xuemin Sherman ShenAbstract:With the advancement of smartphones, mobile social networks (MSNs) have emerged where Information can be shared among mobile users via opportunistic peer-to-peer links. Since the social ties and users' behaviors in MSNs have diverse characteristics, the Information Dissemination in MSNs becomes a new challenge. In particular, mobile users' interested Information may vary, which can significantly affect the Information Dissemination. In this paper, we develop an analytical model to analyze the epidemic Information Dissemination in MSNs. We first adopt preimmunity and immunity to represent the features of mobile nodes when they change their interests. Then, the Information Dissemination mechanism is introduced with four proposed Dissemination rules according to the process of the epidemic Information Dissemination. We develop the analytical model through ordinary differential equations to mimic epidemic Information Dissemination in MSNs. The trace-driven simulation demonstrates that our analytical model is more accurate to mimic epidemic Information Dissemination than other existing ones.
Qichao Xu - One of the best experts on this subject based on the ideXlab platform.
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Epidemic Information Dissemination in Mobile Social Networks With Opportunistic Links
IEEE Transactions on Emerging Topics in Computing, 2015Co-Authors: Qichao Xu, Kuan Zhang, Zhou Su, Pinyi Ren, Xuemin Sherman ShenAbstract:With the advancement of smartphones, mobile social networks (MSNs) have emerged where Information can be shared among mobile users via opportunistic peer-to-peer links. Since the social ties and users' behaviors in MSNs have diverse characteristics, the Information Dissemination in MSNs becomes a new challenge. In particular, mobile users' interested Information may vary, which can significantly affect the Information Dissemination. In this paper, we develop an analytical model to analyze the epidemic Information Dissemination in MSNs. We first adopt preimmunity and immunity to represent the features of mobile nodes when they change their interests. Then, the Information Dissemination mechanism is introduced with four proposed Dissemination rules according to the process of the epidemic Information Dissemination. We develop the analytical model through ordinary differential equations to mimic epidemic Information Dissemination in MSNs. The trace-driven simulation demonstrates that our analytical model is more accurate to mimic epidemic Information Dissemination than other existing ones.