8,777 research outputs found

    FLEET: Butterfly Estimation from a Bipartite Graph Stream

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    We consider space-efficient single-pass estimation of the number of butterflies, a fundamental bipartite graph motif, from a massive bipartite graph stream where each edge represents a connection between entities in two different partitions. We present a space lower bound for any streaming algorithm that can estimate the number of butterflies accurately, as well as FLEET, a suite of algorithms for accurately estimating the number of butterflies in the graph stream. Estimates returned by the algorithms come with provable guarantees on the approximation error, and experiments show good tradeoffs between the space used and the accuracy of approximation. We also present space-efficient algorithms for estimating the number of butterflies within a sliding window of the most recent elements in the stream. While there is a significant body of work on counting subgraphs such as triangles in a unipartite graph stream, our work seems to be one of the few to tackle the case of bipartite graph streams.Comment: This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in Seyed-Vahid Sanei-Mehri, Yu Zhang, Ahmet Erdem Sariyuce and Srikanta Tirthapura. "FLEET: Butterfly Estimation from a Bipartite Graph Stream". The 28th ACM International Conference on Information and Knowledge Managemen

    QoE in Pull Based P2P-TV Systems: Overlay Topology Design Tradeoff

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    Abstract—This paper presents a systematic performance anal-ysis of pull P2P video streaming systems for live applications, providing guidelines for the design of the overlay topology and the chunk scheduling algorithm. The contribution of the paper is threefold: 1) we propose a realistic simulative model of the system that represents the effects of access bandwidth heterogeneity, latencies, peculiar characteristics of the video, while still guaranteeing good scalability properties; 2) we propose a new latency/bandwidth-aware overlay topology design strategy that improves application layer performance while reducing the underlying transport network stress; 3) we investigate the impact of chunk scheduling algorithms that explicitly exploit properties of encoded video. Results show that our proposal jointly improves the actual Quality of Experience of users and reduces the cost the transport network has to support. I
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