Researcher:
İskender, Emre

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Master Student

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Emre

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İskender

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İskender, Emre

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2008 - 20094

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Researcher Of Publications: search.filters.isAuthorOfPublication.e4ec38a6-08ae-411b-b634-a3d5c6d11918

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Now showing 1 - 4 of 4
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    Topology dependent information dissemination in P2P networks for anti-entropy algorithmS
    (Ieee, 2008) N/A; N/A; Department of Computer Engineering; Department of Mathematics; İskender, Emre; Özkasap, Öznur; Çağlar, Mine; Master Student; Faculty Member; Faculty Member; Department of Computer Engineering; Department of Mathematics; Graduate School of Sciences and Engineering; College of Engineering; College of Sciences; N/A; 113507; 105131
    Analyzing the behavior of epidemic spreading in a network is a good way of modeling several network phenomena. There are several studies analyzing the spreading of email viruses. Spreading of epidemics is also a good model for several types of information dissemination in distributed systems. In this study, we examine spreading of epidemics for anti-entropy algorithms in a peer-to-peer network with any given topology. We derive nodes' exact probability distributions of being infected in each epidemic cycle.
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    Topology dependent information dissemination in P2P networks for anti-entropy algorithms
    (IEEE, 2008) N/A; Department of Computer Engineering; Department of Mathematics; Özkasap, Öznur; Çağlar, Mine; İskender, Emre; Faculty Member; Faculty Member; Master Student; Department of Computer Engineering; Department of Mathematics; College of Engineering; College of Sciences; Graduate School of Sciences and Engineering; 113507; 105131; N/A
    Analyzing the behavior of epidemic spreading in a network is a good way of modeling several network phenomena. There are several studies analyzing the spreading of email viruses. Spreading of epidemics is also a good model for several types of information dissemination in distributed systems. In this study, we examine spreading of epidemics for anti-entropy algorithms in a peer-to-peer network with any given topology. We derive nodes' exact probability distributions of being infected in each epidemic cycle.
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    Analytical model for topology dependence in peer-to-peer anti-entropy spreading
    (Bogazici University, 2008) N/A; Department of Computer Engineering; Department of Mathematics; Özkasap, Öznur; Çağlar, Mine; İskender, Emre; Faculty Member; Faculty Member; Master Student; Department of Computer Engineering; Department of Mathematics; College of Engineering; College of Sciences; Graduate School of Sciences and Engineering; 113507; 105131; N/A
    We examine spreading of epidemics for an anti-entropy algorithm in networks with various P2P (peer-to-peer) overlay topologies. Neighborhood knowledge among peers and information exchange based on proximity are considered. Our analytical model for SI (Susceptible-Infected) epidemics involves equations for calculating the infection probability of each peer in consecutive epidemic rounds as a function of the topology. Using numerical evaluations, we study the effect of graph properties on dissemination as an aspect of real world P2P overlays
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    Stepwise fair-share buffering for gossip-based peer-to-peer data dissemination
    (Elsevier, 2009) Ahi, Emrah; Department of Computer Engineering; Department of Mathematics; N/A; N/A; N/A; Özkasap, Öznur; Çağlar, Mine; Çem, Emrah; İskender, Emre; Faculty Member; Faculty Member; PhD Student; Master Student; Department of Computer Engineering; Department of Mathematics; College of Engineering; College of Sciences; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; 113507; 105132; N/A; N/A
    We consider buffer management in support of large-scale gossip-based peer-to-peer data dissemination protocols. Coupled with an efficient buffering mechanism, system-wide buffer usage can be optimized while providing reliability and scalability in such protocols. We propose a novel approach, stepwise fair-share buffering, that provides uniform load distribution and reduces the overall buffer usage where every peer has a partial view of the system. We report and discuss the comparative performance results with existing buffering approaches as well as random buffering which serves as a benchmark. We present separate evaluations of bufferer selection and gossip-based data dissemination. Reliability, content dissemination time, message delay, buffering delay, and minimum buffer requirements are considered as the key metrics investigated through simulations. The performance of our approach in the case of multiple senders, link failures with multiple bufferers, and scalability to larger networks are investigated. Several power-law and hierarchical overlay topologies are considered. Analytical bounds for reliability of dissemination are also provided.