Emrah Çem

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—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(More)
This study addresses the problem of discovering frequent items in unstructured P2P networks. This problem is relevant for several distributed services such as cache management, data replication, sensor networks and security. We make three contributions to the current state of the art. First, we propose a fully distributed Protocol for Frequent Item Set(More)
We address the problem of discovering frequent items in unstructured P2P networks which is relevant for several distributed services such as cache management, data replication, query refinement, topology optimization and security. This study makes the following contributions to the current state of the art. First, we propose and develop a fully distributed(More)
For large scale distributed systems, designing energy efficient protocols and services has become as significant as considering conventional performance criteria like scalability, reliability, fault-tolerance and security. We consider frequent item set discovery problem in this context. Although it has attracted attention due to its extensive applicability(More)
Studying structural and functional characteristics of large scale graphs (or networks) has been a challenging task due to the related computational overhead. Hence, most studies consult to sampling to gather necessary information to estimate various features of these big networks. On the other hand, using a best effort approach to graph sampling within the(More)
• Power awareness of flat and hierarchical epidemics in P2P systems is addressed. • We developed energy cost model formulations for flat and hierarchical epidemics. • We proposed a dominating-set based and power-aware hierarchical epidemic approach. • Through large scale simulations on PeerSim, we compared the epidemic approaches. • We analyzed the effect(More)
We propose estimators for popular clustering coefficient measures 1) network average clustering coefficient and 2) global clustering coefficient (aka transitivity). Unlike most of previous studies estimating clustering coefficients, we do not use independent vertex sampling as it is either unavailable or inefficient to implement in most Online Social(More)
Estimating the structural characteristics of large graphs from a sample is a classical problem. In this study, we propose asymptotically unbiased estimators for the average degree characteristic of a network under ego-centric sampling. In this sampling design, we first sample a number of vertices called ego vertices from the underlying graph and then obtain(More)