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Interlaced: fully decentralized churn stabilization for Skip Graph-based DHTs

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English

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As a distributed hash table (DHT) routing overlay, Skip Graph is used in a variety of peer-to-peer (P2P) systems including cloud storage. The overlay connectivity of P2P systems is negatively affected by the arrivals and departures of nodes to and from the system that is known as churn. Preserving connectivity of the overlay network (i.e., the reachability of every pair of nodes) under churn without compromising the overlay latency is a performance challenge in every P2P system including the Skip Graph-based ones. The existing decentralized churn stabilization solutions that are applicable to Skip Graphs mainly optimize the connectivity of the system under churn and do not consider routing latency of overlay as an optimization goal. Additionally, those existing solutions change the message complexity of Skip Graphs, distort its topology, or apply constant message overhead to the system. In this paper, we propose Interlaced, a fully decentralized churn stabilization mechanism for Skip Graphs that provides drastically stronger overlay connectivity and faster search queries without changing the asymptotic complexity of the Skip Graph in terms of storage, computation, and communication. We also propose the Sliding Window De Bruijn Graph (SWDBG ) as a tool to predict the availability of nodes with high accuracy. Our simulation results show that in comparison to the best existing DHT-based solutions, Interlaced improves the overlay connectivity of the Skip Graph under churn with the gain of about 1.73 times. Likewise, compared to the existing availability prediction approaches for P2P systems, SWDBG is about 1.26 times more accurate. A Skip Graph that benefits from Interlaced and SWDBG is about 2.47 times faster on average in routing the queries under churn compared to the best existing solutions. We also present an adaptive extension of Interlaced to be applied to other DHTs, for example, Kademlia.

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Journal of Parallel and Distributed Computing

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Elsevier

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Computer science

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