On Optimal Replication Group Splits in P2P Data Stores Based on the Hypercube (original) (raw)
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The availability of critical services and their data can be significantly increased by replicating them on multiple systems connected with each other, even in the face of system and network failures. In some platforms such as peerto-peer (P2P) systems, their inherent characteristic mandates the employment of some form of replication to provide acceptable service to their users. However, the problem of how best to replicate data to build highly available peer-to-peer systems is still an open problem. In this paper, we propose an approach to address the data replication problem on P2P systems. The proposed scheme is compared with other techniques and is shown to require less communication cost for an operation as well as provide higher degree of data availability.
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One way for Peer-to-Peer data stores to achieve high data availability is to replicate their data. This is necessary to counter the effects of peer population dynamics also known as churn. A consequence of churn is that locating a data item may require a peer to resend search messages thus introducing additional communication. A formal model of this communication pertaining to data item lookups is introduced and evaluated using simulation in this paper. Results hold true for hypercube-based P2P data stores.
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Peer-to-peer (P2P) technology is an emerging approach to overcoming the limitations of the traditional client server architecture. However, building a highly available P2P system is quite challenging, in particular a P2P storage system. The reason is due to the fundamental nature of P2P systems: peers can join and leave at any time without any notice. Replication is one of the strategies in overcoming the unpredictable behavior of peers. A good replication algorithm should use the minimum number of replicas to provide the desired availability of data. The popular approach in the previous studies is a random placement of replicas, but it ignores the wide difference in the availability of each peer. In this paper, we develop a replica placement algorithm which exploits the availability pattern of each individual peer. By comparing our algorithm with a random placement scheme, we show that our algorithm dramatically improves the data availability with moderate overhead in terms of memory consumption and processing time in both ideal and practical conditions.
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