Title | ||
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Economic Incentive Schemes For Improving Availability Of Rare Data In Mobile-P2p Networks |
Abstract | ||
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In mobile ad-hoc peer-to-peer (M-P2P) networks, data availability is typically low due to rampant free-riding, frequent network partitioning and mobile resource constraints. Rare data items are those, which get sudden bursts in accesses based on events as they are only hosted by a few peers in comparison to the network size. Thus, they may not be available within few hops of query-issuing peers. This work proposes E-Rare, a novel economic incentive model for improving rare data availability by means of licensing-based replication in M-P2P networks. In E-Rare, each data item is associated with four types of prices (in virtual currency), which provide different rights to the query-issuer concerning the usage of the item. E-Rare requires a query-issuer to pay one of these prices for its queried data item to the query-serving peer, thereby effectively increasing data availability and combating free-riders. The main contributions of this paper are three-fold. First, it provides incentives for replication of rare data items by means of a novel licensing mechanism, thereby improving rare data availability. Second, it provides additional incentives for MPs to collaborate in groups, thereby further improving rare data availability. Third, a detailed performance evaluation has been done to show the improvement in query response times and availability of rare data items in M-P2P networks. |
Year | Venue | Keywords |
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2017 | INTERNATIONAL JOURNAL OF NEXT-GENERATION COMPUTING | Mobile Peer-to-Peer, economic incentive scheme, rare data availability |
Field | DocType | Volume |
Network size,Data availability,Incentive,Computer security,Computer science,Virtual currency | Journal | 8 |
Issue | ISSN | Citations |
1 | 2229-4678 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
---|---|---|---|
Nilesh Padhariya | 1 | 21 | 3.37 |
Anirban Mondal | 2 | 386 | 31.29 |
Sanjay Kumar Madria | 3 | 892 | 276.61 |
Masaru Kitsuregawa | 4 | 3188 | 831.46 |