CADRE: A Collaborative replica allocation and deallocation approach for Mobile-P2P networks

Mondal, Anirban; Madria, Sanjay

doi:10.1109/ideas.2006.13

Cited by 22 publications

(16 citation statements)

References 16 publications

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“…It exploits user mobility patterns, and considers load and different levels of replica consistency. The proposal in [31] has discussed both collaborative replica allocation and deallocation in tandem to facilitate optimal replication and to avoid 'thrashing' conditions. However, these proposals do not consider economic schemes.…”

Section: Non-incentive-based Replication In M-p2p Networkmentioning

confidence: 99%

E-ARL: An Economic incentive scheme for Adaptive Revenue-Load-based dynamic replication of data in Mobile-P2P networks

Mondal

Madria

2010

Distrib Parallel Databases

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In mobile ad hoc peer-to-peer (M-P2P) networks, frequent network partitioning occurs due to peer movement or owing to peers switching 'off' their mobile devices. This leads to typically low data availability in M-P2P networks, thereby necessitating data replication. This work proposes E-ARL, which is a novel Economic scheme for Adaptive Revenue-Load-based dynamic replication of data in dedicated M-P2P networks with the aim of improving data availability. Thus, E-ARL considers a mobile cooperative environment, where the MPs are working towards the same goal, and the network performance is facilitated by the economic scheme. E-ARL essentially allocates replicas based on its economic scheme. Each data item has a price in virtual currency. E-ARL requires a query issuing peer to pay the price of its queried data item to the query-serving peer and a commission to relay peers in the successful query path. The main contributions of E-ARL follow. First, it uses an economic scheme for efficiently managing M-P2P resources in a context-aware manner by facilitating effective replica hosting and message relaying by peers. Second, it collaboratively performs bid-based replica allocation to facilitate better quality of service. Third, it incorporates both revenue-balancing and load-balancing to improve peer participation and performance. Fourth, it conserves the energy of low-energy Communicated by Ashfaq Khokhar. 2 Distrib Parallel Databases (2010) 28: 1-31MPs to facilitate network connectivity. Our performance evaluation shows that E-ARL is indeed effective in improving peer participation in M-P2P networks, thereby improving query response times, query success rates, query hop-counts and replica allocation traffic.

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Section: Non-incentive-based Replication In M-p2p Networkmentioning

confidence: 99%

E-ARL: An Economic incentive scheme for Adaptive Revenue-Load-based dynamic replication of data in Mobile-P2P networks

Mondal

Madria

2010

Distrib Parallel Databases

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“…DQ is the range of user-desired data quality (e.g., image resolution, audio quality) provided by the data-providing MP to the query-issuing MP. We consider three discrete levels of DQ i.e., high, medium and low, their values being 1, 0.5 and 0.25 respectively [30,31]. Each MP maintains a table T ,DQ , which contains the following entries: (x%, high), (y%, medium), (z%, low), where x, y, z are error-bounds, whose values are essentially application-dependent and pre-specified by the system at design time.…”

Section: Specifying Constraint Queries In Conquermentioning

confidence: 99%

An economic incentive model for encouraging peer collaboration in mobile-P2P networks with support for constraint queries

Mondal

Madria

2009

Peer-to-Peer Netw. Appl.

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In mobile ad hoc peer-to-peer (M-P2P) networks, economic models become a necessity for enticing non-cooperative mobile peers to provide service. M-P2P users may issue queries with varying constraints on query response time, data quality of results and trustworthiness of the data source. Hence, we propose ConQuer, which is an economic incentive model for the efficient processing of constraint queries in M-P2P networks. ConQuer also provides incentives for peer collaboration in order to improve data availability. The main contributions of ConQuer are three-fold. First, it uses a broker-based economic M-P2P model for processing constraint queries via a Vickrey auction mechanism. Second, it proposes the CR*-tree, a dynamic multidimensional R-tree-based index for constraints of data quality, trust and price of data to determine target peers efficiently. The CR*-tree is hosted by brokers, who can sell it to other peers, thereby encouraging the creation of multiple copies of the index for facilitating routing. Third, it provides incentives for peers to form collaborative peer groups for maximizing data A. Mondal · M. Kitsuregawa availability and revenues by mutually allocating and deallocating data items using royalty-based revenuesharing. Such reallocations facilitate better data quality, thereby further increasing peer revenues. Our performance study shows that ConQuer is indeed effective in answering constraint queries with improved response time, success rate and data quality, and querying hopcounts.

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“…In [5] a way to solve the problem of mobile data networks access based on data replication is proposed. At first, three methods of allocation replica suggested and assuming that the data are not updated.…”

Section: Related Workmentioning

confidence: 99%

Multicast Data Replication Approach for Improving Fault Tolerance in Mobile Ad hoc Networks

Moghaddam¹,

Karimi²

2015

CeN

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Multicast data replication provides a possible solution for improving data accessibility in highly dynamic and fault prone mobile ad hoc environments. Our novel multicast data replication approach operates in a self-organizing manner where the network nodes that has unit host detector construct a connected dominating set (CDS) based on the topology graph by collecting information from neighboring nodes using multicast if gathered data from neighbors have two non-adjacent neighbors then use that virtual backbone for efficient data replication, data search and routing. In this study, we compare our proposed approach with SCALAR and evaluate it in average hop counts and successful delivery ratio with different node numbers and speeds.It is shown that the average hop counts increased but with falling rate and 20 percent successful delivery ratio is achieved, so it is demonstrated that PM act with respect to fault tolerance improvement, power consumption and load balancing is occurred.

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CADRE: A Collaborative replica allocation and deallocation approach for Mobile-P2P networks

Cited by 22 publications

References 16 publications

E-ARL: An Economic incentive scheme for Adaptive Revenue-Load-based dynamic replication of data in Mobile-P2P networks

E-ARL: An Economic incentive scheme for Adaptive Revenue-Load-based dynamic replication of data in Mobile-P2P networks

An economic incentive model for encouraging peer collaboration in mobile-P2P networks with support for constraint queries

Multicast Data Replication Approach for Improving Fault Tolerance in Mobile Ad hoc Networks

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