Publication:
Dynamic Random Replication for Data Centric Storage

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2010-10
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Association for Computing Machinery
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Abstract
This paper presents a novel framework for Data Centric Storage in a wireless sensor and actor network that enables the use of a randomly-selected set of data replication nodes which also change over the time. This allows reducing the average network traffic and energy consumption by adapt-ing the number of replicas to applications’ traffic, while bal-ancing energy burdens by varying their location. To that end we propose and validate a simple model to determine the optimal number of replicas, in terms of minimizing av-erage traffic/energy consumption, from the measured ap-plications’ production/consumption traffic. Simple proto-cols/mechanisms are proposed to decide when the current set of replication nodes should be changed, to enable new applications and sensor nodes to efficiently bootstrap into a working sensor network, to recover from failing nodes, and to adapt to changing conditions. Extensive simulations demon-strate that our approach can extend a sensor network’s life-time by at least a 60%, and up to a factor of 10x depending on the lifetime criterion being considered.
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This work is at: 13th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM' 10), took pkace October, 17-21, 2010, in Bodrum (Turquía). This web site is:http://www.cmpe.boun.edu.tr/mswim2010/
Keywords
Wireless sensor and actor networks, Data-Centric Storage (DCS), Random Replication, Epoch, Optimization, WSAN
Bibliographic citation
Proceedings of the 13th ACM International Conference on Modeling, Analysis, and Simulation of Wireless and Mobile Systems (2010), pp. 393-402