STARR-DCS: Spatio-Temporal Adaptation of Random Replication for Data Centric Storage

This paper presents a novel framework for Data Centric Storage in a Wireless Sensor and Actor Network (WSAN) that enables the use of a randomly-selected set of data replication nodes, which also change over the time. This enables reductions in the average network traffic and energy consumption by adapting the number of replicas to applications' traffic, while balancing energy burdens by varying their locations. To that end the authors propose and validate a simple model to determine the optimal number of replicas, in terms of minimizing average traffic/energy consumption, based on measurements of applications' production and consumption traffic.

Provided by: Association for Computing Machinery Topic: Networking Date Added: Nov 2011 Format: PDF

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