A Cost Model for Storing and Retrieving Data in Wireless Sensor Networks

Abstract

Many applications require storing data in Wireless Sensor Networks (WSNs). For example, in environmental monitoring applications. WSN may archive sensor data for retrieval at periodic intervals. In contrast to conventional network data storage, storing data in WSNs is challenging because of the limited power, memory, and communication bandwidth of WSNs. This paper identifies the critical parameters of WSNs and proposes a cost model for data storage and retrieval. This paper also proposes a distributed algorithm that utilizes the cost model to intelligently distribute excess data from sensor nodes over WSN. The proposed algorithm chooses for remote storage nodes with the most extra memory and the least communication cost. The algorithm also adapts dynamically to changes in the storage requirements of sensor nodes. The benefits of the cost model are experimentally evaluated by using the algorithm in a simulated WSN. Results from the experiments show that as much as 30% more data may be stored in WSN at a slightly higher communication cost when a node's data is distributed across WSN instead of only being stored locally in the node.