Data Storage Algorithms Based on Clustering in Wireless Sensor Networks

Abstract

Wireless sensor’s traditional data storage algorithms exist many problems, such as lack of adaptability and load balancing, great energy consumption, long network cycle lifetime, high delay access rate and so on. This paper proposes an adaptive clustering based on data storage (CBDS) algorithm to deal with these problems. Through analysis of the available data storage methods, we studied how to determine data storage nodes under the premise of limited energy of sensor networks and more consumers exist in the network. We concluded a common storage strategy which combines sensor networks set’s centralized storage, local storage and distributed storage. Finally, we did compared experiments between the CBDS algorithm and other related algorithms. Experiments showed that: CBDS has obvious advantages like self-adaptive, load balancing, low access latency and less energy consumption than traditional algorithm. CBDS is more conducive to data storage.