NUNS: A Nonuniform Network Split Method for Data-Centric Storage Sensor Networks

If data have the same value frequently in a data-centric storage sensor network, then the load is concentrated on a specific sensor node and the node consumes energy rapidly. In addition, if the sensor network is expanded, the routing distance to the target sensor node becomes longer in data storing and query processing, and this increases the communication cost of the sensor network. This paper proposes a nonuniform network split(NUNS) method that distributes the load among sensor nodes in data-centric storage sensor networks and efficiently reduces the communication cost of expanding sensor networks. NUNS splits a sensor network into partitions of nonuniform sizes in a way of minimizing the difference in the number of sensor nodes and in the size of partitions, and it stores data occurring in each partition in the sensor nodes of the partition. In addition, NUNS splits each partition into zones of nonuniform sizes as many as the number of sensor nodes in the partition in a way of minimizing the difference in the size of the split zones and assigns each zone to the processing area of each sensor node. Finally, we performed various performance evaluations and proved the superiority of NUNS to existing methods.