A grid-based dynamic load balancing approach for data-centric storage in wireless sensor networks

In many data-centric storage techniques, each event corresponds to a hashing location by event type. However, most of them fail to deal with storage memory space due to high percentage of the load is assigned to a relatively small portion of the sensor nodes. Hence, these nodes may fail to deal with the storage of the sensor nodes effectively. To solve the problem, we propose a grid-based dynamic load balancing approach for data-centric storage in sensor networks that relies on two schemes: (1) a cover-up scheme to deal with a problem of a storage node whose memory space is depleted. This scheme can adjust the number of storage nodes dynamically; (2) the multi-threshold levels to achieve load balancing in each grid and all nodes get load balancing. Simulations have shown that our scheme can enhance the quality of data and avoid hotspot of the storage while there are a vast number of the events in a sensor network.