A dynamic geographic hash table for data-centric storage in sensor networks

This paper proposes a dynamic geographic hash table for data-centric storage (DCS) in sensor networks. In DCS systems, data storage locations are determined by data name. The storage locations are obtained through the use of a geographic hash table (GHT) that maps data names to geographic locations. Traditional DCS systems use a static hash function for this purpose, resulting in a static set of nodes serving the network throughout its lifetime. Hence, these nodes may experience unbalanced resource utilization problems and the network will not be capable of dealing with network dynamics such as new sensor deployments or runtime sensor failures. We address these problems by proposing a dynamic GHT solution that relies on two schemes: 1) a temporal-based geographic hash table to achieve overall load balancing among sensor nodes over time; and 2) a location selection scheme based on node contribution potential to proactively adapt the system to network dynamics. Our performance evaluations show that the dynamic GHT can alleviate the resource utilization problem of DCS systems and can prolong the network lifetime significantly