Mobile effect reduction in data-centric storage for wireless sensor networks

The future wireless sensor networks (WSNs) are usually scale to size of thousands to millions of sensors deployed in an area to sense events. Therefore, sensors have to manage a huge amount of data. The way how to store data in WSNs can influence the response time and the lifetime of the network. One of the existent works in this domain is called data-centric storage (DCS), and it is a recent research tendency in WSNs. DCS has to face with two problems. First, it uses hash function distribute the load uniformly over the network. When the hash value does not match the position of any node, DCS has to search for the nearest node of the hash value (called home node) to store the data. Sometimes, it can take many hops to find the home node. This process is a communication waste needed to be avoided. Second, in WSNs, there are often mobile nodes. They are one of the causes of routing errors in the network. Routing errors implies retransmissions and information lost. Hence, they are also an energy waste. In this paper, we try to solve those two problems in order to reduce energy waste and prolong the network lifetime. We propose a clustered architecture called C-DCS (clustered data-centric storage) in order to help WSNs to avoid the search for home node and minimising the mobility effect of mobile nodes in the network. Besides, we take advantage of clustered architecture to propose a two-level aggregation method to reduce the number of communication in the network. By theoretical and simulation result, we prove that C-DCS reduces the number of transmission which improves the network lifetime.