Adaptive data aggregation and energy efficiency using network coding in a clustered wireless sensor network: An analytical approach

Abstract

In an energy-constraint wireless sensor network (WSN), the sensor nodes near the Sink deplete their energy quickly due to heavy traffic and create a bottleneck zone. In a large monitoring area, the sensor nodes in a cluster may communicate with the cluster head using multi-hop mode. A bottleneck effect can also be created near the cluster heads in a cluster based WSN with several clusters. The clustering technique (along with data aggregation) exploits the data correlation among the sensors’ data and provides opportunities for reduction of energy consumption in WSN. Integrating an energy efficient scheme, namely, network coding, with clustering and duty cycling may facilitate the design of a new cluster based data collection scheme. This work proposes an energy efficient adaptive data aggregation strategy using network coding (ADANC) which improves the energy efficiency in a cluster based duty-cycled WSN. A set of nodes (one-hop away from the cluster head) act as network coder nodes and rest of the nodes act as simple relay nodes in a cluster. The network coder nodes also act as aggregation points, opportunistically, based on the level of data correlation. The proposed ADANC strategy provides reduction of traffic inside a cluster and thus improves the energy efficiency of the bottleneck zone. It has been shown that the packet delivery ratio improves with the proposed scheme in a cluster. The improvement in energy efficiency with ADANC scheme has been analyzed and the upper bound of network lifetime has been estimated. A detailed theoretical analysis has been performed for a cluster based duty cycled WSN.