Effective Data Aggregation Supported by Dynamic Routing in Wireless Sensor Networks

Abstract

Data aggregation is an main method to conserve energy in wireless sensor network (WSN). Prior work on data aggregation protocols are generally based on static routing schemes, such as tree-based, cluster-based or chain-based routing schemes. Although they can save energy to some extent, in dynamic scenarios where the source nodes are changing frequently, they will not only incur high overhead to continuously reconstruct the routing but also can not reduce the communication overhead effectively. Our work aims to design an effective data aggregation mechanism supported by dynamic routing (DASDR) which can adapt to different scenarios without incurring much overhead. Enlightened by the concept of potential field in the discipline of physics, the dynamic routing in DASDR is designed based on two potential fields: depth potential field which guarantees packets reaching the sink at last and queue potential field which makes packets more spatially convergent and thus data aggregation will be more efficient. Simulation results show that DASDR is more effective in energy savings as well as scales well with regard to the network size.