Energy-Efficient Data Aggregation Routing and Duty-Cycle Scheduling in Cluster-Based Sensor Networks

The lifetime of a network, dependent upon battery capacity and energy consumption efficiency, plays an important role in wireless sensor networks. In this paper, the reduction of energy consumption is investigated by the considerations of the effects of cluster-based data aggregation routing in conjunction with well-scheduled and dynamic power range. Modeling power consumption as a mixed integer- and nonlinear-programming problem, the objective function provides the basis by which the total energy consumption is minimized. The problem of cluster construction and data aggregation trees were proven NP- complete. Thus, we proposed heuristics for cluster construction (i.e., AvgEnergy and MaxNumS) and data aggregation routing (i.e., CDAR). We also propose a duty cycle scheduling scheme and dynamic radius to ensure the total energy consumption is minimized. The experimental results show that the heuristic proposed above outperforms other modified existing algorithms.

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