An energy-efficient clustering routing algorithm for WSN-assisted IoT

Zijing Wang, Xiaoqi Qin, Baoling Liu

Abstract: Machine-type communication (MTC) is endorsed in the fifth-generation (5G) networks to realize innovative IoT based applications, such as smart city and intelligent manufacturing. MTC devices with sensing and communication capabilities can monitor the surrounding environment and transmit the collected information back to Base Station (BS) for further data analysis. The dense deployment of sensing devices calls for a clustering structure to preprocess the redundant data to avoid traffic overload. Moreover, due to limited battery capacity, the energy cost remains a critical concern in such IoT systems. In this paper, we propose an energy-efficient clustering routing algorithm. Considering the non-uniform traffic distribution, we propose an uneven cluster formation scheme for load balancing and energy efficiency. Moreover, we propose a distributed cluster head (CH) rotation mechanism to balance energy consumption within each cluster. As for long distance transmission to BS, we design a dynamic multi-hop routing algorithm among CH nodes based on a proposed distance-and-energy-aware cost function to avoid the energy hole problem. Simulation results show that the performance of our proposed algorithm is competitive in terms of network lifetime, throughput and energy efficiency.