Enabling Heterogeneous mMTC by Energy-Efficient and Connectivity-Aware Clustering and Routing
Zhehan Li, Jun shuo Chen, Rui Ni, Si Chen, Li Jun Xu, Qiyang Zhao · 2017
Clustering is the fundamental of data aggregation for energy-efficient Low Power Wide Area (LPWA) networks while routing is also essential to solve the connectivity problem. In this paper, a novel clustering and routing algorithm based on a 2-level genetic framework is proposed, taking both energy-efficiency and connectivity into consideration, for massive Machine Type Communication (mMTC), where ultra-heterogeneous types of nodes may exist. The performance of the proposed algorithm is compared with the state-of-the-art and a benchmark. It doubles the network lifetime compared with the benchmark if defining it as the number of collections when the first dead node appears. The probability of successful collection is also significantly improved since connectivity is considered in the algorithm. The inter-networking gain in the heterogeneous scenario is also investigated.