GWO-Based Power Allocation Optimization Algorithm for Consumer IoT Networks

The Internet of Things (IoT) can realize intelligent perception, and has been widely used in various consumer application scenarios. The consumer IoT has become an emerging industry and an important component in the field of consumer electronics, which has led to the vigorous development of the smart consumer industry. With the leapfrog improvement of the new generation of information technology such as fifth generation (5G) communication, big data and artificial intelligence(AI), the consumer IoT applications have also ushered in explosive development. However, with the increase of consumer electronic equipments, energy consumption has become a global problem. In this paper, with decode-and-forward (DF) relaying, the consumer IoT power allocation optimization is investigated. First, we derive novel mathematical expressions to analyze outage probability (OP). Then, employing the OP analysis results, we investigate the OP performance minimization problem through power allocation optimization. Considering the advantages of grey wolf optimization(GWO), an optimization algorithm for mobile power allocation is proposed. The proposed GWO approach carries out an comparison with other optimization algorithms. After different comparisons, it shows that GWO algorithm can obtain a shorter running time and a smaller OP. In terms of running time, GWO is 81% faster than genetic algorithm.