Multi-objective design of energy harvesting enabled wireless networks based on evolutionary genetic optimisation

What is it about?

Sustainable operation of energy-restrained wireless network services requires multiple objectives to be satisfied synchronously. Among these objectives, reduced spectrum outage, energy conservation, and minimal packet transmission failures considerably effect the energy harvesting operation of these networks. These three objectives are associated with disparate protocol layers incorporating the transport, MAC and physical layers of traditional networking architecture. In this paper, we investigate energy harvesting wireless communications by formulating the multi-objective optimization problem comprising of these global networking criteria which are simultaneously optimized with heuristic design procedure. For this, we employ Pareto-based evolutionary genetic algorithm technique built in the wireless network design and operation to find the optimal set of all non-dominated solutions traversing the entire design search space. Besides, iterative implementation of the presented genetic optimization model with distinct feasible integrations of crossover and mutation operations is performed to evaluate the proficiency of the proposed scheme for evaluating the Pareto-optimal frontier set. The influence of different combinations of these operations is examined and adaptively applied with appropriate genetic parameters tuning for efficient meta-heuristic search through the candidate solution space. Simulation results demonstrate that the proposed hybrid genetic mechanism outperforms the existing methods in terms of throughput, energy efficiency and loss rate.

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