A novel shifting balance theory-based approach to optimization of an energy-constrained modulation scheme for wireless sensor networks

This paper presents a new approach to optimization of an energy-constrained modulation scheme for wireless sensor networks by taking advantage of a novel bio-inspired optimization algorithm. The algorithm is inspired by Wrightpsilas shifting balance theory (SBT) of evolution in population genetics. The total energy consumption of an energy-constrained modulation scheme is minimized by using the new SBT-based optimization algorithm. The results obtained by this new algorithm are compared with other popular optimization algorithms. Numerical experiments are performed to demonstrate that the SBT-based algorithm could be used as an efficient optimizer for solving the optimization problems arising from currently emerging energy-efficient wireless sensor networks.