Journal of King Saud University: Computer and Information Sciences (May 2022)
An adaptive cuckoo search based algorithm for placement of relay nodes in wireless body area networks
Abstract
The evolution of wireless body area networks (WBAN) has changed the human life for its applications in the field of healthcare, fitness, entertainment and sports etc. However, two of the major challenges in the design of WBAN are energy efficiency and connectivity. The placement of relay nodes in a wireless body area network (WBAN) plays an important role in design of energy efficient and reliable WBAN. This problem is a joint problem of data routing and placement of relay nodes and formulated as a linear integer programming model. The main objective of the problem is to minimize the cost of relay nodes, energy consumption and distributing the loads uniformly on the relay nodes. Considering the hardness of the problem, we propose an adaptive cuckoo search based algorithm which uses an efficient fitness function and an adaptive step size proportional to the fitness function for placement of relay nodes. The set of relay nodes obtained by our proposed adaptive cuckoo search algorithm compared with cuckoo search as well as other state of the art algorithms via simulation results. The simulation results reveal that the proposed algorithm not only consumes less energy than its counterparts but also distributes the load evenly on the relay nodes. We consider two different postures of the body with 13 biosensors placed in fixed positions and 50–100 candidate sites for placement of relay nodes. Furthermore, we also consider 80 biosensors randomly deployed in a rectangular area with 50–300 candidate sites to study the scalability of our algorithm.