A multi-objective parameter optimization approach to maximize lifetime of wireless sensor networks inspired by spider web

Spider-web-inspired hierarchical clustering network is an emerging research topic in wireless sensor networks (WSNs), benefitting from the particular characteristics in invulnerability. It is of great practical significance to achieve a proper parameter combination for optimizing network clustering and cluster head (CH) selection. However, there is no feasible solution to determine these parameters to lessen the energy consumption of resource-limited spider-web-inspired WSNs. Meanwhile, the existing protocols cannot adequately balance the total network energy dissipation and the network performance due to insufficient consideration of invulnerability. In this paper, a novel multi-objective optimization approach of parameter combination (MOOAPC) is proposed to solve the predicament, including the number of layers L , number of interval rounds for CH re-election m , grade communication radius within a cluster G cr , number of sectors Z , and total number of nodes N . Specifically, the statistical methods, consisting of normality test, homogeneity of variance test, and ANOVA, are used to clarify the effect of different parameters on the network performance. Moreover, the logistic regression algorithm is applied to establish the optimization objective functions of invulnerability and average residual energy with the impact degree as the basis for setting the parameter constraints, and then, NSGA-II algorithm is adopted to acquire the optimal parameter combination. We discovered that the parameter combination ( L = 6, m = 20, G cr = 4, Z = 4, and N = 1100) was appropriate to prolong the network lifetime. In the case of reaching the threshold of death rate of nodes, the number of death rounds of MOOAPC was 670, which was 10.56%, 4.36% and 6.35% higher than that of LEACH, HEED and EEUC, respectively. Compared with LEACH, HEED, and EEUC, MOOAPC demonstrated significant performance advantages in invulnerability and average residual energy, 42.06% and 17.99% higher on average. Based on these results, the proposed method can be utilized to increase the capability of spider-web-inspired WSNs against deterioration of quality of service and energy constraints.