Interval type-2 fuzzy logic based transmission power allocation strategy for lifetime maximization of WSNs

Abstract

In wireless sensor networks (WSNs), it is critical to design an advisable transmission power allocation strategy for balancing the latency and energy efficiency, and prolonging the lifetime of WSNs. However, some measured key parameters, e.g., data latency, energy consumption and communication radius, are with high levels of uncertainties, which deteriorate the transmission power allocation performance greatly. How to employ an advanced method to deal with the uncertainties and to further improve the network performance is a pressing issue. Type-2 fuzzy logic system (T2FLS) as a powerful tool for handling the uncertainties provides an effective way for designing such advisable allocation strategies. Therefore, this paper adopts the interval T2FLS (IT2FLS) to design the transmission power allocation (TPA) strategy for lifetime maximization of WSNs. Firstly, the problem of lifetime enhancement in WSNs is formulated in detail, and then it is converted into a TPA problem. Secondly, the IT2FLS method is applied to the transmission power decision making process for maximizing the lifetime of WSNs. In the designed IT2FLS-based TPA strategy, expected latency, residual energy and distance between nodes are taken as input variables, while the transmission power and communication radius are considered as the output variables. Finally, both simulation and experiment results are given. The results indicate that the proposed TPA strategy using IT2FLS can effectively realize the tradeoff between the latency and energy efficiency, and can prolong the network lifetime of the WSNs. Moreover, compared with other TPA strategies, including the minimum total energy algorithm, the flow augmentation algorithm and the type-1 fuzzy logic method, the proposed IT2FLS-based TPA strategy has obvious advantages in terms of network lifetime, average latency and energy consumption.