Multi-Objective Whale Optimization for Network Interface Selection in HWNs

The network interface selection (NIS) is an important function that should be executed to connect the user's equipment to the best available network anytime and anywhere by meeting the user/application QoS requirements. Multi-attribute decision-making approaches (MADM) are commonly applied to model and solve NIS problems. Although they can rank networks quickly with a high precision, they suffer from two drawbacks. Firstl, the rank reversal problem (RRP). Second, The selection of the highest-ranking score network without considering user and/or service requirements. In this paper, we introduce a novel approach to solve the above-cited drawbacks. We model the weighting techniques as a multi-objective problem. Then, we apply an extended version of the Whale optimization algorithm to obtain the decision criteria weights according to the traffic classes and the chosen MADM approaches. The obtained simulations clearly show that applying our approach with MADM approaches reduces the RRP and satisfies the user/service requirements.