A QoS-Aware Service-Driven Network Selection for HWNs Based on MARCOS and Utility Functions

Heterogeneous wireless networks (HWNs) are essential in modern communication systems, as they seamlessly integrate various radio access technologies (RATs). In this context, network selection (NS) emerges as a pivotal element, responsible for selecting the most appropriate network for user equipment (UE) during transitions between RATs. Conventional NS mechanisms, such as the multi-attribute decision-making (MADM) methods, are commonly employed for their fast ranking of RATs, real-time support, and flexibility. However, they suffer from three primary limitations; the rank reversal problem (RRP), overlooking specific user/service requirements while favouring the highest-ranking RAT, and the associated frequent handovers. To address these limitations, in this paper, we first employ one of the most recent and effective MADM approaches, known as the measurement of alternatives and ranking according to the compromise solution (MARCOS), to model and solve the NS problem (MARCOS-NS) for the first time in the literature. We then propose novel sigmoid utility functions to assess the quality of each RAT attribute within the HWNs environment, taking into account user/application requirements. Further, we enhance MARCOS-NS by replacing its original normalization technique with the proposed sigmoid utility functions to overcome its limitation, creating a new MADM approach called MARCOS-Utility. Our results demonstrate the superiority of MARCOS-Utility over conventional MADM approaches as it completely eliminates the RRP, reduces vertical handover occurrences by an average of 33.1%, and achieves a balance between data rate and packet loss ratio for the streaming traffic class.