Bringing always best connectivity vision a step closer: challenges and perspectives

"Always best connectivity," which constitutes a key challenge in the context of 4G systems, solicits service access and provisioning through the most appropriate access network any time, any place. In this relatively well investigated area, the problem of dynamically selecting the most suitable network for a specific service, referred to as access network selection (ANS), has recently received considerable attention. However, the several ANS proposals in the literature, which have explored relevant ANS criteria, methodologies, and techniques, point out that some related technical issues are still open challenges to be resolved. The aim of this article is to identify and discuss critical aspects and research challenges involved in the design of ANS decision schemes. At the same time, current research efforts are revisited, and potential enabling technologies/solutions are highlighted, in particular the ones associated with cognition and advanced learning capabilities.