Online user allocation in mobile edge computing environments:A decentralized reactive approach

As a newly emerging computing paradigm, mobile edge computing (MEC) can energize novel mobile applications, especially the ultra-latency-sensitive ones, by providing powerful local computing capabilities and lower end-to-end delays. However, considering the complex cyber–physical environment and varied time-space user behaviors, as mobile application vendors, how to decide which edge server to serve which edge user in real-time becomes the key challenge. Instead of assuming the simultaneous-batch-arrival pattern of incoming edge users and handling the edge user allocation (EUA) problem as a static optimization, in this paper, we consider the online EUA problem where edge users’ resource demands arrive and depart dynamically. We consider the long-term edge user allocation rate, edge server hiring cost, and edge server energy consumption as allocation targets from the mobile application vendor perspective, and propose a decentralized reactive approach by employing a fuzzy control mechanism to yield the real-time allocation decisions. Experiments based on real-world MEC environment datasets demonstrate our approach outperforms state-of-the-art and baseline ones in terms of user allocation rate, server hiring cost, and energy consumption.