Collaborative Mobile Edge and Cloud Computing: Tasks Unloading for Improving Users’ Quality of Experience in Resource-Intensive Mobile Applications
Michael P. J. Mahenge, Chunlin Li, Camilius Aloyce Sanga · 2019 IEEE 4th International Conference on Computer and Communication Systems (ICCCS) · 2019
The advancement in resource-intensive and latency-sensitive applications challenge the legacy systems in Mobile Cloud Computing (MCC) in terms of network congestion, bandwidth utilization, performance and Quality of Service (QoS) metrics. Such challenges emanate from first, limited energy sources and resource poverty of mobile devices. Second, multi-hop connection between user devices and the cloud. To address such challenges, mobile edge computing is a promising solution. This study proposes an architecture that considers unloading resource-intensive tasks from clients' devices to more resourceful edge servers which exploit cooperative approach for tasks processing. Thus, it is essential for minimizing delay, bandwidth usage, congestion to the core network and guarantees cost-effective approach for meeting user's demands. The simulation results show that the proposed approach through unloading, it reduces response time and energy usage. This in turn improves performance, system utility and Quality of Experience (QoE).