Collaborative Cloud-Edge Computing with Mixed Wireless and Wired Backhaul Links: Joint Task Offloading and Resource Allocation

Mobile Edge Computing (MEC) is a promising technology that provides computing services at the edge of wireless networks to reduce the latency and the energy consumption for Smart Mobile Devices (SMDs). Additionally, the Ultra-Dense Network (UDN) will play a key role in providing high transmission capacity for SMDs in 5G networks. In order to improve the edge cloud efficiency within limited communication and computing resources, this paper proposes a joint task offloading and resource allocation scheme collaborated between cloud computing and edge computing in the UDN. Since wireless backhaul is more economical than expensive wired backhaul deployments, we consider the mixed deployment of either wired or wireless backhaul between each Small Base Station (SBS) and the Macro Base Station (MBS) in UDN scenarios, then formulate an optimization problem to minimize the system-wide computation overhead, and apply the Linear Decreasing Weight Particle Swarm Optimization (LDWPSO) algorithm to solve the problem. Numerical experiments validate the effectiveness of our proposed scheme compared to other baseline schemes.