Offloading Collaborative Cloud-Edge-End Tasks Utilizing Mobile Edge of The Network Systems With Reduced Communication Systems

Abstract

Mobile edge computing (MEC) is a new computing architecture that places processing platforms at the network’s edge to provide low-latency, high-bandwidth, and adaptable mobile services. To improve the cloud-edge-end computing efficacy of the tasks within the constrained computation and communication functionality, we investigate cooperative computation unloading, computation and connectivity resource allotment, and create a collaborative computing structure that enables the activities of mobile devices (MDs) to be partially activated at the terminals, edge nodes (EN), and cloud centre (CC). Then, we propose the pipeline-based offloading technique, which enables MDs and ENs to assign computationally difficult tasks to certain ENs and CCs depending on their computing and communication capabilities. Given the offloading mechanism, computation resource, delivery rate, and power allocation, minimising the total latency of all MDs presents a significant challenge. Using the time-honored sequential convex approximation (SCA) technique, we first transform the non-convex optimization problem into a convex one. Simulation results show that the proposed cooperation offloading approach using the pipeline methodology is efficient and provides superior performance to currently used offloading strategies.