Joint partial computation offloading and resource allocation in MEC-enable networks

The sudden surge of various applications poses great challenges to the computation capability of mobile devices. To address this issue, computation offloading to multi-access edge computing(MEC) was proposed as a promising paradigm. This paper studies partial computation offloading scenario by considering time delay and energy consumption, where the task can be splitted into several blocks and computed both in local devices and MEC, respectively. Since the formulated problem is a nonconvex probl...

Joint partial computation offloading and resource allocation inMEC-enable networks

The sudden surge of various applications poses great challenges to the computation capability of mobile devices.To address this issue, computation offloading to multi-access edge computing (MEC) was proposed as a promisingparadigm. This paper studies partial computation offloading scenario by considering time delay and energyconsumption, where the task can be splitted into several blocks and computed both in local devices and MEC,respectively. Since the formulated problem is a nonconvex problem, this paper proposes an ant colony-basedalgorithm to achieve the suboptimal solution. Specifically, the proposed method first establish a multi-user one-MEC scenario, in which user devices are able to offload some part of the task to MEC server. Then, it develops anant colony-based algorithm to decide the offloading parts and allocation strategy of MEC resources to minimizesystem cost. Finally, simulation results show the effectiveness of the proposed algorithm in terms of system cost anddemonstrate that it outperforms other existing methods.