Multi-Objective Computation Sharing in Energy and Delay Constrained Mobile Edge Computing Environments

In a mobile edge computing (MEC) network, devices, also called clients, offload their computations to multiple servers that provide additional resources. Since the are placed at network edge, e.g., cell-phone towers, transmission delays between and clients shorter compared those of cloud computing. addition, can tasks other nearby with available resources by exploiting Fog Computing (FC) paradigm. A major challenge in MEC FC networks is assign from servers, as well such way completed minimum energy consumption processing delay. this paper, we model task offloading constrained multi-objective optimization problem (CMOP) minimizes both delay devices. To solve CMOP, design an evolutionary algorithm efficiently find representative sample best trade-offs delay, i.e., Pareto-optimal front. Compared existing approaches for MEC, see our approach finds decisions lower