Joint task offloading and resource allocation in mobile edge computing with energy harvesting

Abstract Mobile edge computing (MEC) is considered to be a promising technique enhance the computation capability and reduce energy consumption of smart mobile devices (SMDs) in sixth-generation (6G) networks. With huge increase SMDs, many applications SMDs can interrupted due limited supply. Combining MEC harvesting (EH) help solve this issue, where computation-intensive tasks offloaded servers also charged during offloading. In work, we aim minimize total subject service latency requirement by jointly optimizing task offloading ratio resource allocation (including time switching (TS) factor, uplink transmission power downlink eNodeB, resources server). Compared with previous studies, time, results downloading are all problem. Since problem non-convex, first reformulate it, then decompose it into two subproblems, i.e., joint optimization subproblem (JUDTT-OP) TS factor (JTORTSF-OP). By solving EH (JTORAEH) algorithm proposed Simulation show that compared other benchmark methods, JTORAEH achieve better performance terms consumption.