A Computation Offloading Scheme for UAV-Edge Cloud Computing Environments Considering Energy Consumption Fairness

A heterogeneous computing environment has been widely used with UAVs, edge servers, and cloud servers operating in tandem. Various applications can be allocated linked to the nodes that constitute this environment. Efficiently offloading allocating computational tasks is essential, especially these environments differentials processing power, network bandwidth, latency. In particular, such as drones, operate using minimal battery power. Therefore, energy consumption must considered when tasks. This study proposed an fairness-aware scheme based on a genetic algorithm (GA). The method minimized differences by evenly among drones. Based performance evaluations, our improved efficiency of fairness, compared previous approaches, Liu et al.’s scheme. We showed fairness was up 120%.