Context-aware computation offloading for mobile edge computing

Along with the rise of mobile devices, the resource demands of respective applications grow. However, mobile devices have limited computation and storage resources. Computation offloading is a prominent solution to overcome the limitations. However, current approaches fail to address the complexity caused by quickly and constantly changing context conditions in mobile edge computing. In this paper, the contexts are gathered and processed using Monitor-Analysis-Plan-Execution (MAPE) loop for making offloading decisions. The results show that the proposed context-aware approach outperforms local computing and offloading without considering context approaches in terms of delay, energy consumption, network usage, and execution cost.