Despite the remarkable work conducted to improve fog computing applications’ efficiency, task scheduling problem in such an environment is still a big challenge. Optimizing these applications, i.e. critical healthcare smart cities, and transportation urgent save energy, quality of service, reduce carbon emission rate, flow time. As proposed much recent work, dealing with this as single objectiv...

Optimizing the scheduling algorithm is a key problem to improving service efficiency of urban heterogeneous computing platforms. In this paper, we propose novel list-based called Modified Predict Earliest Finish Time (MPEFT) for systems with aim minimize total execution time. The consists two stages: task prioritization and processor selection. phase, priority tasks calculated by time cost all ...