Energy Efficient and Deadline Satisfied Task Scheduling in Mobile Cloud Computing

Due to some inherent defects of mobile devices, such as limited battery energy, insufficient storage space, mobile applications are confronted with many challenges in mobility management, quality of service (QoS) insurance, energy management and security issues, which has stimulated the emergence of many computing paradigms, such as Mobile Cloud Computing (MCC), Fog Computing, etc. These computation paradigms allow to offload some tasks to the cloud for execution, which makes task scheduling crucial both at the mobile device and in the mobile cloud. In this paper, we models this problem as an energy consumption optimization problem, while taking into account task dependency, data transmission and some constraint conditions such as response time deadline and cost, and further solve it by genetic algorithms. A series of simulation experiments are conducted to evaluate the performance of the algorithm and the results have shown that our proposal is more efficient than the baseline approach.