Energy Saving Strategy on Mobile Devices under Mobile Cloud Systems

Currently, applications on mobile devices have led to severe energy consumption problems, but the mobile cloud computing is an effective solution. In this paper, we propose a novel mobile cloud computing (MCC) system, in which mobile users have multiple independent task migration options. Our goal is to work together to optimize the unloading decisions of all tasks, balance energy consumption and time, and also minimize the total cost of energy, computing and delays for users. An improved genetic algorithm is proposed to map a few legitimate descendant genes into one-digit values and reduce the time spent on screening the legitimacy of descendants. Compared with the global optimal solution, our experiment results are more suitable for simultaneous computation migration.