A Single Task Migration Strategy Based on Ant Colony Algorithm in Mobile-Edge Computing

Abstract

Mobile user devices, such as smartphones or laptops, run increasingly complex applications that require more computing power and more computing resources. However, the battery capacity and energy consumption of mobile devices limit these developments. Mobile-Edge Computing (MEC) is a technology that utilizes wireless network to provide IT and cloud computing services for nearby users. IT can build a network environment with low latency and high bandwidth and accelerate the response speed of network services. Transferring computing tasks of mobile devices to MEC server through task migration technology can effectively relieve computing pressure of devices. Efficient task migration method can minimize the energy consumption of mobile devices on the basis of ensuring the data delay requirement. According to the characteristics of coarse-grained task migration in current mobile edge computing, this paper proposes a finegrained task migration scheme based on Ant Colony Algorithm(ACO), aiming to minimize the energy consumption of mobile devices on the basis of strict delay constraints in mobile applications. Finally, experimental results show that the method used in this paper can effectively reduce the energy consumption of mobile devices by 26%, compared to the static strategy.