An Effective Offloading Model Based on Genetic Markov Process for Cloud Mobile Applications
Mobile Cloud Computing (MCC) has drawn significant research attention as mobile devices’ capability has been improved in recent years. MCC forms the platforms for a broad range of mobile cloud solutions. MCC’s key idea is to use powerful back-end computin
- PDF / 1,384,276 Bytes
- 13 Pages / 439.37 x 666.142 pts Page_size
- 78 Downloads / 229 Views
Abstract. Mobile Cloud Computing (MCC) has drawn significant research attention as mobile devices’ capability has been improved in recent years. MCC forms the platforms for a broad range of mobile cloud solutions. MCC’s key idea is to use powerful back-end computing nodes to enhance the capabilities of small mobile devices and provide better user experiences. In this paper, we propose a novel idea for solving multisite computation offloading in dynamic mobile cloud environments that considers the environmental changes during applications’ life cycles and relationships among components of an application. Our proposal, called Genetic Markov Mobile Cloud Computing (GM-MCC), adopts a Markov Decision Process (MDP) framework to determine the best offloading decision that assigns components of the application to the target site by consuming the minimum amount of mobile’s energy through determining the cost metrics to identify overhead on each the component. Furthermore, the suggested model utilizes a genetic algorithm to tune the MDP parameters to achieve the highest benefit. Simulation results demonstrate that the proposed model considers the different capabilities of sites to allocate appropriate components. There is a lower energy cost for data transfer from the mobile to the cloud. Keywords: Mobile Cloud Computing Offloading Application partitioning algorithm Genetic algorithm Markov Decision Process
1 Introduction Mobile Cloud Computing (MCC) is an emerging technology linked to a broad range of mobile learning applications, healthcare, context-aware navigation, and social cloud. MCC is an infrastructure where the data storage and data processing are performed outside the mobile device but inside the cloud [1]. A mobile device itself has limitations such as limited network bandwidth, energy consumed by transmission and computation, network availability, and little storage [2]. However, the limited battery life is still a big obstacle for the further growth of mobile devices. Several known power-conservation techniques include turning off the mobile computing devices screen when not used, optimizing I/O, and slowing down the CPU [3]. One accessible © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 A. E. Hassanien et al. (Eds.): AISI 2020, AISC 1261, pp. 38–50, 2021. https://doi.org/10.1007/978-3-030-58669-0_4
An Effective Offloading Model Based on Genetic Markov Process
39
technology to reduce the energy consumption for mobile devices is MCC. Its fundamental idea is computation offloading or cyber forging, which means that parts of an application executing on the remote server, with results communicated back to the local device [4]. The offloading mechanism divides the application between local and remote execution. The decision may have to change with fluctuations in operating conditions such as computation cost, communication cost, excepted total cost of executing, user input, response time, and security agent [5]. Some critical issues concern
Data Loading...
