Abstract
Mobile edge computing can deliver high-throughput and low-latency computing services by means of offloading computation tasks of mobile devices to edge servers. This paper aims at scheduling security-critical workflow tasks, which require data encryption and decryption during the offloading procedure and have precedence relations among each other, in a mobile edge computing environment. The scheduling problem is formulated as an optimization problem that minimizes workflow execution time and total energy consumption under precedence constraints upon security-critical tasks. The optimization model takes into account the time and energy overhead for data encryption and decryption. We propose a new particle swarm optimization algorithm to solve the resulting optimization problem. This algorithm uses a position-based mapping operator to convert each particle into a high-quality feasible solution, which is represented by a task sequence. For each converted solution, we develop a greedy search strategy to offload workflow tasks onto edge servers such that the completion time and energy consumption can be evaluated. In addition, we incorporate Levy flight into the standard movement scheme for updating particle positions, to improve the computational efficiency of the particle updating procedure. Experimental results show that the proposed algorithm outperforms baseline approaches in terms of both effectiveness and efficiency when solving the considered scheduling problem.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.