Multi-user energy efficient secured framework with dynamic resource allocation policy for mobile edge network computing

With an exploding use of Mobiles, smartphones and IoT device, mobile edge computing (MEC) emerged as technological boon in computing paradigm. The device offloads the computationally intensive task as well as task relevant to storage to the MEC cloud server to meet the requirement of service delay, extend the battery lifespan of mobile, and resolve the problem of limited mobile device resources. With this reference we propose novel framework architecture with security to perform offloading of high storage and computationally intensive task to MEC server with minimum energy consumption and delay. For dynamic resource allocation, we employ two scheduling policy one at mobile side i.e. SJFP and other at MEC server side i.e. eSFFDRR. Before to offload task, first AES encryption technique is employed to secure input parameter, and then compressed this encrypted data to secure task data and utilize more bandwidth. Our experimental result depicts that for high storage and computationally intensive task our proposed framework can save 85–87% processing time, 70% of memory utilization with minimum energy consumption. The experimental result also proved that our proposed work improves the performance of computationally intensive mobile application with reduced consumption of mobile device resources like computation time, memory utilization, CPU usage and energy consumption.