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.

随着手机，智能手机和物联网设备的爆炸式增长，移动边缘计算（MEC）成为计算范式中的技术福音。设备将计算密集型任务以及与存储相关的任务分担给MEC云服务器，以满足服务延迟的需求，延长了移动设备的电池寿命，解决了移动设备资源有限的问题。以此参考为基础，我们提出了一种具有安全性的新颖框架架构，可以以最少的能耗和延迟将高存储量和计算密集型任务卸载到MEC服务器。对于动态资源分配，我们采用两种调度策略，一种在移动端即SJFP，另一种在MEC服务器端即eSFFDRR。在卸载任务之前，首先采用AES加密技术来保护输入参数，然后压缩此加密数据以保护任务数据并利用更多带宽。我们的实验结果表明，对于高存储量和计算密集型任务，我们提出的框架可以以最少的能耗节省85-87％的处理时间，70％的内存利用率。实验结果还证明，我们的工作提高了计算密集型移动应用程序的性能，同时减少了移动设备资源的消耗，例如计算时间，内存利用率，CPU使用率和能耗。