Priority-MECE: A Mobile Edge Cloud Ecosystem Based on Priority Tasks Offloading

With the rapid development of Internet of things, the traditional city model is no longer applicable. Therefore, the emerging concept of smart city meets the needs of users. Smart medical system needs to meet the service needs of different priority users in emergency. In order to improve the service quality of users, we apply mobile edge computing technology to the smart medical system. In this article, we consider the priority of the offloading tasks and establish a priority-mobile edge cloud ecosystem (priority-MECE). The system taked into account user priorities, the combined cost value genereted by the delay and energy consumption was reduced. In the priority-MECE computing offloading system, an optimization problem is established with the task offloading cost as the optimization goal. The result of this optimization problem can provide an optimal offloading scheme for priority-MECE. In order to solve this optimization problem, we propose a priority constraint optimal offloading algorithm(priority-COFA) based on dynamic programming. In order to prove that the performance of this algorithm is better than random selection, we design a simulation experiment based on previous studies. Finally, the simulation results show that the proposed algorithm is superior to random offloading and no priority offloading.

Automated summary

This article introduces the importance of the development needs of smart cities and the use of mobile edge computing technology in improving the service quality of smart medical systems. The study proposes a priority-mobile edge cloud ecosystem, establishes an optimization problem with the task offloading cost as the optimization goal, and introduces a priority constraint optimal offloading algorithm. Simulation results demonstrate the superior performance of the algorithm.