移动云计算中面向能耗优化的资源管理  

Energy Optimization Oriented Resource Management in Mobile Cloud Computing

作　　者：金小敏 滑文强 JIN Xiao-min;HUA Wen-qiang(School of Computer Science and Technology,Xi’an University of Posts and Telecommunications,Xi’an 710121,China;Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing,Xi’an University of Posts and Telecommunications,Xi’an 710121,China)

机构地区：[1]西安邮电大学计算机学院,西安710121 [2]西安邮电大学陕西省网络数据分析与智能处理重点实验室,西安710121

出　　处：《计算机科学》2020年第6期247-251,共5页Computer Science

基　　金：陕西省教育厅专项科研计划项目(19JK0806);陕西省重点研发计划项目(2019ZDLGY07-08);西安邮电大学青年教师科研基金;陕西省普通高等学校重点学科专项资金建设项目。

摘　　要：移动云计算(Mobile Cloud Computing,MCC)作为传统云计算的扩展,可利用计算迁移突破移动终端资源瓶颈并增强其能力。然而,在带来优势的同时,MCC也面临诸多问题。资源管理问题关系到MCC能否良性运转,是决定MCC能否规模化发展的关键。针对MCC中的资源管理问题,文中首先建立了一种以优化云资源运营商能耗为目标的资源管理模型,该模型是一个受约束的组合优化问题;然后,提出一种基于启发式自适应模拟退火遗传算法(Heuristic Adaptive Simulated Annealing Genetic Algorithm,HASAGA)的资源管理策略求解算法,该算法利用首次适应算法(First Fit,FF)初始化种群并结合自适应算法和模拟退火算法优化遗传操作。仿真结果表明,所提算法可求得近似最优资源管理策略且具有收敛速度快和不易陷入局部最优解的优点。仿真实验还比较了传统轮询算法(Round Robin,RR)和首次适应算法的资源管理效果,结果表明这两种算法不适用于MCC中的资源管理。As an extension of the traditional cloud computing,mobile cloud computing(MCC)breaks through the bottleneck of mobile device resources and enhances its capabilities by computation offloading.However,MCC faces many problems while bringing advantages.The problem of resource managementis related to the benign operation of MCC,and it is the key to determining whether MCC can be scaled up.To solve the problem of resource management in MCC,firstly,a resource management model aiming at optimizing energy consumption of the cloud resource operator is established,which is a constrained combinatorial optimization problem.Then a resource management strategy solution algorithm based on the heuristic adaptive simulated annealing genetic algorithm is proposed.This algorithm initializes the population by using the first fit algorithm and combines the adaptive algorithm and the simulated annealing algorithm to optimize its genetic operations.Simulation shows that the proposed algorithm can obtain the approximate optimal resource management strategy and has advantages of fast convergence rate and not easy to fall into local optimal solutions.The simulation experiments also compare the resource management effects of the traditional round robin algorithm and the first fit algorithm,and the results show that these two algorithms are not suitable for resource management in MCC.

关 键 词：移动云计算 资源管理 能耗优化 遗传算法 模拟退火 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]