基于ILS-PSO算法的移动云计算DAG图的任务调度研究与应用  

Research and Application on DAG Task Scheduling in Mobile Cloud Computing Based on ILS-PSO

作　　者：董韵 张毅 孙晋[1] DONG Yun;ZHANG Yi;SUN Jin(School of Computer Science and Engineering,Nanjing University of Science and Technology,Nanjing 210094)

机构地区：[1]南京理工大学计算机科学与工程学院,南京210094

出　　处：《计算机与数字工程》2020年第3期575-580,595,共7页Computer & Digital Engineering

基　　金：国家自然科学基金项目(编号:71501096,61502234);江苏省自然科学基金项目(编号:BK20150785)资助。

摘　　要：移动云计算已经深入到人们工作和生活的各个方面,同时也对移动设备的续航时间、计算能力,存储容量和安全性提出了更高的要求。移动云计算网络中的移动设备由于资源有限、通信受限,无法满足复杂应用的要求。为了解决移动云计算环境下复杂应用的有效使用问题,对移动设备网络和DAG任务图进行深入研究,将复杂应用分解成多个不相交的集合分配给移动设备并行执行,满足移动设备电池容量的约束下,提出了粒子群优化(PSO)算法求解最优调度方案的方法,并且应用迭代局部搜索(ILS)策略,保证了全局和局部搜索的平衡。Mobile cloud computing has penetrated into all aspects of people’s work and life,and it also puts forward higher requirements for battery capacity,computing performance,storage and security. Mobile devices in mobile cloud computing networks cannot meet the requirements of complex applications due to limited resources and communication. In order to solve the problem of effective use of complex applications in mobile cloud computing and conducts in-depth research on mobile device networks and DAG task graph,complex application is divided into multiple sections and distributed to mobile devices. Under the constraint of mobile device battery capacity,Particle Swarm Optimizer(PSO)algorithm is proposed to solve the optimal scheduling scheme,and Iterated Local Search(ILS)strategy is applied to ensure the balance between global and local search.

关 键 词：移动云计算 移动设备 DAG任务图 粒子群优化 迭代局部搜索 搜索平衡 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]