云计算模式下多租户软件最优调度方法仿真
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摘要
针对当前调度方法对多租户软件调度时,难以保证调度任务服务水平目标、租户间公平性,同时存在任务调度执行效率低的问题,提出基于蚁群优化的云计算模式下多租户软件最优调度方法。多租户软件最优调度机制引人占优资源熵以及占优资源权重的概念使任务调度到多租户需求和供给更为贴合的虚拟机上。在此前提下保障获取资源最少的租户优先获得任务调度,并根据租户的资源使用情况,以最大化全局占优资源熵为目标构建最优调度模型。采用蚁群算法对最优调度模型进行求解,对调度方案可行解添加不同信息素,使得多租户调度服务水平目标、调度执行效率、租户间公平性等综合需求达到最优,即最优解。实验结果表明,所提方法能够保证调度任务服务水平目标、租户间公平性,且有效提高了任务调度执行效率。
This paper presents an optimal scheduling method for multi-tenancy software in cloud computing mode based on ant colony optimization. Firstly, the conception about dominant resource entropy and dominant resource weight was introduced into multi-tenancy software optimal scheduling mechanism so that tasks could be dispatched or the virtual machine that multi-tenancy demand was more appropriate for supply. Based on this premise, the tenan with the least resource was guaranteed to obtain task scheduling preferentially. According to tenant's resource usage,the maximized global dominant resource entropy was used to build the optimal scheduling model. Moreover, the an colony algorithm was used to solve the optimal scheduling model and added different pheromone on the feasible solu tion of scheduling scheme. Thus, multi-tenancy scheduling service level, scheduling execution efficiency, fairness among tenants and other integrated demands could be optimized, namely the optimal solution. Simulation results show that the proposed method can guarantee the service level of scheduling task and fairness. Meanwhile, it effectively improves the efficiency of task scheduling.
This paper presents an optimal scheduling method for multi-tenancy software in cloud computing mode based on ant colony optimization. Firstly, the conception about dominant resource entropy and dominant resource weight was introduced into multi-tenancy software optimal scheduling mechanism so that tasks could be dispatched or the virtual machine that multi-tenancy demand was more appropriate for supply. Based on this premise, the tenan with the least resource was guaranteed to obtain task scheduling preferentially. According to tenant's resource usage,the maximized global dominant resource entropy was used to build the optimal scheduling model. Moreover, the an colony algorithm was used to solve the optimal scheduling model and added different pheromone on the feasible solu tion of scheduling scheme. Thus, multi-tenancy scheduling service level, scheduling execution efficiency, fairness among tenants and other integrated demands could be optimized, namely the optimal solution. Simulation results show that the proposed method can guarantee the service level of scheduling task and fairness. Meanwhile, it effectively improves the efficiency of task scheduling.
引文
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[2]苑中梁,陈兴蜀,王毅桐.IaaS环境下多租户安全资源分配算法和安全服务调度框架[J].计算机应用,2017,37(2):383-387.
[3]李响,等.一种面向SaaS多租户的多层模型[J].计算机科学,2017,44(11):56-63.
[4]顾炜江.物联网中共享资源数据调度方法的研究[J].计算机仿真,2017,34(1):268-271.
[5]齐平,王福成,王必晴.一种基于图模型的可信云资源调度算法[J].山东大学学报:理学版,2018,53(1):63-74.
[6]陈爱国,等.基于资源分组的多约束云工作流调度算法[J].电子科技大学学报,2017,46(3):562-568.
[7]熊余,等.TWDM-PON中带有业务区分的混合资源调度算法[J].电子学报,2017,45(6):1490-1497.
[8]薛涛,马腾.基于资源权重最大资源利用率的动态资源调度算法[J].计算机应用研究,2016,33(5):1374-1378.
[9]张利永,段荣,罗恒钰.一种面向SaaS环境的工作流系统集成和负载均衡方法[J].中国电子科学研究院学报,2016,11(4):417-424.
[10]张中一,等.一种QoS收益感知的服务请求动态调度算法[J].小型微型计算机系统,2017,38(12):2791-2796.