In today’s world, Cloud Computing (CC) enables the users to accesscomputing resources and services over cloud without any need to own the infrastructure. Cloud Computing is a concept in which a network of devices, l...In today’s world, Cloud Computing (CC) enables the users to accesscomputing resources and services over cloud without any need to own the infrastructure. Cloud Computing is a concept in which a network of devices, located inremote locations, is integrated to perform operations like data collection, processing, data profiling and data storage. In this context, resource allocation and taskscheduling are important processes which must be managed based on the requirements of a user. In order to allocate the resources effectively, hybrid cloud isemployed since it is a capable solution to process large-scale consumer applications in a pay-by-use manner. Hence, the model is to be designed as a profit-driven framework to reduce cost and make span. With this motivation, the currentresearch work develops a Cost-Effective Optimal Task Scheduling Model(CEOTS). A novel algorithm called Target-based Cost Derivation (TCD) modelis used in the proposed work for hybrid clouds. Moreover, the algorithm workson the basis of multi-intentional task completion process with optimal resourceallocation. The model was successfully simulated to validate its effectivenessbased on factors such as processing time, make span and efficient utilization ofvirtual machines. The results infer that the proposed model outperformed theexisting works and can be relied in future for real-time applications.展开更多
针对实时系统负载动态变化的问题,提出一种面向软实时的基于资源预留的反馈调度模型(Feedback Scheduling M odel based on Resource Reservation,FSM-RR),当负载发生变化时调整服务器的CPU带宽.接着针对混合任务提出一种自适应分层调...针对实时系统负载动态变化的问题,提出一种面向软实时的基于资源预留的反馈调度模型(Feedback Scheduling M odel based on Resource Reservation,FSM-RR),当负载发生变化时调整服务器的CPU带宽.接着针对混合任务提出一种自适应分层调度框架(Adaptive Hierarchical Scheduling Framework,AHSF),对不同类型任务采用相应的调度算法,保证硬实时任务在其截止期之前完成,同时尽可能的降低软实时以及非实时任务的截止期错失率.在RTSim平台上进行仿真实验,并与传统调度算法进行对比分析,实验结果表明本文提出调度算法具有较好的性能.展开更多
文摘In today’s world, Cloud Computing (CC) enables the users to accesscomputing resources and services over cloud without any need to own the infrastructure. Cloud Computing is a concept in which a network of devices, located inremote locations, is integrated to perform operations like data collection, processing, data profiling and data storage. In this context, resource allocation and taskscheduling are important processes which must be managed based on the requirements of a user. In order to allocate the resources effectively, hybrid cloud isemployed since it is a capable solution to process large-scale consumer applications in a pay-by-use manner. Hence, the model is to be designed as a profit-driven framework to reduce cost and make span. With this motivation, the currentresearch work develops a Cost-Effective Optimal Task Scheduling Model(CEOTS). A novel algorithm called Target-based Cost Derivation (TCD) modelis used in the proposed work for hybrid clouds. Moreover, the algorithm workson the basis of multi-intentional task completion process with optimal resourceallocation. The model was successfully simulated to validate its effectivenessbased on factors such as processing time, make span and efficient utilization ofvirtual machines. The results infer that the proposed model outperformed theexisting works and can be relied in future for real-time applications.
基金the National Natural Science Foundation of China under Grant No.90412001 (国家自然科学基金)the National High-Tech Research and Development Plan of China under Grant No.2006AA02Z334 (国家高技术研究发展计划(863))the National Basic Research Program of China under Grant No.G2005CB321806 (国家重点基础研究发展计划(973))
文摘针对实时系统负载动态变化的问题,提出一种面向软实时的基于资源预留的反馈调度模型(Feedback Scheduling M odel based on Resource Reservation,FSM-RR),当负载发生变化时调整服务器的CPU带宽.接着针对混合任务提出一种自适应分层调度框架(Adaptive Hierarchical Scheduling Framework,AHSF),对不同类型任务采用相应的调度算法,保证硬实时任务在其截止期之前完成,同时尽可能的降低软实时以及非实时任务的截止期错失率.在RTSim平台上进行仿真实验,并与传统调度算法进行对比分析,实验结果表明本文提出调度算法具有较好的性能.
