Enterprises build private clouds to provide IT re- sources for geographically distributed subsidiaries or prod- uct divisions. Public cloud providers like Amazon lease their platforms to enterprise users, thus, enterp...Enterprises build private clouds to provide IT re- sources for geographically distributed subsidiaries or prod- uct divisions. Public cloud providers like Amazon lease their platforms to enterprise users, thus, enterprises can also rent a number of virtual machines (VMs) from their data centers in the service provider networks. Unfortunately, the network cannot always guarantee stable connectivity for their clients to access the VMs or low-latency transfer among data centers. Usually, both latency and bandwidth are in unstable network environment. Being affected by background traffics, the net- work status can be volatile. To reduce the latency uncertainty of client accesses, enterprises should consider the network status when they deploy data centers or rent virtual data cen- ters from cloud providers. In this paper, we first develop a data center deployment and assignment scheme for an enter- prise to meet its users' requirements under uncertain network status. To accommodate to the changes of the network status and users' demands, a VMs migration-based redeployment scheme is adopted. These two schemes work in a joint way, and lay out a framework to help enterprises make better use of private or public clouds.展开更多
Cloud simulation derived data is defined as the data related to service version,characteristics,relationships,runtime environments and cross-domain communication during service execution in cloud simulation environmen...Cloud simulation derived data is defined as the data related to service version,characteristics,relationships,runtime environments and cross-domain communication during service execution in cloud simulation environment,collectively.It is of great value and significance in cloud simulation for service description,service composition and resource management.The types of derived data are abundant and the amount of it is huge.Existing studies on cloud simulation usually assume all of the derived data required for a specific task is well organized and available anytime,which is of course impossible.Derived data needs to be expressed and managed in terms of knowledge to make sure the smooth execution of cloud simulation platform.Therefore,this paper presents a derived data management method in cloud simulation platform to enable derived data collection and dynamic knowledge storage.The prototype system of the proposed method are established and a virtual prototype of double girder crane is taken as an example to verify the effectiveness of the method.展开更多
基金This work was supported in part by the National Basic Research Program of China (2010CB328105, 2009CB320504), the National Natural Science Foundation of China (NSFC) (Grant No. 60932003). We would like to thank the anonymous reviewers for their suggestions that help us improve this paper.
文摘Enterprises build private clouds to provide IT re- sources for geographically distributed subsidiaries or prod- uct divisions. Public cloud providers like Amazon lease their platforms to enterprise users, thus, enterprises can also rent a number of virtual machines (VMs) from their data centers in the service provider networks. Unfortunately, the network cannot always guarantee stable connectivity for their clients to access the VMs or low-latency transfer among data centers. Usually, both latency and bandwidth are in unstable network environment. Being affected by background traffics, the net- work status can be volatile. To reduce the latency uncertainty of client accesses, enterprises should consider the network status when they deploy data centers or rent virtual data cen- ters from cloud providers. In this paper, we first develop a data center deployment and assignment scheme for an enter- prise to meet its users' requirements under uncertain network status. To accommodate to the changes of the network status and users' demands, a VMs migration-based redeployment scheme is adopted. These two schemes work in a joint way, and lay out a framework to help enterprises make better use of private or public clouds.
基金the National High-Tech Research and Development Plan of China under Grant No.2015AA042101National Natural Science Foundation of China under Grant No.61374199State Key Laboratory of Intelligent Manufacturing System Technology.
文摘Cloud simulation derived data is defined as the data related to service version,characteristics,relationships,runtime environments and cross-domain communication during service execution in cloud simulation environment,collectively.It is of great value and significance in cloud simulation for service description,service composition and resource management.The types of derived data are abundant and the amount of it is huge.Existing studies on cloud simulation usually assume all of the derived data required for a specific task is well organized and available anytime,which is of course impossible.Derived data needs to be expressed and managed in terms of knowledge to make sure the smooth execution of cloud simulation platform.Therefore,this paper presents a derived data management method in cloud simulation platform to enable derived data collection and dynamic knowledge storage.The prototype system of the proposed method are established and a virtual prototype of double girder crane is taken as an example to verify the effectiveness of the method.