With the simultaneous rise of energy costs and demand for cloud computing, efficient control of data centers becomes crucial. In the data center control problem, one needs to plan at every time step how many servers t...With the simultaneous rise of energy costs and demand for cloud computing, efficient control of data centers becomes crucial. In the data center control problem, one needs to plan at every time step how many servers to switch on or off in order to meet stochastic job arrivals while trying to minimize electricity consumption. This problem becomes particularly challenging when servers can be of various types and jobs from different classes can only be served by certain types of server, as it is often the case in real data centers. We model this problem as a robust Markov decision process(i.e., the transition function is not assumed to be known precisely). We give sufficient conditions(which seem to be reasonable and satisfied in practice) guaranteeing that an optimal threshold policy exists. This property can then be exploited in the design of an efficient solving method, which we provide.Finally, we present some experimental results demonstrating the practicability of our approach and compare with a previous related approach based on model predictive control.展开更多
In data centers, the transmission control protocol(TCP) incast causes catastrophic goodput degradation to applications with a many-to-one traffic pattern. In this paper, we intend to tame incast at the receiver-side a...In data centers, the transmission control protocol(TCP) incast causes catastrophic goodput degradation to applications with a many-to-one traffic pattern. In this paper, we intend to tame incast at the receiver-side application. Towards this goal, we first develop an analytical model that formulates the incast probability as a function of connection variables and network environment settings. We combine the model with the optimization theory and derive some insights into minimizing the incast probability through tuning connection variables related to applications. Then,enlightened by the analytical results, we propose an adaptive application-layer solution to the TCP incast.The solution equally allocates advertised windows to concurrent connections, and dynamically adapts the number of concurrent connections to the varying conditions. Simulation results show that our solution consistently eludes incast and achieves high goodput in various scenarios including the ones with multiple bottleneck links and background TCP traffic.展开更多
随着互联网数据中心IDC的快速发展,为其配备的不间断电源系统UPS规模越来越大,由于UPS的电池系统只有在少数的停电时段应用,造成了大量的资源闲置。在保证备电的前提下,充分挖掘UPS中电池系统的储能功能,是一种经济高效的储能形式。在常...随着互联网数据中心IDC的快速发展,为其配备的不间断电源系统UPS规模越来越大,由于UPS的电池系统只有在少数的停电时段应用,造成了大量的资源闲置。在保证备电的前提下,充分挖掘UPS中电池系统的储能功能,是一种经济高效的储能形式。在常规UPS的基础上,提出了储能型不间断电源系统(energy storage type of UPS,EUPS)的实现架构,EUPS多种“备电+储能”应用功能的控制策略,以及EUPS参与电网多场景调节的协调控制策略。最后,基于建成的EUPS示范系统,验证了所提的EUPS系统架构和控制策略的有效性。展开更多
探讨软件定义网络(Software Defined Network,SDN)在数据中心传输中的自适应流量管理。SDN架构的关键组成要素包括控制器、应用层和南向接口,通过控制平面和数据平面的分离,实现了网络的灵活性和可编程性。OpenFlow协议作为关键通信协议...探讨软件定义网络(Software Defined Network,SDN)在数据中心传输中的自适应流量管理。SDN架构的关键组成要素包括控制器、应用层和南向接口,通过控制平面和数据平面的分离,实现了网络的灵活性和可编程性。OpenFlow协议作为关键通信协议在SDN中得到广泛应用,为控制器提供了调整数据平面行为的标准化手段。在自适应流量管理方面,控制器通过实时监测和智能调整网络状态,识别瓶颈和拥塞点,并根据不同应用的性能需求进行精确的流量管理决策。基于流和基于应用的自适应管理算法使网络能够灵活适应不同流量负载,提高资源利用效率。流量监测工具如NetFlow和sFlow以及反馈机制在实现自适应流量管理中发挥关键作用,实时感知和调整网络状态,使SDN网络更加智能、适应性更强,并提供了优越的应用体验。未来的研究方向将关注SDN中自适应流量管理的创新策略,推动网络技术不断进步。展开更多
文摘With the simultaneous rise of energy costs and demand for cloud computing, efficient control of data centers becomes crucial. In the data center control problem, one needs to plan at every time step how many servers to switch on or off in order to meet stochastic job arrivals while trying to minimize electricity consumption. This problem becomes particularly challenging when servers can be of various types and jobs from different classes can only be served by certain types of server, as it is often the case in real data centers. We model this problem as a robust Markov decision process(i.e., the transition function is not assumed to be known precisely). We give sufficient conditions(which seem to be reasonable and satisfied in practice) guaranteeing that an optimal threshold policy exists. This property can then be exploited in the design of an efficient solving method, which we provide.Finally, we present some experimental results demonstrating the practicability of our approach and compare with a previous related approach based on model predictive control.
基金supported by the Fundamental Research Fundsfor the Central Universities under Grant No.ZYGX2015J009the Sichuan Province Scientific and Technological Support Project under Grants No.2014GZ0017 and No.2016GZ0093
文摘In data centers, the transmission control protocol(TCP) incast causes catastrophic goodput degradation to applications with a many-to-one traffic pattern. In this paper, we intend to tame incast at the receiver-side application. Towards this goal, we first develop an analytical model that formulates the incast probability as a function of connection variables and network environment settings. We combine the model with the optimization theory and derive some insights into minimizing the incast probability through tuning connection variables related to applications. Then,enlightened by the analytical results, we propose an adaptive application-layer solution to the TCP incast.The solution equally allocates advertised windows to concurrent connections, and dynamically adapts the number of concurrent connections to the varying conditions. Simulation results show that our solution consistently eludes incast and achieves high goodput in various scenarios including the ones with multiple bottleneck links and background TCP traffic.
文摘随着互联网数据中心IDC的快速发展,为其配备的不间断电源系统UPS规模越来越大,由于UPS的电池系统只有在少数的停电时段应用,造成了大量的资源闲置。在保证备电的前提下,充分挖掘UPS中电池系统的储能功能,是一种经济高效的储能形式。在常规UPS的基础上,提出了储能型不间断电源系统(energy storage type of UPS,EUPS)的实现架构,EUPS多种“备电+储能”应用功能的控制策略,以及EUPS参与电网多场景调节的协调控制策略。最后,基于建成的EUPS示范系统,验证了所提的EUPS系统架构和控制策略的有效性。
文摘探讨软件定义网络(Software Defined Network,SDN)在数据中心传输中的自适应流量管理。SDN架构的关键组成要素包括控制器、应用层和南向接口,通过控制平面和数据平面的分离,实现了网络的灵活性和可编程性。OpenFlow协议作为关键通信协议在SDN中得到广泛应用,为控制器提供了调整数据平面行为的标准化手段。在自适应流量管理方面,控制器通过实时监测和智能调整网络状态,识别瓶颈和拥塞点,并根据不同应用的性能需求进行精确的流量管理决策。基于流和基于应用的自适应管理算法使网络能够灵活适应不同流量负载,提高资源利用效率。流量监测工具如NetFlow和sFlow以及反馈机制在实现自适应流量管理中发挥关键作用,实时感知和调整网络状态,使SDN网络更加智能、适应性更强,并提供了优越的应用体验。未来的研究方向将关注SDN中自适应流量管理的创新策略,推动网络技术不断进步。
