Large latency of applications will bring revenue loss to cloud infrastructure providers in the cloud data center. The existing controllers of software-defined networking architecture can fetch and process traffic info...Large latency of applications will bring revenue loss to cloud infrastructure providers in the cloud data center. The existing controllers of software-defined networking architecture can fetch and process traffic information in the network. Therefore, the controllers can only optimize the network latency of applications. However, the serving latency of applications is also an important factor in delivered user-experience for arrival requests. Unintelligent request routing will cause large serving latency if arrival requests are allocated to overloaded virtual machines. To deal with the request routing problem, this paper proposes the workload-aware software-defined networking controller architecture. Then, request routing algorithms are proposed to minimize the total round trip time for every type of request by considering the congestion in the network and the workload in virtual machines（VMs）. This paper finally provides the evaluation of the proposed algorithms in a simulated prototype. The simulation results show that the proposed methodology is efficient compared with the existing approaches.展开更多
With the wide application of virtualization technology in cloud data centers, how to effectively place virtual machine （VM） is becoming a major issue for cloud providers. The existing virtual machine placement （VMP...With the wide application of virtualization technology in cloud data centers, how to effectively place virtual machine （VM） is becoming a major issue for cloud providers. The existing virtual machine placement （VMP） solutions are mainly to optimize server resources. However, they pay little consideration on network resources optimization, and they do not concern the impact of the network topology and the current network traffic. A multi-resource constraints VMP scheme is proposed. Firstly, the authors attempt to reduce the total communication traffic in the data center network, which is abstracted as a quadratic assignment problem; and then aim at optimizing network maximum link utilization （MLU）. On the condition of slight variation of the total traffic, minimizing MLU can balance network traffic distribution and reduce network congestion hotspots, a classic combinatorial optimization problem as well as NP-hard problem. Ant colony optimization and 2-opt local search are combined to solve the problem. Simulation shows that MLU is decreased by 20%, and the number of hot links is decreased by 37%.展开更多
The data center network(DCN), which is an important component of data centers, consists of a large number of hosted servers and switches connected with high speed communication links. A DCN enables the deployment of r...The data center network(DCN), which is an important component of data centers, consists of a large number of hosted servers and switches connected with high speed communication links. A DCN enables the deployment of resources centralization and on-demand access of the information and services of data centers to users. In recent years, the scale of the DCN has constantly increased with the widespread use of cloud-based services and the unprecedented amount of data delivery in/between data centers, whereas the traditional DCN architecture lacks aggregate bandwidth, scalability, and cost effectiveness for coping with the increasing demands of tenants in accessing the services of cloud data centers. Therefore, the design of a novel DCN architecture with the features of scalability, low cost, robustness, and energy conservation is required. This paper reviews the recent research findings and technologies of DCN architectures to identify the issues in the existing DCN architectures for cloud computing. We develop a taxonomy for the classification of the current DCN architectures, and also qualitatively analyze the traditional and contemporary DCN architectures. Moreover, the DCN architectures are compared on the basis of the significant characteristics, such as bandwidth, fault tolerance, scalability, overhead, and deployment cost. Finally, we put forward open research issues in the deployment of scalable, low-cost, robust, and energy-efficient DCN architecture, for data centers in computational clouds.展开更多
Data Center Networks （DCNs） are the fundamental infrastructure for cloud computing. Driven by the massive parallel computing tasks in cloud computing, one-to-many data dissemination becomes one of the most important...Data Center Networks （DCNs） are the fundamental infrastructure for cloud computing. Driven by the massive parallel computing tasks in cloud computing, one-to-many data dissemination becomes one of the most important traffic patterns in DCNs. Many architectures and protocols are proposed to meet this demand. However, these proposals either require complicated configurations on switches and servers, or cannot deliver an optimal performance. In this paper, we propose the peer-assisted data dissemination for DCNs. This approach utilizes the rich physical connections with high bandwidths and mutli-path connections, to facilitate efficient one-to-many data dissemination. We prove that an optimal P2P data dissemination schedule exists for FatTree, a specially- designed DCN architecture. We then present a theoretical analysis of this algorithm in the general multi-rooted tree topology, a widely-used DCN architecture. Additionally, we explore the performance of an intuitive line structure for data dissemination. Our analysis and experimental results prove that this simple structure is able to produce a comparable performance to the optimal algorithm. Since DCN applications heavily rely on virtualization to achieve optimal resource sharing, we present a general implementation method for the proposed algorithms, which aims to mitigate the impact of the potentially-high churn rate of the virtual machines.展开更多
伴随云计算技术的迅猛发展,海量数据处理与存储的基础设施对网络性能的要求持续提升。软件定义网络(Software Defined Network,SDN)作为实现云计算数据中心优化的关键技术,依靠在网络管理上的灵活性与智能化控制能力,有效提高了网络性...伴随云计算技术的迅猛发展,海量数据处理与存储的基础设施对网络性能的要求持续提升。软件定义网络(Software Defined Network,SDN)作为实现云计算数据中心优化的关键技术,依靠在网络管理上的灵活性与智能化控制能力,有效提高了网络性能、资源利用率与安全性。文章分析了SDN在流量管理、安全保障以及故障检查等方面的应用策略,包括路径优化方案、自动化运维模式和实时管控,切实解决了传统网络所面临的挑战。展开更多
Cloud computing as an emerging technology promises to provide reliable and available services on de- mand. However, offering services for mobile requirements without dynamic and adaptive migration may hurt the perform...Cloud computing as an emerging technology promises to provide reliable and available services on de- mand. However, offering services for mobile requirements without dynamic and adaptive migration may hurt the performance of deployed services. In this paper, we propose MAMOC, a cost-effective approach for selecting the server and migrating services to attain enhanced QoS more econom- ically. The goal of MAMOC is to minimize the total operating cost while guaranteeing the constraints of resource de- mands, storage capacity, access latency and economies, including selling price and reputation grade. First, we devise an objective optimal model with multi-constraints, describing the relationship among operating cost and the above con- straints. Second, a normalized method is adopted to calculate the operating cost for each candidate VM. Then we give a de- tailed presentation on the online algorithm MAMOC, which determines the optimal server. To evaluate the performance of our proposal, we conducted extensive simulations on three typical network topologies and a realistic data center net- work. Results show that MAMOC is scalable and robust with the larger scales of requests and VMs in cloud environment. Moreover, MAMOC decreases the competitive ratio by identifying the optimal migration paths, while ensuring the constraints of SLA as satisfying as possible.展开更多
基金supported by the National Postdoctoral Science Foundation of China(2014M550068)
文摘Large latency of applications will bring revenue loss to cloud infrastructure providers in the cloud data center. The existing controllers of software-defined networking architecture can fetch and process traffic information in the network. Therefore, the controllers can only optimize the network latency of applications. However, the serving latency of applications is also an important factor in delivered user-experience for arrival requests. Unintelligent request routing will cause large serving latency if arrival requests are allocated to overloaded virtual machines. To deal with the request routing problem, this paper proposes the workload-aware software-defined networking controller architecture. Then, request routing algorithms are proposed to minimize the total round trip time for every type of request by considering the congestion in the network and the workload in virtual machines（VMs）. This paper finally provides the evaluation of the proposed algorithms in a simulated prototype. The simulation results show that the proposed methodology is efficient compared with the existing approaches.
基金supported by the National Natural Science Foundation of China(61002011)the National High Technology Research and Development Program of China(863 Program)(2013AA013303)+2 种基金the Fundamental Research Funds for the Central Universities(2013RC1104)the Natural Science Foundation of Gansu Province,China(1308RJZA306)the Open Fund of the State Key Laboratory of Software Development Environment(SKLSDE-2009KF-2-08)
文摘With the wide application of virtualization technology in cloud data centers, how to effectively place virtual machine （VM） is becoming a major issue for cloud providers. The existing virtual machine placement （VMP） solutions are mainly to optimize server resources. However, they pay little consideration on network resources optimization, and they do not concern the impact of the network topology and the current network traffic. A multi-resource constraints VMP scheme is proposed. Firstly, the authors attempt to reduce the total communication traffic in the data center network, which is abstracted as a quadratic assignment problem; and then aim at optimizing network maximum link utilization （MLU）. On the condition of slight variation of the total traffic, minimizing MLU can balance network traffic distribution and reduce network congestion hotspots, a classic combinatorial optimization problem as well as NP-hard problem. Ant colony optimization and 2-opt local search are combined to solve the problem. Simulation shows that MLU is decreased by 20%, and the number of hot links is decreased by 37%.
基金Project supported by the Malaysian Ministry of Higher Education under the University of Malaya High Impact Research Grant(No.UM.C/HIR/MOHE/FCSIT/03)
文摘The data center network(DCN), which is an important component of data centers, consists of a large number of hosted servers and switches connected with high speed communication links. A DCN enables the deployment of resources centralization and on-demand access of the information and services of data centers to users. In recent years, the scale of the DCN has constantly increased with the widespread use of cloud-based services and the unprecedented amount of data delivery in/between data centers, whereas the traditional DCN architecture lacks aggregate bandwidth, scalability, and cost effectiveness for coping with the increasing demands of tenants in accessing the services of cloud data centers. Therefore, the design of a novel DCN architecture with the features of scalability, low cost, robustness, and energy conservation is required. This paper reviews the recent research findings and technologies of DCN architectures to identify the issues in the existing DCN architectures for cloud computing. We develop a taxonomy for the classification of the current DCN architectures, and also qualitatively analyze the traditional and contemporary DCN architectures. Moreover, the DCN architectures are compared on the basis of the significant characteristics, such as bandwidth, fault tolerance, scalability, overhead, and deployment cost. Finally, we put forward open research issues in the deployment of scalable, low-cost, robust, and energy-efficient DCN architecture, for data centers in computational clouds.
基金supported in part by the Natural Science Foundation of USA(Nos.ECCS 1128209,CNS 10655444,CCF 1028167,CNS 0948184,and CCF 0830289)
文摘Data Center Networks （DCNs） are the fundamental infrastructure for cloud computing. Driven by the massive parallel computing tasks in cloud computing, one-to-many data dissemination becomes one of the most important traffic patterns in DCNs. Many architectures and protocols are proposed to meet this demand. However, these proposals either require complicated configurations on switches and servers, or cannot deliver an optimal performance. In this paper, we propose the peer-assisted data dissemination for DCNs. This approach utilizes the rich physical connections with high bandwidths and mutli-path connections, to facilitate efficient one-to-many data dissemination. We prove that an optimal P2P data dissemination schedule exists for FatTree, a specially- designed DCN architecture. We then present a theoretical analysis of this algorithm in the general multi-rooted tree topology, a widely-used DCN architecture. Additionally, we explore the performance of an intuitive line structure for data dissemination. Our analysis and experimental results prove that this simple structure is able to produce a comparable performance to the optimal algorithm. Since DCN applications heavily rely on virtualization to achieve optimal resource sharing, we present a general implementation method for the proposed algorithms, which aims to mitigate the impact of the potentially-high churn rate of the virtual machines.
文摘伴随云计算技术的迅猛发展,海量数据处理与存储的基础设施对网络性能的要求持续提升。软件定义网络(Software Defined Network,SDN)作为实现云计算数据中心优化的关键技术,依靠在网络管理上的灵活性与智能化控制能力,有效提高了网络性能、资源利用率与安全性。文章分析了SDN在流量管理、安全保障以及故障检查等方面的应用策略,包括路径优化方案、自动化运维模式和实时管控,切实解决了传统网络所面临的挑战。
文摘Cloud computing as an emerging technology promises to provide reliable and available services on de- mand. However, offering services for mobile requirements without dynamic and adaptive migration may hurt the performance of deployed services. In this paper, we propose MAMOC, a cost-effective approach for selecting the server and migrating services to attain enhanced QoS more econom- ically. The goal of MAMOC is to minimize the total operating cost while guaranteeing the constraints of resource de- mands, storage capacity, access latency and economies, including selling price and reputation grade. First, we devise an objective optimal model with multi-constraints, describing the relationship among operating cost and the above con- straints. Second, a normalized method is adopted to calculate the operating cost for each candidate VM. Then we give a de- tailed presentation on the online algorithm MAMOC, which determines the optimal server. To evaluate the performance of our proposal, we conducted extensive simulations on three typical network topologies and a realistic data center net- work. Results show that MAMOC is scalable and robust with the larger scales of requests and VMs in cloud environment. Moreover, MAMOC decreases the competitive ratio by identifying the optimal migration paths, while ensuring the constraints of SLA as satisfying as possible.
