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Server virtualization in autonomic management of heterogeneous workloads
"... Abstract—Server virtualization opens up a range of new possibilities for autonomic datacenter management, through the availability of new automation mechanisms that can be exploited to control and monitor tasks running within virtual machines. This offers not only new and more flexible control to th ..."
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Abstract—Server virtualization opens up a range of new possibilities for autonomic datacenter management, through the availability of new automation mechanisms that can be exploited to control and monitor tasks running within virtual machines. This offers not only new and more flexible control to the operator using a management console, but also more powerful and flexible autonomic control, through management software that maintains the system in a desired state in the face of changing workload and demand. This paper explores in particular the use of server virtualization technology in the autonomic management of data centers running a heterogeneous mix of workloads. We present a system that manages heterogeneous workloads to their performance goals and demonstrate its effectiveness via realsystem experiments and simulation. We also present some of the significant challenges to wider usage of virtual servers in autonomic datacenter management. I.
Large-scale Virtualization in the Emulab Network Testbed
"... Network emulation is valuable largely because of its ability to study applications running on real hosts and “somewhat real ” networks. However, conservatively allocating a physical host or network link for each corresponding virtual entity is costly and limits scale. We present a system that can fa ..."
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Cited by 33 (3 self)
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Network emulation is valuable largely because of its ability to study applications running on real hosts and “somewhat real ” networks. However, conservatively allocating a physical host or network link for each corresponding virtual entity is costly and limits scale. We present a system that can faithfully emulate, on low-end PCs, virtual topologies over an order of magnitude larger than the physical hardware, when running typical classes of distributed applications that have modest resource requirements. This version of Emulab virtualizes hosts, routers, and networks, while retaining near-total application transparency, good performance fidelity, responsiveness suitable for interactive use, high system throughput, and efficient use of resources. Our key design techniques are to use the minimum degree of virtualization that provides transparency to applications, to exploit the hierarchy found in real computer networks, to perform optimistic automated resource allocation, and to use feedback to adaptively allocate resources. The entire system is highly automated, making it easy to use even when scaling to more than a thousand virtual nodes. This paper identifies the many problems posed in building a practical system, and describes the system’s motivation, design, and preliminary evaluation. 1
Analysis of Virtualization Technologies for High Performance Computing Environments
- in Cloud Computing (CLOUD), 62 International Journal of Electrical and Computer Engineering Systems 2011 IEEE International Conference on, 2011
"... All in-text references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately. ..."
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Cited by 24 (7 self)
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All in-text references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately.
VMDriver: A Driver-based Monitoring Mechanism for Virtualization
"... Abstract—Monitoring virtual machine (VM) is an essential function for virtualized platforms. Existing solutions are either coarse-grained–monitoring in granularity of VM level, or not general–only support specific monitoring functions for particular guest operating system (OS). Thus they do not sati ..."
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Cited by 7 (0 self)
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Abstract—Monitoring virtual machine (VM) is an essential function for virtualized platforms. Existing solutions are either coarse-grained–monitoring in granularity of VM level, or not general–only support specific monitoring functions for particular guest operating system (OS). Thus they do not satisfy the monitoring requirement in large-scale server cluster such as data center and public cloud platform, where each physical platform runs hundreds of VMs with different guest OSes. As a result of this reason, we propose VMDriver, a general and fine-grained approach for virtualization monitoring. The novel design of VMDriver is the separation of event interception point in VMM level and rich guest OS semantic reconstruction in management domain. With this design, variant monitoring drivers in management domain can mask the differences of guest OSes. We implement VMDriver on Xen and our experimental study shows that it introduces very small performance overhead. We demonstrate its generality by inspecting four aspects information about the target virtual machines with different guest OSes. The unified interface of VMDriver brings convenience to develop complex monitoring tools for distributed virtualization environment.
Review of facts, data and proposals for a greener Internet
- In Proceedings of Broadnets09
"... Abstract-The issue of Internet energy consumption and its contribution to global warming has been gaining importance lately. In this paper we present a compilation of facts and data extracted from scattered Internet sources and provide an overview of the basic ideas and most relevant methods suggest ..."
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Abstract-The issue of Internet energy consumption and its contribution to global warming has been gaining importance lately. In this paper we present a compilation of facts and data extracted from scattered Internet sources and provide an overview of the basic ideas and most relevant methods suggested to reduce consumption. I.
Reducing wasted resources to help achieve green data centers
"... In this paper we introduce a new approach to the consolidation strategy of a data center that allows an important reduction in the amount of active nodes required to process a heterogeneous workload without degrading the offered service level. This article reflects and demonstrates that consolidatio ..."
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Cited by 4 (0 self)
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In this paper we introduce a new approach to the consolidation strategy of a data center that allows an important reduction in the amount of active nodes required to process a heterogeneous workload without degrading the offered service level. This article reflects and demonstrates that consolidation of dynamic workloads does not end with virtualization. If energy-efficiency is pursued, the workloads can be consolidated even more using two techniques, memory compression and request discrimination, which were separately studied and validated in previous work and is now to be combined in a joint effort. We evaluate the approach using a representative workload scenario composed of numerical applications and a real workload obtained from a top national travel website. Our results indicate that an important improvement can be achieved using 20 % less servers to do the same work. We believe that this serves as an illustrative example of a new way of management: tailoring the resources to meet high level energy efficiency goals. 1.
Optimizing Resource Consumptions in Clouds
"... Abstract—This paper considers the scenario where multiple clusters of Virtual Machines (i.e., termed as Virtual Clusters) are hosted in a Cloud system consisting of a cluster of physical nodes. Multiple Virtual Clusters (VCs) cohabit in the physical cluster, with each VC offering a particular type o ..."
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Cited by 2 (1 self)
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Abstract—This paper considers the scenario where multiple clusters of Virtual Machines (i.e., termed as Virtual Clusters) are hosted in a Cloud system consisting of a cluster of physical nodes. Multiple Virtual Clusters (VCs) cohabit in the physical cluster, with each VC offering a particular type of service for the incoming requests. In this context, VM consolidation, which strives to use a minimal number of nodes to accommodate all VMs in the system, plays an important role in saving resource consumption. Most existing consolidation methods proposed in the literature regard VMs as “rigid” during consolidation, i.e., VMs ’ resource capacities remain unchanged. In VC environments, QoS is usually delivered by a VC as a single entity. Therefore, there is no reason why VMs’ resource capacity cannot be adjusted as long as the whole VC is still able to maintain the desired QoS. Treating VMs as being “mouldable ” during consolidation may be able to further consolidate VMs into an even fewer number of nodes. This paper investigates this issue and develops a Genetic Algorithm (GA) to consolidate mouldable VMs. The GA is able to evolve an optimized system state, which represents the VM-to-node mapping and the resource capacity allocated to each VM. After the new system state is calculated by the GA, the Cloud will transit from the current system state to the new one. The transition time represents overhead and should be minimized. In this paper, a cost model is formalized to capture the transition overhead, and a reconfiguration algorithm is developed to transit the Cloud to the optimized system state at the low transition overhead. Experiments have been conducted in this paper to evaluate the performance of the GA and the reconfiguration algorithm. Keywords-virtualization; Cluster; Cloud I.
Trusted Computing on Heterogeneous Embedded Systems-on-Chip with Virtualization and Memory Protection
"... Abstract—The paper examines the architecture of a secure and trustworthy cloud platform, which ensures strong logical and physical security on the client devices using a two-layer security mechanism: a) a hardware security module located on the SoC of the client device that protects incoming and out ..."
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Abstract—The paper examines the architecture of a secure and trustworthy cloud platform, which ensures strong logical and physical security on the client devices using a two-layer security mechanism: a) a hardware security module located on the SoC of the client device that protects incoming and outgoing communications (e.g., to/from an external memory) against physical attacks, and b) system software and hypervisor extensions that isolate virtual machines from one another and from the underlying hardware in order to protect against logical attacks. Keywords-cloud computing; confidentiality; integrity; multicore SoC; protection; security; virtualization. I.
Host virtualization: a taxonomy of management challenges
- In SPIRIT 2009, Proceedings of the 2nd Workshop on Services, Platforms, Innovations and Research for new Infrastructures in Telecommunications. Gesellschaft für Informatik
"... Abstract: Host virtualization is quickly being introduced to production environments as it facilitates the recent years ’ computing centre consolidation efforts. While its introduction offers new opportunities in IT management, it also presents challenges that are yet to be tackled. In this paper, w ..."
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Abstract: Host virtualization is quickly being introduced to production environments as it facilitates the recent years ’ computing centre consolidation efforts. While its introduction offers new opportunities in IT management, it also presents challenges that are yet to be tackled. In this paper, we chart these areas of concern according to established conceptual management frameworks and juxtapose the result to a survey of current work. 1
Evaluation of Different Hypervisors Performance in the Private Cloud with SIGAR Framework
"... Abstract — To make cloud computing model Practical and to have essential characters like rapid elasticity, resource pooling, on demand access and measured service, two prominent technologies are required. One is internet and second important one is virtualization technology. Virtualization Technolog ..."
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Abstract — To make cloud computing model Practical and to have essential characters like rapid elasticity, resource pooling, on demand access and measured service, two prominent technologies are required. One is internet and second important one is virtualization technology. Virtualization Technology plays major role in the success of cloud computing. A virtualization layer which provides an infrastructural support to multiple virtual machines above it by virtualizing hardware resources such as CPU, Memory, Disk and NIC is called a Hypervisor. It is interesting to study how different Hypervisors perform in the Private Cloud. Hypervisors do come in Paravirtualized, Full Virtualized and Hybrid flavors. It is novel idea to compare them in the private cloud environment. This paper conducts different performance tests on three hypervisors XenServer, ESXi and KVM and results are gathered using SIGAR API (System Information Gatherer and Reporter) along with Passmark benchmark suite. In the experiment, CloudStack 4.0.2 (open source cloud computing software) is used to create a private cloud, in which management server is installed on Ubuntu 12.04 – 64 bit operating system. Hypervisors XenServer 6.0, ESXi 4.1 and KVM (Ubuntu 12.04) are installed as hosts in the respective clusters and their performances have been evaluated in detail by
