Reshaping The Virtual Machines In Self Organizing Clouds

2335 words - 9 pages

Cloud platforms face two competing requirements from the perspectives of the cloud provider and the cloud user, respectively. The cloud provider would like to minimize power and cooling costs, which form a large portion of their operational costs. To achieve this goal, server consolidation can be used to minimize the number of physical servers required for hosting a set of applications. However, consolidation is often undesirable for cloud users, who are seeking maximum performance and reliability from their applications. Under provisioning of physical resources to applications may indirectly increase costs if frequent SLA violations result in lost business1. The key factor that determines the provisioning requirements of a virtual machine is its physical footprint: the amount of physical resources it consumes in terms of CPU time, storage (memory and disk), network bandwidth, and power. Existing consolidation and dynamic placement techniques have largely treated the physical footprint of a virtual machine as a location-independent measure. That is, it is generally assumed that the footprint of a VM will be the same regardless of which physical machine it is placed on. This assumption is reasonable for a homogeneous environment, where physical machines are identical and most VMs are running the same OS and applications. However, in a cloud environment, we expect a diverse collection of applications to share a resource pool composed of heterogeneous resources. Applications will vary significantly in terms of resource requirements, access patterns and inter-dependencies; and the physical hosts will also vary in terms of their resource capacities and data affinities.
In such an environment, we contend that the physical footprint of a VM is highly malleable; that is, a VM’s physical resource consumption is heavily dependent on its location, the characteristics of its physical host, and its interactions with other VMs. A key factor for achieving economies of scale in a compute cloud is resource provisioning, which refers to allocating resources to VMs to match their workload. Typically, efficient provisioning is achieved by two operations: static resource provisioning. VMs are created with specified size and then consolidated onto a set of physical servers. The VM capacity does not change; and dynamic resource provisioning. VM capacity is dynamically adjusted to match workload fluctuations. Static provisioning often applies to the initial stage of capacity planning. It is usually conducted in offline and occurs on monthly or seasonal timescales. Such provisioning functionality has been included in much commercial cloud management software. In both static and dynamic provisioning, VM sizing is perhaps the most vital step. VM sizing refers to the estimation of the amount of resources that should be allocated to a VM. The objective of VM sizing is to ensure that VM capacity is commensurate with the workload. While over-provisioning...

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