Energy optimization schemes in cluster with virtual machines

Abstract

Large scale clusters based on virtualization technologies have been widely used in many areas, including the data center and cloud computing environment. But how to save energy is a big challenge for building a "green cluster" recently. However, previous researches, including local approaches, which focus on saving the energy of the components in a single workstation without a global vision on the whole cluster, and cluster-wide energy saving techniques, which can only be applied to homogeneous workstations and specific applications, cannot solve the challenges. This paper describes the design and implementation of a novel scheme, called Magnet, that uses live migration of virtual machines to transfer load among the nodes on a multi-layer ring-based overlay. This scheme can reduce the power consumption greatly by regarding all the cluster nodes as a whole based on virtualization technologies. And, it can be applied to both the homogeneous and heterogeneous servers. Experimental measurements show that the new method can reduce the power consumption by 74.8% over base at most with certain adjustably acceptable overhead. The effectiveness and performance insights are also analytically verified.

Modeling and Analysis of Queueing-Based Vary-On/Vary-Off Schemes for Server Clusters

“…Server clusters are widely adopted in cloud data centers [28]. In order to support various kinds of services including user-end applications and back-end activities, heterogeneity becomes common in multifunctional cloud data centers.…”

“…Queueing analysis can be naturally applied to the performance measures of server clusters. Server clusters have been widely adopted in many cloud data centers to resolve the increasing user needs [28]. Although heterogeneity is common in multifunctional cloud data centers, server closets or blade systems that form the basic computing units usually consist of homogeneous nodes.…”

Server consolidation techniques in virtualized data centers of cloud environments: A systematic literature review

“…Using the logic that processor consumes more power compared to other server resources; in most of the researches related to server consolidation the energy evaluation policy is concentrated in CPU utilization parameter . The challenge for this logic appears when data center workload includes GPU‐intensive tasks, as well as CPU‐intensive tasks.…”

“…Using the logic that processor consumes more power compared to other server resources; in most of the researches related to server consolidation the energy evaluation policy is concentrated in CPU utilization parameter. 99,100 The challenge for this logic appears when data center workload includes GPU-intensive tasks, as well as CPU-intensive tasks. By developing an energy consumption evaluation approach, Jiang et al 44 proposed a new live VM consolidation policy based on Artificial Bee Colony (ABC).…”