The large scale virtualized data centers have been established due to the requirement of rapid growth in computational power driven by cloud computing model . The high energy consumption of such data centers is becoming more and more serious problem .In order to reduce the energy consumption, server consolidation techniques are used .But aggressive consolidation of VMs can lead to performance d...

Consolidation of multiple workloads, encapsulated in virtual machines (VMs), can significantly improve efficiency in cloud infrastructures. But consolidation also introduces contention in shared resources such as the memory hierarchy, leading to degraded VM performance. To avoid such degradation, the current practice is to not pack VMs tightly and leave a large fraction of server resource unuse...

Large-scale virtualized data centers require cloud providers to implement scalable, autonomic, and energy-efficient cloud management systems. To address these challenges this thesis provides four main contributions. The first one proposes Snooze, a novel Infrastructure-as-a-Service (IaaS) cloud management system, which is designed to scale across many thousands of servers and virtual machines (...

Large-scale virtualized data centers require cloud providers to implement scalable, autonomic, and energy-efficient cloud management systems. To address these challenges this thesis provides four main contributions. The first one proposes Snooze, a novel Infrastructure-as-a-Service (IaaS) cloud management system, which is designed to scale across many thousands of servers and virtual machines (...

Server consolidation based on virtualization technology simplifies system administration and improves energy efficiency by improving resource utilizations and reducing the physical machine (PM) number in contemporary service-oriented data centers. The elasticity of Internet applications changes the consolidation technologies from addressing virtual machines (VMs) to PMs mapping schemes which mu...

Energy efficiency in data centers is a very important issue and getting growing attention from researchers. One approach to reduce energy consumption is to allocate virtual machines (VMs) to physical machines (PMs) in such a way that the number of idle PMs is maximized. Approaches of this kind are called VM consolidation methods. Idle PMs can be put into an energy-saving sleep mode, in which PM...

Cloud computing has revolutionized the information technology industry by enabling elastic on-demand provisioning of computing resources. The proliferation of Cloud computing has resulted in the establishment of large-scale data centers around the world containing thousands of compute nodes. However, Cloud data centers consume enormous amounts of electrical energy resulting in high operating co...

Cloud Computing is a new paradigm of distributed computing that offers virtualized resources and services over the Internet. To offer Infrastructure-as-a-Service (IaaS) many Cloud providers uses a large data center which usage ranges 5% to 10% of capacity in average. In order to improve Cloud data center management and resources usage a Virtual Machine (VM) consolidation technique can be applie...

Monitoring and analyzing virtual machines (VMs) in a datacenter enables a cloud provider to place them on fewer physical machines with negligible performance penalty, a process which is known as the VM consolidation. Such a consolidation allows the cloud provider to take advantage of dissimilar workloads to reduce the number of ON servers, and thereby, reduce the datacenter energy consumption. ...