Beyond Server Consolidation

Abstract

Virtualization technology was developed in the late 1960s to make more efficient use of hardware. Hardware was expensive, and there was not that much available. Processing was largely outsourced to the few places that did have computers. On a single IBM System/360, one could run in parallel several environments that maintained full isolation and gave each of its customers the illusion of owning the hardware. Virtualization was time sharing implemented at a coarse-grained level, and isolation was the key achievement of the technology. It also provided the ability to manage resources efficiently, as they would be assigned to virtual machines such that deadlines could be met and a certain quality of service could be achieved.

Evolutionary Computing Based on QoS Oriented Energy Efficient VM Consolidation Scheme for Large Scale Cloud Data Centers

“…A significant amount of research has explored VM consolidation approaches [2][3][4][5] for QoS and energy optimization. To deal with overload detection in data centers, initially researchers used the static threshold approach [6], where they considered overall CPU utilization and scheduled hosts to be in the range of certain defined thresholds.…”

“…Later, bin packing problem was considered in [10][11][12] for efficient VM consolidation. Majority of existing approaches have used Best Fit Decrease (BFD) based consolidation [2]. The algorithms made effort to minimize number of host count by packing more and more VMs onto host.…”

A Bio-inspired Approach for Power and Performance Aware Resource Allocation in Clouds

“…According to [7], an idle resource consumes up to 70% of the power consumed at full utilization. Furthermore, average resource utilization of most of the data centers is about 15-20% [21,13] which results in wastage of huge amount of energy. According to Koomey [15], "Total data center power consumption from servers, storage, communications, cooling, and power distribution equipment accounts for 1.7-2.2% of total electricity used in U.S. in 2010".…”

Energy proportionality and workload consolidation for latency-critical applications

“…Hardware enhancements, primarily in dynamic voltage/frequency scaling (DVFS) and idle modes in modern processors [22,45] provide a foundation for energy proportionality. The second goal is workload consolidation, which raises server utilization and minimizes the number of servers needed for a particular set of workloads [14,46,50]. Advances in cluster management [11,32] and server consolidation using virtual machines or container systems have also played an important role in datacenter efficiency by enabling multiple workloads to be consolidated on each machine.…”