Approaches Towards Energy-Efficiency in the Cloud for Emerging Markets

Abstract

With the growing importance of the cloud computing paradigm, it is a challenge for cloud providers to keep the operational costs of the data centers in check, especially in the emerging markets, alongside catering to the customers' needs. It becomes essential to increase the operational efficiency of the data centers to be able to maximize VM (Virtual machine) offerings at minimal cost. To that end, energy-efficiency of the servers plays a critical role, as they influence the electrical and the cooling costs which constitute a major part of the total cost involved in the operation of a data center.Power-savings can be achieved at several different levels in a system: processors, memory, devices, and system-wide (involving powering down multiple components of a host all at once). At the processors level, depending on the workload trends, we can exploit technologies like DVFS (Dynamic Voltage and Frequency Scaling) or P-states when the CPU is running, and CPU sleep states (C-states) when the CPU is idle, to save power. Memory standards such as DDR3 have provisions for putting idle memory banks into low-power states. At the devices level, individual devices can be put into low-power states, controlled and coordinated by a run-time power management framework in the Operating System.This paper outlines the state-of-the-art in power-management technology on server hardware and describes how these raw features can be abstracted into a set of energy policies. We then explain how these policies or energy-profiles can be used to run a cloud datacener energy efficiently. Further, this paper also highlights some of the challenges involved in running cloud infrastructures in the emerging markets optimally despite some unique energy constraints.

Energy Aware Load Prediction for Cloud Data Centers

“…One technique that is found in research literature is Dynamic Frequency and Voltage Scaling (DVFS) [3]. In this research the authors show a technique of creating power management policies for using processor and memory power reduction techniques to minimize the energy used across the data center.…”

“…The problem of reducing the amount of energy required for the operation of CDCs has had much research [1][2][3][4][5][6][7][8][9]. One technique that is found in research literature is Dynamic Frequency and Voltage Scaling (DVFS) [3].…”

Cloud Computing

“…In addition to improving management over existing cache subsystems, using novel cache architectures and technologies can cut energy loss at the start. Dreslinski et al [2008] suggest using near-threshold cache architectures to reduce energy consumption. Additionally, they combine this with traditional cache methods to maintain performance.…”

“…Using components that can automatically scale their power consumption based on current load would move toward achieving this goal; for example, using dynamic voltage and frequency scaling (DVFS)-capable CPUs that provide different P-states (power modes while being utilized), as well as sleep C-states (power modes while idle). Dharwar et al [2012] provide an overview of these techniques along with power capping. The same applies for other components, such as memory and storage disks, which can be put into a low power state while idle.…”

“…With this approach, goal L1 is also achieved since large UPS units leak electricity due to their low efficiency [Greenberg et al 2006]. In addition to cooling and power supply systems, during idle run, subsystems such as cache can be turned off on most modern processors that employ more sophisticated hardware [Dharwar et al 2012]. -W1.…”