The document outlines a stochastic framework for energy efficiency and performance analysis in dynamic voltage scaling (DVS)-enabled cloud datacenters to address the increasing demand for green cloud solutions. It emphasizes the need for energy-aware management of applications to reduce operational costs and improve system reliability, leveraging DVS technology to balance performance and energy efficiency. The framework utilizes various server metrics and queuing network-based analysis to optimize the design of high-performance cloud systems.

1. A Stochastic Approach to Analysis of Energy-Aware DVS-Enabled Cloud
Datacenters
Abstract:
With the increasing call for green cloud, reducing energy consumption has
been an important requirement for cloud resource providers not only to
reduce operating costs, but also to improve system reliability. Dynamic
voltage scaling (DVS) has been a key technique in exploiting the hardware
characteristics of cloud datacenters to save energy by lowering the supply
voltage and operating frequency. This paper presents a novel stochastic
framework for energy efficiency and performance analysis of DVS-enabled
cloud. This framework uses virtual machine request arrival rate, failure
rate, repair rate, and service rate of datacenter servers as model inputs.
Based on a queuing network- based analysis, this paper gives analytic
solutions of three metrics. The proposed framework can be used to help the
design and optimization of energy-aware high performance cloud systems.
Existing System:
It delivers computing services to users as a utility in a pay-as-you-go
manner. Cloud providers offer various types of services, such as IaaS, PaaS,

2. and SaaS. They make good use of IaaS and PaaS for developing their
services and need no consideration of physical configurations of
computational resources, while users can also access on-demand and pay-
per-use services anywhere. The operation of large geographically
distributed cloud datacenters requires a considerable amount of energy
that accounts for a large slice of the total operational cost for cloud based
applications.
Proposed System:
Therefore, how to manage the applications in a cloud datacenter in an
energy-efficient way becomes an urgent problem. DVS technologies give
rise to a flexible solution to the above question.
DVS tries to address the trade-off between performance and energy
efficiency by taking into account two important characteristics of today’s
computational systems:
1) The energy needed at the peak computing rate is much higher than the
average one and
2) Most today’s processors are based on CMOS logic. They suggest that
high performance is needed only for a small fraction of the time in general,
while for the rest of the time, a low-performance low-power pattern
suffices.
We can achieve the low performance by simply lowering the operating
frequency of processors since the full speed mode is less energy-efficient.
DVS goes beyond this and scales the operating voltage of processors along
with the frequency. This is supported by today’s CMOS technology used
by mainstream unicore/multicore processors.
Hardware Requirements:

3. • System : Pentium IV 2.4 GHz.
• Hard Disk : 40 GB.
• Floppy Drive : 1.44 Mb.
• Monitor : 15 VGA Colour.
• Mouse : Logitech.
• RAM : 256 Mb.
Software Requirements:
• Operating system : - Windows XP.
• Front End : - JSP
• Back End : - SQL Server
Software Requirements:
• Operating system : - Windows XP.
• Front End : - .Net
• Back End : - SQL Server