Optimal
Multiserver Configuration for Profit Maximization in Cloud Computing
ABSTRACT:
As cloud computing becomes more and more popular,
understanding the economics of cloud computing becomes critically important. To
maximize the profit, a service provider should understand both service charges
and business costs, and how they are determined by the characteristics of the
applications and the configuration of a multiserver system. The problem of
optimal multiserver configuration for profit maximization in a cloud computing
environment is studied. Our pricing model takes such factors into considerations
as the amount of a service, the workload of an application environment, the
configuration of a multiserver system, the service-level agreement, the satisfaction
of a consumer, the quality of a service, the penalty of a low-quality service,
the cost of renting, the cost of energy consumption, and a service provider’s
margin and profit. Our approach is to treat a multiserver system as an M/M/m queuing
model, such that our optimization problem can be formulated and solved
analytically. Two server speed and power consumption models are considered,
namely, the idle-speed model and the constant-speed model. The probability
density function of the waiting time of a newly arrived service request is
derived. The expected service charge to a service request is calculated. The
expected net business gain in one unit of time is obtained. Numerical
calculations of the optimal server size and the optimal server speed are
demonstrated.
EXISTING SYSTEM:
To increase the revenue of business, a service
provider can construct and configure a multiserver system with many servers of
high speed. Since the actual service time (i.e., the task response time)
contains task waiting time and task execution time, more servers reduce the
waiting time and faster servers reduce both waiting time and execution time.
DISADVANTAGES
OF EXISTING SYSTEM:
However, more servers (i.e., a larger multiserver system)
increase the cost of facility renting from the infrastructure vendors and the
cost of base power consumption. Furthermore, faster servers increase the cost
of energy consumption. Such increased cost may counterweight the gain from
penalty reduction.
PROPOSED SYSTEM:
In this paper, we study the problem of optimal
multiserver configuration for profit maximization in a cloud computing
environment. Our approach is to treat a multiserver system as an M/M/m queuing
model, such that our optimization problem can be formulated and solved analytically.
We consider two server speed and power consumption models, namely, the
idle-speed model and the constant-speed model. Our main contributions are as follows.
We derive the probability density function (pdf) of the waiting time of a newly
arrived service request.
ADVANTAGES
OF PROPOSED SYSTEM:
We calculate the expected service charge to a service
request. Based on these results, we get the expected net business gain in one
unit of time, and obtain the optimal server size and the optimal server speed
numerically. To the best of our knowledge, there has been no similar
investigation in the literature, although the method of optimal multicore
server processor configuration has been employed for other purposes, such as
managing the power and performance tradeoff
SYSTEM REQUIREMENTS:
HARDWARE REQUIREMENTS:
·
System : Pentium IV 2.4 GHz.
·
Hard Disk : 40 GB.
·
Monitor :
15 inch VGA Colour.
·
Mouse :
Logitech Mouse.
·
Ram : 512 MB
·
Keyboard :
Standard Keyboard
SOFTWARE REQUIREMENTS:
·
Operating System : Windows XP.
·
Coding Language : ASP.NET, C#.Net.
·
Database :
SQL Server 2005
REFERENCE:
Junwei Cao, Senior Member, IEEE, Kai
Hwang, Fellow, IEEE, Keqin Li, Senior Member, IEEE, and Albert Y. Zomaya,
Fellow, IEEE, “Optimal Multiserver Configuration for Profit Maximization in
Cloud Computing”, IEEE TRANSACTIONS ON
PARALLEL AND DISTRIBUTED SYSTEMS, VOL. 24, NO. 6, JUNE 2013.
