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Monday, 28 May 2018

Customer-Satisfaction-Aware Optimal Multiserver Configuration for Profit Maximization in Cloud Computing

ABSTRACT:
Along with the development of cloud computing, an increasing number of enterprises start to adopt cloud service, which promotes the emergence of many cloud service providers. For cloud service providers, how to configure their cloud service platforms to obtain the maximum profit becomes increasingly the focus that they pay attention to. In this paper, we take customer satisfaction into consideration to address this problem. Customer satisfaction affects the profit of cloud service providers in two ways. On one hand, the cloud configuration affects the quality of service which is an important factor affecting customer satisfaction. On the other hand, the customer satisfaction affects the request arrival rate of a cloud service provider. However, few existing works take customer satisfaction into consideration in solving profit maximization problem, or the existing works considering customer satisfaction do not give a proper formalized definition for it. Hence, we firstly refer to the definition of customer satisfaction in economics and develop a formula for measuring customer satisfaction in cloud computing. And then, an analysis is given in detail on how the customer satisfaction affects the profit. Lastly, taking into consideration customer satisfaction, service-level agreement, renting price, energy consumption and so forth, a profit maximization problem is formulated and solved to get the optimal configuration such that the profit is maximized.

EXISTING SYSTEM:
  • Chen et al. adopted utility theory leveraged from economics and developed an utility model for measuring customer satisfaction in cloud. In the utility model, consumer satisfaction is relevant to two factors: service price and response time. They assumed that consumer satisfaction is decreased with higher service price and longer response time.
  • In other work, the user satisfaction is calculated as the ratio of the actual QoS level and the expected QoS level.
  • Wu et al. proposed an admission control and scheduling algorithms for SaaS providers to maximize profit by minimizing cost and improve customer satisfaction level. However, they did not give a specific formula to measure customer satisfaction level.
  • Chao et al. proposed a customer satisfaction aware algorithm based on the Ant-Colony Optimization (AMP) for geo-distributed datacenters.
DISADVANTAGES OF EXISTING SYSTEM:
  • The request arrival rate of a service provider is affected by many factors in actual, and customer satisfaction is the most important factor
  • Few existing works take customer satisfaction into consideration in solving profit maximization problem, or the existing works considering customer satisfaction do not give a proper formalized definition for it.
  • The existing formulas measuring customer satisfaction of cloud computing cannot properly reflect the definition of customer satisfaction, and they did not take into account user’s psychological differences
PROPOSED SYSTEM:
  • This paper adopts the thought in Business Administration, and firstly defines the customer satisfaction level of cloud computing.
  • Based on the definition of customer satisfaction, we build a profit maximization model in which the effect of customer satisfaction on quality of service (QoS) and price of service (PoS) is considered.
  • In this paper, we build a customer satisfaction- aware profit optimization model and propose a discrete hill climbing algorithm to find the numeric optimal cloud configuration for cloud service providers.
ADVANTAGES OF PROPOSED SYSTEM:
  • Based on the definition of customer satisfaction level in economics, develop a calculation formula for measuring customer satisfaction in cloud
  • Analyze the interrelationship between customer satisfaction and profit, and build a profit optimization model considering customer satisfaction.
  • Develop a discrete hill climbing algorithm to find the optimal cloud configuration such that the profit is maximized.
SYSTEM ARCHITECTURE:
SYSTEM REQUIREMENTS:
HARDWARE REQUIREMENTS: 
  • System : Pentium Dual Core.
  • Hard Disk : 120 GB.
  • Monitor : 15’’ LED
  • Input Devices : Keyboard, Mouse
  • Ram : 1 GB
SOFTWARE REQUIREMENTS: 
  • Operating system : Windows 7.
  • Coding Language : JAVA/J2EE
  • Tool : Eclipse Luna
  • Database : MYSQL