Title: Multi-user utility pattern based cloud service negotiation for quality of service improvement: an implicit interest prediction approach

Authors: Mohan Manoharan; Selvarajan Saraswathi

Addresses: Department Computer Science and Engineering, Manonmaiyam Sundaranar University, Tirunelveli, Tamil Nadu, India ' Department of Information Technology, Pondicherry Engineering College, Pondicherry, India

Abstract: The growing deployment of cloud services increases the responsibility of cloud service provider in meeting consumer satisfaction in great measure. As the interest of the user changes in time and the number of service providers are growing the cloud user has more options in choosing the required service. But the problem of service negotiation must be handled by all the service providers in order to improve the quality of service. To solve the issue of service negotiation, a multi-user utility pattern based service negotiation approach is discussed in this paper. The method monitors the service negotiation values and keeps track of services accessed by different cloud user. It also maintains a trace of sequence of service access based on user's interest. The proposed technique uses the implicit tracking approach to predict the interest of the user by monitoring the service access without the knowledge of the end user and generate a pattern called utility pattern. Based on the generated pattern, the most impacting services are ranked according to the implicit activities of different users. The ranked services are given to the user to select a single service to fulfil the request. The proposed technique improves the performance of cloud environment to 95% and increases the satisfaction of the cloud user.

Keywords: cloud environment; software as a service; SaaS; service negotiation; service level agreements; SLA; multi-user utility pattern; implicit tracking.

DOI: 10.1504/IJIE.2017.087003

International Journal of Intelligent Enterprise, 2017 Vol.4 No.1/2, pp.3 - 20

Received: 12 Mar 2016
Accepted: 30 Jun 2016
Published online: 04 Oct 2017 *

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