Neural Network Solution For Service Level Agreement

• Published in: International journal of advanced computer science & applications Vol. 4; no. 2
• Main Author: Al-Aloussi, Sarmad
• Format: Journal Article
• Language: English
• Published: West Yorkshire Science and Information (SAI) Organization Limited 01.01.2013
• Subjects: Artificial neural networks; Data centers; Government services; Impact analysis; Neural networks; Policies; Resource allocation
• ISSN: 2158-107X; 2156-5570
• DOI: 10.14569/IJACSA.2013.040211

Service Oriented Computing is playing an important role in sharing the industry and the way business is conducted and services are delivered and managed. This paradigm is expected to have major impact on service economy; the service sector includes health services, financial services, government services, etc. This involves significant interaction between clients and service providers[1]. This paper is pointed in addressing the problem of enabling Service Level Agreement (SLA) oriented resources allocation in data centers to satisfy competing applications demand for computing services. A QoS report designed to compare performance variables to QoS parameters and indicate when a threshold has been crossed. This paper was suggested a methodology which helps in SLA evaluation and comparison. The methodology was found on the adoption of policies both for service behavior and SLA description and on the definition of a metric function for evaluation and comparison of policies. In addition, this paper contributes a new philosophy to evaluate the agreements between user and service provider by monitoring the measurable and immeasurable qualities to extract the decision by using artificial neural networks (ANN).