Interactive Preference-based Approach to Optimal Feature Configuration of Multi-dimensional Service Platforms

Ezenwoke, Azubuike (2017) Interactive Preference-based Approach to Optimal Feature Configuration of Multi-dimensional Service Platforms. ACM.

PDF Download (780Kb)

Abstract

A multi-dimensional service delivery platform (MDSP) supports development, deployment and management of services in multiple business domains, serves multiple consumers with different functional and non-functional requirements and integrates services from diverse external collaborators to actualize the platform’s business objective. Consumers of product line services have variant needs that are based on the specific requirements of their business objectives, which demands optimal configuration of the MDSP. Optimal configuration of the MDSP connotes the existence of the most appropriate set of features on the MDSP that best approximates the consumer’s requirements, in the face of multiple conflicting objectives. So far, solutions proposed in the literature have mainly used either a priori or a-posterior methods. In prior methods, the requirements and preference information is provided before the configuration process begins; while a set of possible configurations is first generated and preferred selection is made from the set in a-posterior methods. These methods lack the kind of flexibility afforded by interactive methods in an attempt to generate satisfactory results. The aim of this research is to develop an approach that engenders the derivation of optimal configurations from a multi-dimensional service platform (MDSP), in a manner that is interactive and meets the needs of the consumer.

Item Type:	Article
Uncontrolled Keywords:	Feature Modeling, Variability Modeling, Software Product Line, Optimization, multi-objective optimization, Automated Analysis, Cloud computing, Platform as a service, Interactive Configuration, service delivery platform
Subjects:	Q Science > Q Science (General) Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science
Depositing User:	Mrs Hannah Akinwumi
Date Deposited:	07 Mar 2019 08:05
Last Modified:	07 Mar 2019 08:05
URI:	http://eprints.covenantuniversity.edu.ng/id/eprint/12464

Actions (login required)

View Item