Service adaptation using fuzzy theory in context-aware mobile computing middleware

Jiannong Cao, Na Xing, Alvin T S Chan, Yulin Feng, Beihong Jin

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

28 Citations (Scopus)

Abstract

Context-aware mobile computing middleware is designed to automatically adapt its behavior to changing environment. To achieve this, an important issue to be addressed is how to effectively select services for adaptation according to the user's current context. Existing work does not adequately address this issue. In this paper, we propose a Fuzzy-based Service Adaptation Model (FSAM) that can be used in context-aware middleware. We formulate the service adaptation process by using fuzzy linguistic variables and membership degrees to define the context situations and the rules for adopting the policies of implementing a service. We propose three fitness functions to calculate the fitness degree for each policy based on the distance of fuzzy status between the policy and the current context situation. The decision for service adaptation is achieved by selecting the policy with the largest fitness degree. A context-aware application scenario called Campus Assistant is used to exemplify the proposed service adaptation process and demonstrate its effectiveness.
Original languageEnglish
Title of host publicationProceedings - 11th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications
Pages496-501
Number of pages6
DOIs
Publication statusPublished - 1 Dec 2005
Event11th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications - Hong Kong, Hong Kong
Duration: 17 Aug 200519 Aug 2005

Conference

Conference11th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications
CountryHong Kong
CityHong Kong
Period17/08/0519/08/05

ASJC Scopus subject areas

  • Engineering(all)

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