Agent-based negotiation approach for feature interactions in smart home systems using calculus of the context-aware ambient

Ahmed S. Alfakeeh, Ali H. Al-Bayatti, Francois Siewe, Thar Baker

Research output: Contribution to journalArticlepeer-review

Abstract

Smart home systems (SHSs) provide several services that are tailored to different residents' preferences. As a result, SHSs are highly exposed to undesirable interactions, known as feature interactions (FIs). FIs might occur as a result of a conflict in services' goals or a conflict with residents' preferences. Previous studies have proposed solutions based on applying priorities, in which some services or preferable features are disabled in favor of other services. Alternatively, the agent-based negotiation approach (ABNA) utilizes agents and applies negotiation, enabling services with contrary features to work simultaneously. ABNA avoids applying priority between services or house residents' preferences whenever a space for a compromise exists. The mechanism of ABNA is based on the use of a hierarchy of features based on their contribution to the function of the service or on the importance of these features to house residents. To achieve a compromise between conflicting services, ABNA models services and residents by using agents, and implements a negotiation algorithm that allows services with conflicting features to work simultaneously. This paper presents a description of ABNA with a formal specification of ABNA in the calculus of context-aware ambient (CCA). This enables the formal analysis of ABNA by using the execution environment of CCA.

Original languageEnglish
Article numbere3808
JournalTransactions on Emerging Telecommunications Technologies
Volume33
Issue number2
DOIs
Publication statusPublished - 2 Dec 2019

Bibliographical note

Funding Information:
This project was funded by the Deanship of Scientific Research (DSR) at King Abdulaziz University, Jeddah, under grant J-723-611-1438. The authors therefore acknowledge with gratitude DSR for its technical and financial support.

Funding Information:
This project was funded by the Deanship of Scientific Research (DSR) at King Abdulaziz University, Jeddah, under grant J‐723‐611‐1438. The authors therefore acknowledge with gratitude DSR for its technical and financial support.

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