Intelligent Resource Inquisition Framework on Internet-of-Things. (February 2017)

• Record Type: Journal Article
• Authors: Bharti, Monika; Saxena, Sharad; Kumar, Rajesh
• Is Part Of: Computers & electrical engineering. Volume 58(2017)
• Page Start: 265
• Page End: 281
• Publication Date: 2017-02
• Subjects: Internet-of-Things (IoT) -- Resource discovery -- Ontology -- Semantic matchmaking -- Bipartite graph -- IRIF-IoT -- SMEBG -- FCL -- GA; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2016.12.023
• Languages: English
• ISSNs: 0045-7906

Abstract

Highlights: Develop an Intelligent Resource inquisition Framework on Internet-of-Things ( IRIF-IoT ). Propose an optimized SMEBG algorithm for resource discovery. Demonstrate its validity on an application, named Electronic Toll Collection ( ETC ). The algorithm minimizes traffic congestion and enhances system performance significantly. Graphical abstract: Abstract: With the exponential growth of resources on Internet-of-Things ( IoT ), discovery has emerged as one of the major challenges due to requirement of self-manageable resources. The traditional discovery approaches fail to meet the challenge with changing IoT requisition for various metrics like mobility patterns, syntax, scale of experiment, access and search type. The proposed "Intelligent Resource Inquisition Framework on Internet-of-Things ( IRIF-IoT )" framework addresses the challenges through its three layers, namely, perception, discovery, and application. Its main features are linking resources through usage of semantic description and ontology, their discovery with "Semantic Matchmaking Engine using Bipartite Graph ( SMEBG )" and to access information via web terminal for users. The search efficiency is evaluated using toll datasets collected from Ladowal Toll Plaza, Punjab, India. The results obtained shows that SMEBG outperforms Fuzzy Control Logic ( FCL ) and Genetic Algorithm ( GA ) by 47% and 57%, respectively.