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An adaptive meta-heuristic search for the internet of things
Mohammad Ebrahimi1; Elaheh ShafieiBavani1; Raymond K. Wong1; Simon Fong2; Jinan Fiaidhi3
Source PublicationFuture Generation Computer Systems

The number of sensors deployed around the world is growing at a rapid pace when we are moving towards the Internet of Things (loT). The widespread deployment of these sensors represents significant financial investment and technical achievement. These sensors continuously generate enormous amounts of data which is capable of supporting an almost unlimited set of high value proposition applications for users. Given that, effectively and efficiently searching and selecting the most related sensors of a user's interest has recently become a crucial challenge. In this paper, inspired by ant clustering algorithm, we propose an effective context-aware method to cluster sensors in the form of Sensor Semantic Overlay Networks (SSONs) in which sensors with similar context information are gathered into one cluster. Firstly, sensors are grouped based on their types to create SSONs. Then, our meta-heuristic algorithm called AntClust has been performed to cluster sensors using their context information. Furthermore, useful adjustments have been applied to reduce the cost of sensor search process and an adaptive strategy is proposed to maintain the performance against dynamicity in the loT environment. Experiments show the scalability and adaptability of AntClust in clustering sensors. It is significantly faster on sensor search when compared with other approaches. 

KeywordInternet Of Things Context-aware Sensor Search Ant-based Clustering
URLView the original
Indexed BySCIE
WOS Research AreaComputer Science
WOS SubjectComputer Science, Theory & Methods
WOS IDWOS:000407983100042
The Source to ArticleWOS
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Cited Times [WOS]:21   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
Corresponding AuthorSimon Fong
Affiliation1.School of Computer Science and Engineering, University of New South Wales, Australia
2.Department of Computer and Information Science, University of Macau, Macau
3.Department of Computer Science, Lakehead University, Thunder Bay, Canada
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Mohammad Ebrahimi,Elaheh ShafieiBavani,Raymond K. Wong,et al. An adaptive meta-heuristic search for the internet of things[J]. Future Generation Computer Systems,2015,76:486-494.
APA Mohammad Ebrahimi,Elaheh ShafieiBavani,Raymond K. Wong,Simon Fong,&Jinan Fiaidhi.(2015).An adaptive meta-heuristic search for the internet of things.Future Generation Computer Systems,76,486-494.
MLA Mohammad Ebrahimi,et al."An adaptive meta-heuristic search for the internet of things".Future Generation Computer Systems 76(2015):486-494.
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