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Issue No. 07 - July (2017 vol. 29)
ISSN: 1041-4347
pp: 1384-1397
Azadeh Ghari Neiat , School of Information Technologies, University of Sydney, Sydney, NSW, Australia
Athman Bouguettaya , School of Information Technologies, University of Sydney, Sydney, NSW, Australia
Timos Sellis , Department of Computing and Software Engineering, Swinburne University of Technology, Hawthorn, Vic, Australia
Sajib Mistry , School of Information Technologies, University of Sydney, Sydney, NSW, Australia
ABSTRACT
We present a new two-level composition model for crowdsourced Sensor-Cloud services based on dynamic features such as spatio-temporal aspects. The proposed approach is defined based on a formal Sensor-Cloud service model that abstracts the functionality and non-functional aspects of sensor data on the cloud in terms of spatio-temporal features. A spatio-temporal indexing technique based on the 3D R-tree to enable fast identification of appropriate Sensor-Cloud services is proposed. A novel quality model is introduced that considers dynamic features of sensors to select and compose Sensor-Cloud services. The quality model defines Coverage as a Service which is formulated as a composition of crowdsourced Sensor-Cloud services. We present two new QoS-aware spatio-temporal composition algorithms to select the optimal composition plan. Experimental results validate the performance of the proposed algorithms.
INDEX TERMS
Quality of service, IEEE 802.11 Standard, Indexing, Planning, Heuristic algorithms, Australia
CITATION

A. G. Neiat, A. Bouguettaya, T. Sellis and S. Mistry, "Crowdsourced Coverage as a Service: Two-Level Composition of Sensor Cloud Services," in IEEE Transactions on Knowledge & Data Engineering, vol. 29, no. 7, pp. 1384-1397, 2017.
doi:10.1109/TKDE.2017.2672738
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