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Spatio-Temporal Linear Composition of Sensor Cloud Services

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Abstract

The major contribution of this chapter is that it proposes a novel QoS-based sensor cloud service composition framework using the power of the service paradigm. Two major components are involved in this framework. The first component is a sensor cloud service management framework that comprises a service model and an indexing model of sensor cloud services. Therefore, we present a new service model which aims to abstract a sensor cloud service by conceptualizing the spatio-temporal aspect of the service as its functional attributes and the qualitative aspects of the service as its non-functional attributes. The indexing model aims to spatio-temporally index sensor cloud services to enable an effective and efficient search of the services. We also define novel QoS attributes for evaluating sensor cloud services based on dynamic features of the sensor cloud. The composition combines sensor cloud services to provide a new sensor cloud service. Therefore, the second component of the proposed framework is a spatio-temporal linear composition algorithm which enables users to select optimal composition plans based on their own functional and non-functional requirements.

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Authors and Affiliations

  1. School of Information Technologies, University of School of Information Technologies, NSW, Australia

    Azadeh Ghari Neiat

  2. School of Information Technologies, University of Sydney, NSW, Australia

    Athman Bouguettaya

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  1. Azadeh Ghari Neiat
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  2. Athman Bouguettaya
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Ghari Neiat, A., Bouguettaya, A. (2018). Spatio-Temporal Linear Composition of Sensor Cloud Services. In: Crowdsourcing of Sensor Cloud Services. Springer, Cham. https://doi.org/10.1007/978-3-319-91536-4_3

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  • DOI: https://doi.org/10.1007/978-3-319-91536-4_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-91535-7

  • Online ISBN: 978-3-319-91536-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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