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Crowdsourcing of Sensor Cloud Services - Bouguettaya, Athman

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    Brand new, In English, Fast shipping from London, UK; Tout neuf, en anglais, expédition rapide depuis Londres, Royaume-Uni;ria9783030082697_dbm

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        Présentation Crowdsourcing Of Sensor Cloud Services de Bouguettaya, Athman Format Broché

         - Livre Économie

        Livre Économie - Bouguettaya, Athman - 31/12/2018 - Broché - Langue : Anglais

        . .

      • Auteur(s) : Bouguettaya, Athman - Ghari Neiat, Azadeh
      • Editeur : Springer International Publishing
      • Langue : Anglais
      • Parution : 31/12/2018
      • Format : Moyen, de 350g à 1kg
      • Nombre de pages : 136
      • Expédition : 219
      • Dimensions : 23.5 x 15.5 x 0.8
      • ISBN : 9783030082697



      • Résumé :
        This book develops a crowdsourced sensor-cloud service composition framework taking into account spatio-temporal aspects. This book also unfolds new horizons to service-oriented computing towards the direction of crowdsourced sensor data based applications, in the broader context of Internet of Things (IoT). It is a massive challenge for the IoT research field how to effectively and efficiently capture, manage and deliver sensed data as user-desired services. The outcome of this research will contribute to solving this very important question, by designing a novel service framework and a set of unique service selection and composition frameworks. Delivering a novel service framework to manage crowdsourced sensor data provides high-level abstraction (i.e., sensor-cloud service) to model crowdsourced sensor data from functional and non-functional perspectives, seamlessly turning the raw data into ?ready to g? services. A creative indexing model is developed to capture and manage the spatio-temporal dynamism of crowdsourced service providers. Delivering novel frameworks to compose crowdsourced sensor-cloud services is vital. These frameworks focuses on spatio-temporal composition of crowdsourced sensor-cloud services, which is a new territory for existing service oriented computing research. A creative failure-proof model is also designed to prevent composition failure caused by fluctuating QoS. Delivering an incentive model to drive the coverage of crowdsourced service providers is also vital. A new spatio-temporal incentive model targets changing coverage of the crowdsourced providers to achieve demanded coverage of crowdsourced sensor-cloud services within a region. The outcome of this research is expected to potentially create a sensor services crowdsourcing market and new commercial opportunities focusing on crowdsourced data based applications. The crowdsourced community based approach adds significant value to journey planning and map services thus creating a competitive edge for a technologically-minded companies incentivizing new start-ups, thus enabling higher market innovation. This book primarily targets researchers and practitioners, who conduct research work in service oriented computing, Internet of Things (IoT), smart city and spatio-temporal travel planning, as well as advanced-level students studying this field. Small and Medium Entrepreneurs, who invest in crowdsourced IoT services and journey planning infrastructures, will also want to purchase this book.

        Sommaire:
        To the best of our knowledge, this work is among pioneer effort in developing a crowdsourced sensor-cloud service composition framework taking into account spatio-temporal aspects. This research unfolds new horizons to service-oriented computing towards the direction of crowdsourced sensor data based applications, in the broader context of Internet of Things (IoT). It is a massive challenge for the IoT research field how to effectively and efficiently capture, manage and deliver sensed data as user-desired services. The outcome of this research will contribute to solving this very important question, by designing a novel service framework and a set of unique service selection and composition frameworks. ? Provides a novel service framework to manage crowdsourced sensor data. This service framework aims to provide high-level abstraction (i.e., sensor-cloud service) to model crowdsourced sensor data from functional and non-functional perspectives, seamlessly turning the raw data into ready to go services. A creative indexing model is developed to capture and manage the spatio-temporal dynamism of crowdsourced service providers. ? Delivers novel frameworks to compose crowdsourced sensor-cloud services. These frameworks will focus on spatio-temporal composition of crowdsourced sensor-cloud services, which is a new territory for existing service oriented computing research. A creative failure-proof model is also designed to prevent composition failure caused by fluctuating QoS. ? Presents an incentive model to drive the coverage of crowdsourced service providers. A new spati-temporal incentive model targets changing coverage of the crowdsourced providers to achieve demanded coverage of crowdsourced sensor-cloud services within a region....

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