Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/688
Title: Crowdsourcing of Sensor Cloud Services
Authors: Ghari Neiat, Azadeh. ;;Bouguettaya, Athman. ;
subject: Computer Science;Computer Communication Systems;Management Information Systems;Computer Science;Information Systems Applications;Management of Computing and Information Systems. ;;Computer Communication Networks
Year: 2018
place: Cham :
Publisher: Springer International Publishing :
Imprint: Springer,
Abstract: 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 eeready to goee 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. . ;
Description: QA76.76.A65 ;

Printed edition: ; 9783319915357. ;
005.7 ; 23 ;
SpringerLink (Online service) ;




URI: http://localhost/handle/Hannan/688
ISBN: 9783319915364 ;
9783319915357 (print) ;
More Information: XIX, 116 p. 43 illus., 36 illus. in color. ; online resource. ;
Appears in Collections:مدیریت فناوری اطلاعات

Files in This Item:
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9783319915357.pdf3.21 MBAdobe PDFThumbnail
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Title: Crowdsourcing of Sensor Cloud Services
Authors: Ghari Neiat, Azadeh. ;;Bouguettaya, Athman. ;
subject: Computer Science;Computer Communication Systems;Management Information Systems;Computer Science;Information Systems Applications;Management of Computing and Information Systems. ;;Computer Communication Networks
Year: 2018
place: Cham :
Publisher: Springer International Publishing :
Imprint: Springer,
Abstract: 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 eeready to goee 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. . ;
Description: QA76.76.A65 ;

Printed edition: ; 9783319915357. ;
005.7 ; 23 ;
SpringerLink (Online service) ;




URI: http://localhost/handle/Hannan/688
ISBN: 9783319915364 ;
9783319915357 (print) ;
More Information: XIX, 116 p. 43 illus., 36 illus. in color. ; online resource. ;
Appears in Collections:مدیریت فناوری اطلاعات

Files in This Item:
File Description SizeFormat 
9783319915357.pdf3.21 MBAdobe PDFThumbnail
Preview File
Title: Crowdsourcing of Sensor Cloud Services
Authors: Ghari Neiat, Azadeh. ;;Bouguettaya, Athman. ;
subject: Computer Science;Computer Communication Systems;Management Information Systems;Computer Science;Information Systems Applications;Management of Computing and Information Systems. ;;Computer Communication Networks
Year: 2018
place: Cham :
Publisher: Springer International Publishing :
Imprint: Springer,
Abstract: 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 eeready to goee 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. . ;
Description: QA76.76.A65 ;

Printed edition: ; 9783319915357. ;
005.7 ; 23 ;
SpringerLink (Online service) ;




URI: http://localhost/handle/Hannan/688
ISBN: 9783319915364 ;
9783319915357 (print) ;
More Information: XIX, 116 p. 43 illus., 36 illus. in color. ; online resource. ;
Appears in Collections:مدیریت فناوری اطلاعات

Files in This Item:
File Description SizeFormat 
9783319915357.pdf3.21 MBAdobe PDFThumbnail
Preview File