Please use this identifier to cite or link to this item:
http://localhost/handle/Hannan/688
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Ghari Neiat, Azadeh. ; | en_US |
dc.contributor.author | Bouguettaya, Athman. ; | en_US |
dc.date.accessioned | 2013 | en_US |
dc.date.accessioned | 2020-05-17T08:20:42Z | - |
dc.date.available | 2020-05-17T08:20:42Z | - |
dc.date.issued | 2018 | en_US |
dc.identifier.isbn | 9783319915364 ; | en_US |
dc.identifier.isbn | 9783319915357 (print) ; | en_US |
dc.identifier.uri | http://localhost/handle/Hannan/688 | - |
dc.description | QA76.76.A65 ; | en_US |
dc.description | en_US | |
dc.description | Printed edition: ; 9783319915357. ; | en_US |
dc.description | 005.7 ; 23 ; | en_US |
dc.description | SpringerLink (Online service) ; | en_US |
dc.description | en_US | |
dc.description | en_US | |
dc.description | en_US | |
dc.description | en_US | |
dc.description | en_US | |
dc.description.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. . ; | en_US |
dc.description.statementofresponsibility | by Azadeh Ghari Neiat, Athman Bouguettaya. | en_US |
dc.description.tableofcontents | 1 Introduction -- 2 Background -- 3 Spatio-Temporal Linear Composition of Sensor-Cloud Services -- 4 Crowdsourced Coverage as a Service: Two-Level Composition of SensorCloud Services -- 5 Incentive-Based Crowdsourcing of Hotspot Services 84 -- 6 Conclusion. ; | en_US |
dc.format.extent | XIX, 116 p. 43 illus., 36 illus. in color. ; online resource. ; | en_US |
dc.publisher | Springer International Publishing : | en_US |
dc.publisher | Imprint: Springer, | en_US |
dc.relation.haspart | 9783319915357.pdf | en_US |
dc.subject | Computer Science | en_US |
dc.subject | Computer Communication Systems | en_US |
dc.subject | Management Information Systems | en_US |
dc.subject | Computer Science | en_US |
dc.subject | Information Systems Applications | en_US |
dc.subject | Management of Computing and Information Systems. ; | en_US |
dc.subject | Computer Communication Networks | en_US |
dc.title | Crowdsourcing of Sensor Cloud Services | en_US |
dc.type | Book | en_US |
dc.publisher.place | Cham : | en_US |
Appears in Collections: | مدیریت فناوری اطلاعات |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
9783319915357.pdf | 3.21 MB | Adobe PDF | Preview File |
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Ghari Neiat, Azadeh. ; | en_US |
dc.contributor.author | Bouguettaya, Athman. ; | en_US |
dc.date.accessioned | 2013 | en_US |
dc.date.accessioned | 2020-05-17T08:20:42Z | - |
dc.date.available | 2020-05-17T08:20:42Z | - |
dc.date.issued | 2018 | en_US |
dc.identifier.isbn | 9783319915364 ; | en_US |
dc.identifier.isbn | 9783319915357 (print) ; | en_US |
dc.identifier.uri | http://localhost/handle/Hannan/688 | - |
dc.description | QA76.76.A65 ; | en_US |
dc.description | en_US | |
dc.description | Printed edition: ; 9783319915357. ; | en_US |
dc.description | 005.7 ; 23 ; | en_US |
dc.description | SpringerLink (Online service) ; | en_US |
dc.description | en_US | |
dc.description | en_US | |
dc.description | en_US | |
dc.description | en_US | |
dc.description | en_US | |
dc.description.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. . ; | en_US |
dc.description.statementofresponsibility | by Azadeh Ghari Neiat, Athman Bouguettaya. | en_US |
dc.description.tableofcontents | 1 Introduction -- 2 Background -- 3 Spatio-Temporal Linear Composition of Sensor-Cloud Services -- 4 Crowdsourced Coverage as a Service: Two-Level Composition of SensorCloud Services -- 5 Incentive-Based Crowdsourcing of Hotspot Services 84 -- 6 Conclusion. ; | en_US |
dc.format.extent | XIX, 116 p. 43 illus., 36 illus. in color. ; online resource. ; | en_US |
dc.publisher | Springer International Publishing : | en_US |
dc.publisher | Imprint: Springer, | en_US |
dc.relation.haspart | 9783319915357.pdf | en_US |
dc.subject | Computer Science | en_US |
dc.subject | Computer Communication Systems | en_US |
dc.subject | Management Information Systems | en_US |
dc.subject | Computer Science | en_US |
dc.subject | Information Systems Applications | en_US |
dc.subject | Management of Computing and Information Systems. ; | en_US |
dc.subject | Computer Communication Networks | en_US |
dc.title | Crowdsourcing of Sensor Cloud Services | en_US |
dc.type | Book | en_US |
dc.publisher.place | Cham : | en_US |
Appears in Collections: | مدیریت فناوری اطلاعات |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
9783319915357.pdf | 3.21 MB | Adobe PDF | Preview File |
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Ghari Neiat, Azadeh. ; | en_US |
dc.contributor.author | Bouguettaya, Athman. ; | en_US |
dc.date.accessioned | 2013 | en_US |
dc.date.accessioned | 2020-05-17T08:20:42Z | - |
dc.date.available | 2020-05-17T08:20:42Z | - |
dc.date.issued | 2018 | en_US |
dc.identifier.isbn | 9783319915364 ; | en_US |
dc.identifier.isbn | 9783319915357 (print) ; | en_US |
dc.identifier.uri | http://localhost/handle/Hannan/688 | - |
dc.description | QA76.76.A65 ; | en_US |
dc.description | en_US | |
dc.description | Printed edition: ; 9783319915357. ; | en_US |
dc.description | 005.7 ; 23 ; | en_US |
dc.description | SpringerLink (Online service) ; | en_US |
dc.description | en_US | |
dc.description | en_US | |
dc.description | en_US | |
dc.description | en_US | |
dc.description | en_US | |
dc.description.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. . ; | en_US |
dc.description.statementofresponsibility | by Azadeh Ghari Neiat, Athman Bouguettaya. | en_US |
dc.description.tableofcontents | 1 Introduction -- 2 Background -- 3 Spatio-Temporal Linear Composition of Sensor-Cloud Services -- 4 Crowdsourced Coverage as a Service: Two-Level Composition of SensorCloud Services -- 5 Incentive-Based Crowdsourcing of Hotspot Services 84 -- 6 Conclusion. ; | en_US |
dc.format.extent | XIX, 116 p. 43 illus., 36 illus. in color. ; online resource. ; | en_US |
dc.publisher | Springer International Publishing : | en_US |
dc.publisher | Imprint: Springer, | en_US |
dc.relation.haspart | 9783319915357.pdf | en_US |
dc.subject | Computer Science | en_US |
dc.subject | Computer Communication Systems | en_US |
dc.subject | Management Information Systems | en_US |
dc.subject | Computer Science | en_US |
dc.subject | Information Systems Applications | en_US |
dc.subject | Management of Computing and Information Systems. ; | en_US |
dc.subject | Computer Communication Networks | en_US |
dc.title | Crowdsourcing of Sensor Cloud Services | en_US |
dc.type | Book | en_US |
dc.publisher.place | Cham : | en_US |
Appears in Collections: | مدیریت فناوری اطلاعات |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
9783319915357.pdf | 3.21 MB | Adobe PDF | Preview File |