|
Showing 1 - 2 of
2 matches in All Departments
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 go" 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.
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 go" 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.
|
You may like...
Loot
Nadine Gordimer
Paperback
(2)
R398
R330
Discovery Miles 3 300
|