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.
Rezensionen / Stimmen
"The book is suitable for scientists and programmers, both for research and for developing practical applications. . the proposed approaches, models, and algorithms could be useful for managing similar space-intensive and/or time-intensive crowdsourced cloud services." (Snezhana Gocheva-Ilieva, Computing Reviews, February, 2019)
Sprache
Verlagsort
Verlagsgruppe
Springer International Publishing
Illustrationen
7
36 farbige Abbildungen, 7 s/w Abbildungen
XIX, 116 p. 43 illus., 36 illus. in color.
Dateigröße
ISBN-13
978-3-319-91536-4 (9783319915364)
DOI
10.1007/978-3-319-91536-4
Schweitzer Klassifikation
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.