Crowdsourcing of Sensor Cloud Services (eBook)

eBook Download: PDF
2018 | 1st ed. 2018
XIX, 116 Seiten
Springer International Publishing (Verlag)
978-3-319-91536-4 (ISBN)

Lese- und Medienproben

Crowdsourcing of Sensor Cloud Services - Azadeh Ghari Neiat, Athman Bouguettaya
Systemvoraussetzungen
53,49 inkl. MwSt
  • Download sofort lieferbar
  • Zahlungsarten anzeigen

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.  

1              Introduction 1.1          Motivation 1.2          Problem Statement 1.3          Research Objectives 1.4          Contributions  1.5          Organization 2              Background 2.1          Sensor-Cloud Architecture 2.2          Service Composition 2.3          Spatio-Temporal Crowdsourced Services 2.4          Incentive Models 2.5          Chapter Summary 3              Spatio-Temporal Linear Composition of Sensor-Cloud Services 3.1          Introduction 3.2          Background 3.3          Spatio-Temporal Model for Sensor-Cloud Services 3.4          Spatio-Temporal Selection of Sensor-Cloud Services 3.5          Spatio-Temporal Quality Model for Line Segment Services 3.6          Spatio-Temporal Linear Composition of Sensor-Cloud Services 3.7          Failure-Proof Spatio-Temporal Composition of Sensor Cloud Services 3.8          Performance Study 3.9          Chapter Summary 4              Crowdsourced Coverage as a Service: Two-Level Composition of SensorCloud Services 4.1          Introduction 4.2          Coverage as a Service (CaaS) 4.3          Double-Layered Crowdsourced Sensor-Cloud Service Composition 4.4          Experimental Results 4.5          Chapter Summary 5              Incentive-Based Crowdsourcing of Hotspot Services 84 5.1          Introduction 5.2          Background 5.3          System Model and Problem Formulation 5.4          Spatio-Temporal Incentive-Based Approach 5.5          Experiment Results 5.6          Chapter Summary 6              Conclusion 6.1          Research Objectives Revisited 6.2          Future Research 

Erscheint lt. Verlag 25.6.2018
Zusatzinfo XIX, 116 p. 43 illus., 36 illus. in color.
Verlagsort Cham
Sprache englisch
Themenwelt Mathematik / Informatik Informatik
Wirtschaft Betriebswirtschaft / Management Wirtschaftsinformatik
Schlagworte computing • Coverage equilibrium • Crowdsourced services • Crowdsourced WiFi hotspot sharing • dynamic reconfiguration • Incentive model • internet of things • IoT services • QoS • Replanning • Sensor Cloud • Smart City • Spatio-temporal composition • Spatio-temporal service model • travel planning
ISBN-10 3-319-91536-3 / 3319915363
ISBN-13 978-3-319-91536-4 / 9783319915364
Haben Sie eine Frage zum Produkt?
PDFPDF (Wasserzeichen)
Größe: 3,2 MB

DRM: Digitales Wasserzeichen
Dieses eBook enthält ein digitales Wasser­zeichen und ist damit für Sie persona­lisiert. Bei einer missbräuch­lichen Weiter­gabe des eBooks an Dritte ist eine Rück­ver­folgung an die Quelle möglich.

Dateiformat: PDF (Portable Document Format)
Mit einem festen Seiten­layout eignet sich die PDF besonders für Fach­bücher mit Spalten, Tabellen und Abbild­ungen. Eine PDF kann auf fast allen Geräten ange­zeigt werden, ist aber für kleine Displays (Smart­phone, eReader) nur einge­schränkt geeignet.

Systemvoraussetzungen:
PC/Mac: Mit einem PC oder Mac können Sie dieses eBook lesen. Sie benötigen dafür einen PDF-Viewer - z.B. den Adobe Reader oder Adobe Digital Editions.
eReader: Dieses eBook kann mit (fast) allen eBook-Readern gelesen werden. Mit dem amazon-Kindle ist es aber nicht kompatibel.
Smartphone/Tablet: Egal ob Apple oder Android, dieses eBook können Sie lesen. Sie benötigen dafür einen PDF-Viewer - z.B. die kostenlose Adobe Digital Editions-App.

Buying eBooks from abroad
For tax law reasons we can sell eBooks just within Germany and Switzerland. Regrettably we cannot fulfill eBook-orders from other countries.

Mehr entdecken
aus dem Bereich
Datenanalyse für Künstliche Intelligenz

von Jürgen Cleve; Uwe Lämmel

eBook Download (2024)
De Gruyter (Verlag)
74,95
Digitale Geschäftsmodelle auf Basis Künstlicher Intelligenz

von Christian Aichele; Jörg Herrmann

eBook Download (2023)
Springer Fachmedien Wiesbaden (Verlag)
54,99
Wie Sie Daten für die Steuerung von Unternehmen nutzen

von Mischa Seiter

eBook Download (2023)
Vahlen (Verlag)
39,99