國立高雄大學圖資館 |

Pervasive computingnext generation platforms for intelligent data collection /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Pervasive computingedited by Ciprian Dobre and Fatos Xhafa.
Reminder of title:	next generation platforms for intelligent data collection /
other author:	Dobre, Ciprian,
Published:	London, UK :Academic Press is an imprint of Elsevier,2016.
Description:	1 online resource.
Notes:	Includes index.
Subject:	Ubiquitous computing.
Online resource:	https://www.sciencedirect.com/science/book/9780128036631
ISBN:	9780128037027 (electronic bk.)

Pervasive computingnext generation platforms for intelligent data collection /
Pervasive computingnext generation platforms for intelligent data collection /[electronic resource] :edited by Ciprian Dobre and Fatos Xhafa. - London, UK :Academic Press is an imprint of Elsevier,2016. - 1 online resource. - Intelligent data-centric systems: Sensor collected intelligence. - Intelligent data centric systems..

Includes index.

Includes bibliographical references and index.

Front Cover -- Pervasive Computing: Next Generation Platforms for Intelligent Data Collection -- Copyright -- Dedication -- Contents -- Contributors -- About the Editors -- Foreword -- Preface -- Organization of the Book -- Acknowledgments -- Part I: Automated capture of experiences with easy access -- Chapter 1: On preserving privacy in cloud computing using ToR -- 1 Introduction -- 2 Overview of cloud computing -- 2.1 Cloud Computing Reference Model -- 2.2 Privacy in the Cloud -- 2.3 Anonymity in the Cloud -- 3 An overview of ToR -- 3.1 The ToR Network -- 3.2 Connection/Circuit Setup in ToR -- 3.3 Attacks Against ToR -- 3.3.1 Denial of service attack -- 3.3.2 The timing attack -- 3.3.3 Website fingerprinting attack -- 3.4 ToR in Existing Implementations -- 4 ToR in cloud computing -- 4.1 Our Experiments -- 4.1.1 ToR with DropBox -- 4.1.2 ToR with FaceBook -- 4.1.3 ToR with Youtube -- 5 Conclusion -- Acronyms -- Glossary -- References --Chapter 2: Self-adaptive overlay networks -- 1 Introduction -- 2 Background/literature review/context -- 2.1 Unstructured Peer-to-Peer -- 2.1.1 Freenet 2001 -- Joining, leaving, and lookup in Freenet overlay -- 2.1.2 Gnutella 2002 -- Joining, leaving, and lookup in Gnutella overlay -- 2.1.3 FastTrack 2006 -- Joining, leaving, and lookup in FastTrack overlay -- 2.1.4 Other unstructured peer-to-peer overlays -- BitTorrent 2003 -- Gia 2004 -- UMM 2010 -- 2.2 Structured Peer-to-Peer -- 2.2.1 CAN 2001 -- Joining in CAN overlays -- Leaving in CAN overlays -- Lookup in CAN overlays -- Applications of CAN overlays -- 2.2.2 Kademlia 2002 -- Joining and leaving in Kademlia overlays -- Lookup in Kademlia overlays -- Applications of Kademlia overlays -- 2.2.3 Chord 2003 -- Joining and leaving Chord P2P overlays -- Lookup in Chord overlays -- Applications of Chord overlays -- 2.2.4 Other structured P2P overlays.

ISBN: 9780128037027 (electronic bk.)

LCCN: 2017287374Subjects--Topical Terms:

226493
Ubiquitous computing.
Index Terms--Genre/Form:

214472
Electronic books.

LC Class. No.: QA76.5915

Dewey Class. No.: 004

Pervasive computingnext generation platforms for intelligent data collection /
LDR:10459cmm a2200337 a 4500 001 601527
006 m o d
007 cr cnu---unuuu
008 211110s2016 enka gob 001 0 eng d
010 $a 2017287374
020 $a 9780128037027 (electronic bk.)
020 $a 0128037024 (electronic bk.)
020 $a 9780128036631
020 $a 012803663X
035 $a (OCoLC)949929640
035 $a ocn949929640
040 $a OPELS $b eng $c OPELS $d UIU $d YDXCP $d OCLCF $d U3W $d D6H $d WYU $d LQU $d UKMGB $d UUM $d S2H $d OCLCO $d VT2
041 0 $a eng
050 4 $a QA76.5915
082 0 4 $a 004 $2 23
245 0 0 $a Pervasive computing $h [electronic resource] : $b next generation platforms for intelligent data collection / $c edited by Ciprian Dobre and Fatos Xhafa.
260 $a London, UK : $b Academic Press is an imprint of Elsevier, $c 2016.
300 $a 1 online resource.
490 1 $a Intelligent data-centric systems: Sensor collected intelligence
500 $a Includes index.
504 $a Includes bibliographical references and index.
505 0 $a Front Cover -- Pervasive Computing: Next Generation Platforms for Intelligent Data Collection -- Copyright -- Dedication -- Contents -- Contributors -- About the Editors -- Foreword -- Preface -- Organization of the Book -- Acknowledgments -- Part I: Automated capture of experiences with easy access -- Chapter 1: On preserving privacy in cloud computing using ToR -- 1 Introduction -- 2 Overview of cloud computing -- 2.1 Cloud Computing Reference Model -- 2.2 Privacy in the Cloud -- 2.3 Anonymity in the Cloud -- 3 An overview of ToR -- 3.1 The ToR Network -- 3.2 Connection/Circuit Setup in ToR -- 3.3 Attacks Against ToR -- 3.3.1 Denial of service attack -- 3.3.2 The timing attack -- 3.3.3 Website fingerprinting attack -- 3.4 ToR in Existing Implementations -- 4 ToR in cloud computing -- 4.1 Our Experiments -- 4.1.1 ToR with DropBox -- 4.1.2 ToR with FaceBook -- 4.1.3 ToR with Youtube -- 5 Conclusion -- Acronyms -- Glossary -- References --Chapter 2: Self-adaptive overlay networks -- 1 Introduction -- 2 Background/literature review/context -- 2.1 Unstructured Peer-to-Peer -- 2.1.1 Freenet 2001 -- Joining, leaving, and lookup in Freenet overlay -- 2.1.2 Gnutella 2002 -- Joining, leaving, and lookup in Gnutella overlay -- 2.1.3 FastTrack 2006 -- Joining, leaving, and lookup in FastTrack overlay -- 2.1.4 Other unstructured peer-to-peer overlays -- BitTorrent 2003 -- Gia 2004 -- UMM 2010 -- 2.2 Structured Peer-to-Peer -- 2.2.1 CAN 2001 -- Joining in CAN overlays -- Leaving in CAN overlays -- Lookup in CAN overlays -- Applications of CAN overlays -- 2.2.2 Kademlia 2002 -- Joining and leaving in Kademlia overlays -- Lookup in Kademlia overlays -- Applications of Kademlia overlays -- 2.2.3 Chord 2003 -- Joining and leaving Chord P2P overlays -- Lookup in Chord overlays -- Applications of Chord overlays -- 2.2.4 Other structured P2P overlays.
505 8 $a Viceroy 2002 -- SkipNet 2003 -- Coral 2004 -- Tapestry 2004 -- Cycloid 2006 -- HyPeer 2011 -- 3 Self-adaptive overlays -- 3.1 Bio-Inspired P2P Overlays -- 3.1.1 Self-Chord 2010 -- 3.1.2 P2PBA 2011 -- 3.1.3 Self-CAN 2012 -- 3.1.4 Honeycomb 2014 -- 3.1.5 SPIDER 2015 -- 3.2 Multi-Layer Peer-to-Peer -- 4 Hybrid peer-to-peer systems -- 4.1 JXTA -- 4.2 MOPAR -- 5 Discussion and conclusions -- Acronyms -- Acknowledgments -- References -- Chapter 3: Users in the urban sensingprocess: Challenges and research opportunities -- 1 Introduction -- 2 Participatory sensor networks -- 2.1 What is a Participatory Sensor Network? -- 2.2 The Functioning of PSN -- 2.3 Examples of PSNs -- 3 Properties of PSN -- 3.1 Data Description -- 3.2 Network Coverage -- 3.3 Sensing Interval -- 3.4 Routines and Data Sharing -- 3.5 Node Behavior -- 3.6 Discussion -- 4 Working with PSN data -- 4.1 Data Collection -- 4.1.1 APIs -- 4.1.2 Web crawler -- 4.1.3 Applications -- 4.2 Understanding City Dynamics -- 4.3 Social, Economic, and Cultural Patterns -- 4.4 Final Considerations -- 5 Challenges and opportunities -- 5.1 Sensing Layers -- 5.1.1 Preliminaries -- 5.1.2 Framework for the integration of multiple layers -- 5.1.3 Challenges and opportunities -- 5.2 Temporal Dynamics of PSNs -- 5.2.1 Preliminaries -- 5.2.2 Challenges and opportunities -- 5.3 Incentive Mechanism for PSN -- 5.3.1 Preliminaries -- 5.3.2 User cooperation -- 5.3.3 Reward-basedincentive mechanisms -- 5.3.4 Gamification-based incentive mechanism -- 5.3.5 Challenges and opportunities -- 5.4 Quality of Data From PSN -- 5.4.1 Preliminaries -- 5.4.2 Challenges -- 5.4.3 Opportunities -- 5.5 PSNs and Vehicular Networks--5.5.1 Preliminaries -- 5.5.2 Monitoring events -- 5.5.3 Routines and behaviors -- 5.5.4 Traffic management -- 5.5.5 Challenges and opportunities -- 5.6 Other Challenges and Opportunities Related to PSNs.
505 8 $a 5.6.1 Data sampling -- 5.6.2 Large volume of data -- 5.6.3 Privacy -- 6 Conclusion -- Acronyms -- Glossary -- References -- Chapter 4: Integration in the Internet of Things: A semantic middleware approach to seamless integration of heterogeneous t ... -- 1 Introduction -- 2 Motivating scenario -- 3 Current approaches to integration in IoT -- 3.1 Understanding the Integration Issues -- 3.1.1 To connect: The connection problem -- 3.1.2 To communicate: The understanding problem -- 3.1.3 To range: The scalability problem -- 3.1.4 To configure: The adaptation problem -- 3.2 Approaches for Integration: The History -- 3.3 Frameworks Based on Publish/Subscribe -- 3.3.1 Challenges and open issues -- 4 Design of an integration layer for P/S frameworks -- 4.1 Integration Layer -- 4.2 Adapters Design -- 4.2.1 Structure dimension -- 4.2.2 Interaction dimension -- 4.2.3 Behavior dimension -- 4.3 Adapters Implementation and Deployment -- 4.3.1 Boundary layer -- 4.3.2 Control layer -- 4.3.3 Entity layer -- 5 Example of adapters implementation and system deployment -- 5.1 Publisher Adapter -- 5.2 Subscriber Adapter -- 5.3 Run-Time Modifications -- 6 Conclusions and Future Work -- Acronyms -- Glossary -- Acknowledgments -- References -- Part II: Context-aware/sensitive interactions and applications -- Chapter 5: A context-aware system for efficient peer-to-peer content provision -- 1 Introduction -- 2 Related work and researchmotivation -- 2.1 Effective Content Distribution Mechanisms -- 2.2 Service Publication/Management -- 2.3 Peer-to-Peer Network Instantiation Inside the Home Box -- 2.4 Delivery Manager -- 2.5 Publishing Manager -- 2.6 Discovery Manager -- 2.7 Streaming Gateway -- 2.8 HTTP Gateway -- 2.9 Conclusion -- Acronyms -- Glossary -- Acknowledgments -- References -- Chapter 6: Transparent distributed data management in large scale distributed systems.
505 8 $a 1 Introduction and overview -- 1.1 Main Objectives -- 1.2 Contributions -- 2 Mutual Exclusion -- 2.1 Distributed Mutual Exclusion Algorithms -- 2.2 The Naimi and Tréhel Algorithm -- 2.3 Simultaneous Requests -- 3 Algorithm for Exclusive Locks With Mobile Processes (ELMP) -- 3.1 The Data Structure -- 3.2 Atomic Operations -- 3.3 Connecting to the System -- 3.4 Balancing Strategies -- 3.5 Balancing Following New Insertions -- 3.6 Balancing Following a Token Request -- 3.7 Balancing Following Departure -- 3.8 The Proof of the ELMP Algorithm -- 4 Read Write Locks for Mobile Processes (RW-LMP) Algorithm -- 4.1 Handling Requests in the Linked-List -- 4.2 Entering the Critical Section -- 4.3 Leaving the Critical Section -- 4.4 Leaving the System -- 4.5 The Proof of the RW-LMP Algorithm -- 5 Multi-Level Architecture and Data Abstraction -- 5.1 The Basic Model of the DHO API -- 5.1.1 DHO cooperation model -- 5.1.2 The path of a DHO request -- 5.2Modeling of DHO Life Cycle -- 5.3 Observed Delays -- 5.4 Connection and Disconnection at Application Level -- 5.5 Deviation From the Normal DHO Cycle -- 6 Experimental Results -- 6.1 DHO Cycle Evaluation With Asynchronous Locks -- 6.2 Shared and Exclusive Requests -- 6.3 DHO Cycle Evaluation With Mobility of Peers -- 7 Discussion -- 8 Conclusion -- Acronyms -- Glossary -- References -- Chapter 7: Converged information-centric spaces based on wireless data hubs -- 1 Introduction -- 2 Connectivity and congestion in dense wireless spaces -- 2.1 Common Connectivity Problem -- 2.2 Example Devices and Operation Modes -- 2.3 Literature on Wireless Interference and Congestion -- 2.4 Time Slot Division Method -- 3 Groupconnect and wireless traffic offload -- 3.1 Two Wireless Stacks -- 3.2 Conventional Versus P2P WiFi Designs -- 3.3 Basic Idea of Group Connect -- 3.4 Traffic Offload Function of Group Connect.
505 8 $a 4 Wireless data hub -- 4.1 Parameters for a Converged Information-Centric Space -- 4.2 Wireless Data Hub -- 4.3 WDH in the Center of a Social Wireless Network -- 4.4 Maintenance in the No-Wires WDH Space -- 5 Modeling and performance analysis -- 5.1 Mobility Traces and Throughput Datasets -- 5.2 Group Connect and WDH Deployment Models -- 5.3 Group Connect Versus 4G Infrastructure -- 5.4 Wireless Data Hub Versus 3G/LTE Spaces -- 6 Summary -- Acronyms -- Glossary -- References -- Chapter 8: Data fusion for orientation sensing in wireless body area sensor networks using smart phones -- 1 Introduction -- 2 WBASN and E-Health Systems -- 2.1 Data Aggregation and Data Fusion -- 2.1.1 Data fusion algorithms -- 2.2 Smart Phones for e-Health Monitoring -- 3 Orientation sensing -- 3.1 Sensor Data Fusion: A Layered Approach -- 4 Orientation approximation -- 4.1 Gyroscope Accelerometer Integration -- 4.2 Complementary Filtering -- 4.3 Kalman Filter --5 Experimental setup -- 6 Kalman and complementary filtering -- 6.1 On Test Basis -- 6.2 On Real-Time Data -- 6.3 Comparison -- 7 Discussion -- 8 Conclusion and future works -- Acronyms -- Glossary -- References -- Part III: Ubiquitous services independent of devices/platforms -- Chapter 9: Reuse of data from smart medical devices for quality control and evidence-based medicine -- 1 Introduction -- 2 State of the art of medical technology -- 3 Obstacles to the adoption of smart medical devices in the practice -- 4 Smart medical devices as complex cyber-physical systems -- 5 Interdisciplinary approach versus mentality mismatch -- 6 Necessity of postmarket surveillance -- 7 Primary and secondary use of smart medical devices data -- 7.1 Data for Health Support -- 7.1.1 Data characteristics -- 7.1.2 Data management -- 7.2 Data for Quality Assurance -- 7.2.1 Data characteristics -- 7.2.2 Data management.
650 0 $a Ubiquitous computing. $3 226493
655 0 $a Electronic books. $2 local. $3 214472
700 1 $a Dobre, Ciprian, $e editor. $3 872408
700 1 $a Xhafa, Fatos, $e editor. $3 717863
830 0 $a Intelligent data centric systems. $3 784172
856 4 0 $u https://www.sciencedirect.com/science/book/9780128036631