|
|
|
|
| LEADER |
00000cam a2200000 i 4500 |
| 001 |
SCIDIR_ocn949929640 |
| 003 |
OCoLC |
| 005 |
20231120112109.0 |
| 006 |
m o d |
| 007 |
cr cnu---unuuu |
| 008 |
160519s2016 enk ob 001 0 eng d |
| 040 |
|
|
|a OPELS
|b eng
|e rda
|e pn
|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
|d OCLCO
|d OCLCQ
|d OCLCO
|
| 015 |
|
|
|a GBB663155
|2 bnb
|
| 016 |
7 |
|
|a 017836618
|2 Uk
|
| 019 |
|
|
|a 1066654673
|a 1105191027
|a 1105573562
|a 1235826773
|
| 020 |
|
|
|a 9780128037027
|q (ePub ebook)
|
| 020 |
|
|
|a 0128037024
|
| 020 |
|
|
|z 9780128036631
|
| 020 |
|
|
|z 012803663X
|
| 035 |
|
|
|a (OCoLC)949929640
|z (OCoLC)1066654673
|z (OCoLC)1105191027
|z (OCoLC)1105573562
|z (OCoLC)1235826773
|
| 050 |
|
4 |
|a QA76.5915
|
| 082 |
0 |
4 |
|a 004
|2 23
|
| 245 |
0 |
0 |
|a Pervasive computing :
|b next generation platforms for intelligent data collection /
|c edited by Ciprian Dobre and Fatos Xhafa.
|
| 264 |
|
1 |
|a London, UK :
|b Academic Press is an imprint of Elsevier,
|c 2016.
|
| 300 |
|
|
|a 1 online resource
|
| 336 |
|
|
|a text
|b txt
|2 rdacontent
|
| 337 |
|
|
|a computer
|b c
|2 rdamedia
|
| 338 |
|
|
|a online resource
|b cr
|2 rdacarrier
|
| 490 |
1 |
|
|a Intelligent data-centric systems: Sensor collected intelligence
|
| 500 |
|
|
|a Includes index.
|
| 588 |
0 |
|
|a Online resource; title from PDF title page (ScienceDirect, viewed May 19, 2016).
|
| 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 sensing process: 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-based incentive 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 research motivation -- 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 T�rhel 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 -- 5.2 Modeling 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 Group connect 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.
|
| 504 |
|
|
|a Includes bibliographical references and index.
|
| 650 |
|
0 |
|a Ubiquitous computing.
|
| 650 |
|
6 |
|a Informatique omnipr�esente.
|0 (CaQQLa)201-0371302
|
| 650 |
|
7 |
|a Ubiquitous computing
|2 fast
|0 (OCoLC)fst01160283
|
| 700 |
1 |
|
|a Dobre, Ciprian,
|e editor.
|
| 700 |
1 |
|
|a Xhafa, Fatos,
|e editor.
|
| 776 |
0 |
8 |
|i Print version :
|z 9780128036631
|
| 830 |
|
0 |
|a Intelligent data centric systems.
|
| 856 |
4 |
0 |
|u https://sciencedirect.uam.elogim.com/science/book/9780128036631
|z Texto completo
|
