Cognitive Sensors and IoT: Architecture, Deployment, and Data Delivery

281 Pages·2017·22.61 MB·English

by  Fadi Al-Turjman

Cognitive Sensors and IoT
Architecture, Deployment,
and Data Delivery
http://taylorandfrancis.com
Cognitive Sensors and IoT
Architecture, Deployment,
and Data Delivery
Fadi Al-Turjman
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Contents
Preface xiii
about the author xv
chaPter 1 IntroductIon to cognItIon In Iot 1
1.1 Contributions 2
1.2 Book Outline 4
chaPter 2 InformatIon-centrIc SenSor networkS
for cognItIve Iot: an overvIew 5
2.1 Introduction 5
2.2 WSN Design Issues in IoT Applications 8
2.2.1 User Expectations from the Network 8
2.2.1.1 Multi-User Application Platform
Support 8
2.2.1.2 User Requirement—Aware
Request Classification 9
2.2.1.3 Internet Access Interface between
User and WSN 10
2.2.2 Adaptations at the Network Level 10
2.2.2.1 Energy Considerations and
Resource Management 10
2.2.2.2 Query Dissemination and Data
Delivery 11
2.2.3 Summary of WSN Design Change
Requirements 12
2.3 Artificial Intelligence and Learning in WSN 14
2.3.1 Computational Intelligence 14
vii
viii Contents
2.3.2 Machine Learning 16
2.3.2.1 Model-Based Reinforcement
Learning 17
2.3.2.2 Model-Free Reinforcement Learning 17
2.3.2.3 Support Vector Machines 18
2.3.3 Cognitive Framework and Multiagent Systems 18
2.3.4 Context Aware Computing 19
2.4 A Hybrid Solution Platform: Learning in ICSN 19
2.4.1 What Should the ICSN Learn? 19
2.4.2 Choosing the Learning Strategy 24
2.4.3 Heuristically Accelerated Reinforcement
Learning 25
2.4.4 Learning in the ICSN Framework 26
2.5 Use-Case and Performance Evaluation 30
2.5.1 Simulation Setup 31
2.5.2 Simulation Results and Analysis 33
2.6 Conclusion and Open Issues 35
Acknowledgment 36
References 36
chaPter 3 cognItIve-node archItecture and a
dePloyment Strategy for the future
SenSor networkS 41
3.1 Introduction 41
3.2 Related Work 43
3.3 System Models 47
3.3.1 Network Model 47
3.3.2 Energy Consumption Model 48
3.3.3 Communication Model 50
3.3.4 Operational Cost Model 51
3.3.5 Problem Definition 52
3.4 A Cognitive Deployment Strategy for ICSN 52
3.4.1 Learning 58
3.4.2 Knowledge-Representation and Reasoning 59
3.5 Simulation Results and Discussions 62
3.5.1 The Quality of Information (QoI) Attributes 66
3.5.1.1 Node Reliability (NR) at the
Transmitting Node 66
3.5.1.2 Instantaneous Throughput (IT)
at the Receiving Node 66
3.5.1.3 Observed Latency (OL) at the
Receiving Node 67
3.5.2 Simulation Setup 67
3.5.3 Simulation Results 68
3.6 Conclusions 72
Acknowledgment 72
References 73
Contents ix
chaPter 4 QuantIfyIng connectIvIty In wIreleSS
SenSor networkS wIth grId-baSed
dePloymentS 77
FADI AL-TURJMAN, HOSSAM S. HASSANEIN,
AND MOHAMAD IBNKAHLA
4.1 Introduction 77
4.2 Related Work 80
4.3 System Models 81
4.3.1 Network Model 81
4.3.2 Communication Model 82
4.3.3 Placement Uncertainty Models 84
4.3.3.1 Bounded Uniform Errors 84
4.3.3.2 Unbounded Normal Errors 88
4.4 Quantifying the Grid Connectivity 89
4.4.1 Generic Approach 89
4.4.2 Theoretical Analysis 94
4.5 Discussion and Numerical Results 95
4.5.1 Grid Connectivity with Bounded Uniform
Errors 96
4.5.2 Grid Connectivity with Unbounded Normal
Errors 99
4.6 Conclusion 102
Acknowledgment 103
References 103
chaPter 5 a data delIvery framework for
cognItIve InformatIon-centrIc SenSor
networkS In Smart outdoor monItorIng 107
GAYATHRI SINGH AND FADI AL-TURJMAN
5.1 Introduction 107
5.2 Related Work 110
5.2.1 Information-Centric Networks 110
5.2.2 Data-Centric Sensor Networks 111
5.2.3 Cognition in Communication Networks
and Cognitive Sensor Networks 111
5.3 System Models 115
5.3.1 Quality of Information (QoI) 115
5.3.2 Network Lifetime 116
5.3.2.1 Application Traffic Profiles
for Smart Outdoor Monitoring
Applications 117
5.3.2.2 Network Architecture
and Components 117
5.3.2.3 Node Functions 120
5.4 The COGNICENSE Framework 121
5.4.1 Knowledge Representation 121
5.4.2 Learning 124