QoS Routing Algorithms for Wireless Sensor Networks

by K. R. Venugopal, Shiv Prakash T., M. Kumaraswamy

Overview

This book provides a systematic introduction to the fundamental concepts, major challenges, and effective solutions for Quality of Service in Wireless Sensor Networks (WSNs). Unlike other books on the topic, it focuses on the networking aspects of WSNs, discussing the most important networking issues, including network architecture design, medium access control, routing and data dissemination, node clustering, node localization, query processing, data aggregation, transport and quality of service, time synchronization, and network security.

Featuring contributions from researchers, this book strikes a balance between fundamental concepts and new technologies, providing readers with unprecedented insights into WSNs from a networking perspective. It is essential reading for a broad audience, including academics, research engineers, and practitioners, particularly postgraduate/postdoctoral researchers and engineers in industry. It is also suitable as a textbook or supplementary reading for graduate computer engineering and computer science courses.

Product Details

ISBN-13:	9789811527197
Publisher:	Springer Nature Singapore
Publication date:	02/28/2020
Edition description:	1st ed. 2020
Pages:	165
Product dimensions:	6.10(w) x 9.25(h) x (d)

About the Author

Dr. K. R. Venugopal is the Vice Chancellor of Bangalore University. He holds eleven degrees, including a Ph.D. in Computer Science Engineering from IIT-Madras, Chennai and a Ph.D. in Economics from Bangalore University, as well as degrees in Law, Mass Communication, Electronics, Economics, Business Finance, Computer Science, Public Relations, and Industrial Relations.

Dr. Venugopal has authored and edited 68 books and published more than 800 papers in refereed international journals and conferences. Dr. Venugopal was a Postdoctoral Research Scholar at the University of Southern California, USA. He has been conferred IEEE fellow and ACM Distinguished Educator for his contributions to Computer Science Engineering and Electrical Engineering education.

Dr. Shiv Prakash T. is currently Director of the Vijaya Vittala Institute of Technology, Bangalore, India. He holds a Ph.D., M.S and B.E in Computer Science and Engineering from Bangalore University. He has over ten years of IT experience in the field of Embedded Systems and Digital Multimedia. He is currently authoring the book Mastering Java to be published in 2021. His research areas include Wireless Sensor Networks, Computer Vision, Embedded Linux, and Digital Multimedia.

Dr. M. Kumaraswamy is currently a Professor at the Department of Computer Science and Engineering at SJPT, Bangalore. He holds a Ph.D. in Computer Science and Engineering from JNTU Hyderabad, B.E. degree in Electrical and Electronics Engineering from the University of Mysore, Mysore, and M.Tech in System Analysis and Computer Applications from NITK Surathkal. His research interests include Wireless Sensor Networks and Adhoc Networks.

Table of Contents

1 An Introduction to QoS in Wireless Sensor Networks
1.0.1 Wireless Sensor Network Architecture
1.0.2 Network Layer Issues and Challenges
1.0.3 Limitations of Wireless Sensor Networks
1.0.4 Challenges of Wireless Sensor Networks
1.0.5 Medium Access Control Layer Issues and Challenges 1.0.6 Issues of Medium Access Control MAC Layer
1.0.7 MAC Scheme Design Challenges
1.1 MAC Scheme in Wireless Sensor Networks
1.1.1 Contention-freeMAC Prools
1.1.2 Contention MAC Prools
1.1.3 Hybrid MAC Prools
1.2 Motivation
1.2.1 Network Layer
1.2.2 Medium Access Control Layer
1.2.3 Design and Evaluation Metrics in the Network Layer
1.2.4 Design and Evaluation Metrics in the Medium Access Layer
1.3 Applications of Wireless Sensor Networks
1.4 Quality of Service in Wireless Sensor Networks
1.4.1 Introduction
1.4.2 Quality of Service Architecture
1.4.3 Network and MAC Layer QoS Challenges
1.4.4 Network and MAC Layer QoS Requirements
1.5 Software Tools
1.6 Organization of the Book
References
2 LRTHR: Link-Reliability Based Two-Hop Routing forWSNs
2.1 Introduction
2.2 Related Works
2.3 System Model and Problem Definition
2.4 Algorithm
2.4.1 Link Reliability Estimation
2.4.2 Link Delay Estimation
2.4.3 Node Forwarding Metric
2.4.4 LRTHR: An Example
2.5 Performance Evaluation
2.6 Summary
References
3 FTQAC: Fault Tolerant QoS Adaptive Clustering forWSNs
3.1 Introduction
3.2 Related Works
3.3 System Model and Problem Definition
3.4 Cluster Setup and Primary Cluster Head Selection
3.5 Secondary Cluster Head Selection
3.6 QoS Route Establishment
3.7 Simulation Setup
3.8 Summary
References
4 RTTDR: Real-Time Traffic-Differentiated Routing forWSNs
4.1 Introduction
4.2 Related Works
4.3 System Model and Problem Definition
4.4 Algorithm
4.4.1 Link Reliability Estimation
4.4.2 Queueing and Transmission Delay Estimation
4.4.3 Node Forwarding Metric
4.4.4 Queuing Controller
4.5 Implementation and Performance Evaluation
4.6 Summary
References
5 RARR: Reliable Adaptive Replication Routing Scheme forWSNs
5.1 Introduction
5.2 Related Works
5.3 System Model and Problem Definition
5.4 Algorithm
5.4.1 Link Capacity Estimator
5.4.2 Packet Disseminator
5.4.3 Packet Replicator
5.5 Simulation and Performance Evaluation
5.6 Summary
References
6 ETXTD: ETX and RTT Delay based Fault Detection Algorithm for
WSNs
6.1 Introduction
6.2 Related Works
6.3 System Model and Problem Definition
6.4 Algorithm
6.4.1 Estimation of Expected Transmission Count (ETX) Metric
6.4.2 Estimation of Round Trip Time (RTT) and Round Trip
Path (RTP)
6.4.3 Detection of Faulty Sensor Node
6.4.4 Performance Evaluation
6.5 Summary
References
7 DQTSM: Distributed Qos in Time Synchronized MAC Prool for
WSNs
7.1 Introduction
7.2 Related Works
7.3 System Model and Problem Definition
7.4 Mathematical Model
7.4.1 Energy Consumption
7.4.2 DQTSM Algorithm
7.5 Performance Evaluation
7.6 Summary
References
8 ERRAP: Efficient Retransmission Qos-Aware MAC Scheme for WSNs
8.1 Introduction
8.2 Related Works 8.3 System Model and Problem Definition
8.4 Mathematical Model
8.4.1 One-Hop Retransmissions
8.4.2 Two-QoS Groups
8.4.3 ERRAP Algorithm
8.5 Performance Evaluation
8.5.1 Simulation Setup 8.5.2 One-Hop QoS Group
8.5.3 Two QoS Groups
8.5.4 Minimizing Energy Consumption
8.6 Summary
References
9 CBH-MAC: Contention Based Hybrid MAC Prool forWSNs
9.1 Introduction
9.2 Related Works
9.3 System Model and Problem Definition
9.4 Mathematical Model
9.5 Performance Evaluation
9.5.1 Simulation Setup
9.5.2 Multi-hop Chain Topology
9.5.3 Multi-hop Cross Topology
9.5.4 End-to-End Latency
9.5.5 Packet Delivery Ratio (PDR) Performance
9.5.6 Energy Consumption
9.6 Summary
References
10 DMS-MAC: Qos Distributed Multi-Channel Scheduling MAC
Prool forWSNs
10.1 Introduction
10.2 Related Works
10.3 System Model and Problem Definition
10.4 Mathematical Model
10.4.1 DMS-MAC Algorithm
10.5 Performance Evaluation
10.5.1 Simulation Setup
10.6 Summary References
11 QMSR: Qos Multihop Sensor Routing Cross Layer Design forWSns
11.1 Introduction
11.2 Related Works
11.3 System Model and Problem Definition
11.4 QMSR Algorithm
11.5 Performance Evaluation 11.6 Summary
References
12 EPC: Efficient Gateway Selection for Passive Clustering in MWSNs
12.1 Introduction
12.2 Related Works
12.3 Network Model
12.3.1 Definitions
12.3.2 Mobile Wireless Sensor Network as a Graph
12.4 Problem Definition
12.4.1 Topological Problems associated with Passive Clustering
12.5 Algorithm EPC (Efficient Passive Clustering)
12.5.1 Intelligent Gateway Selection Heuristic
12.5.2 Timeout Mechanism
12.6 Performance Analysis
12.7 Summary
References
13 REAR: Topology Controlled Energy Management in WSNs
13.1 Introduction
13.2 Related Works
13.3 Network Model
13.3.1 Architecture
13.3.2 Wireless Sensor Model
13.4 Problem Definition
13.4.1 Basic Energy Routing (BER) in Wireless Sensor Networks
13.5 ILP and MILP Models for Maximizing the lifetime of Wireless Sensor Networks
13.5.1 Algorithm: Residual Energy Adaptive Routing(REAR)
13.5.2 An Example
13.6 Performance Evaluations
13.7 Summary
References
14 GwIP: Life Time Maximization ofWSNs
14.1 Introduction
14.2 Related Works
14.3 Wireless Sensor Model
14.4 Problem Definition 14.5 Existing Algorithms
14.5.1 Broadcast Incremental Power (BIP)
14.5.2 Weighted Broadcast Incremental Prool (WBIP)
14.6 Proposed Algorithms
14.6.1 Total Energy Weighted Incremental Model (Recharge Model)
14.6.2 Global Weighted Incremental Power (GWIP)
14.6.3 Global Weight Incremental Post Sweep (GWIPS)
14.7 Performance Evaluations
14.8 Summary
References
15 MSNL: Energy Efficient Broadcasting in WSNs
15.1 Introduction
15.2 Related Works
15.3 Wireless Sensor Model
15.4 Problem definition
15.5 Static Network Lifetime
15.5.1 Maximizing Static Network Lifetime
15.6 Performance Evaluations
15.7 Summary
References
16 AANTCHAIN: Adaptive ANTChain for Increasing Lifespan in WSNs
16.1 Introduction
16.2 Related Works
16.3 System Model and Problem Definition
16.4 Algorithm: Adaptive AntChain
16.5 Performance Analysis
16.6 Summary
References 17 SAAQ: Secure Aggregation for Approximate Queries in WSNs
17.1 Introduction
17.2 Related Works
17.2.1 Routing and Data Aggregation
17.2.2 Secure Data Aggregation
17.2.3 Introduction to Synopsis Diffusion Framework
17.2.4 Secured Data Aggregation
17.3 Problem Definition and Models
17.3.1 Network Model
17.3.2 Attack Model
17.3.3 Security Model
17.4 The SAAQ Algorithm
17.4.1 Query Dissemination
17.4.2 Synopsis Generation and Aggregation
17.5 Results and Analysis
17.5.1 Energy Consumption per Data Collection Round
17.5.2 Impact of Inflation Attack on Final Aggregate Computed
17.5.3 Impact of Deflation Attack
17.5.4 Impact of Compromised Nodes on Number of Bytes Sent per Node
17.6 Summary
References
18 SDAMQ: Secure Data Aggregation for Multiple Queries in WSNs
18.1 Introduction
18.2 Related Works
18.2.1 Data Aggregation for Multiple Coexisting Queries
18.2.2 Concealed Data Aggregation
18.3 Preliminaries
18.3.1 SafeQ
18.3.2 CDAMA: Concealed Data Aggregation Scheme for Multiple Applications in Wireless Sensor Networks
18.4 Problem Definition and Models
18.4.1 Network Model
18.4.2 Query Model
18.4.3 Attack Model
18.5 The SDAMQ Algorithm 18.5.1 Query Dissemination
18.5.2 Data Generation and Aggregation
18.5.3 Decryption
18.6 Results and Analysis
18.6.1 Impact of Network Size on Overall Energy Consumption
18.6.2 Impact of Attack on Packet Delivery Ratio
18.7 Summary
References
19 DAMS: Data Aggregation using Mobile Sink in Wireless Sensor Networks
19.1 Introduction
19.2 Related Works
19.2.1 Logical Coordinate Space Construction
19.2.2 Destination Identification
19.2.3 Greedy Forwarding
19.3 Problem Definition and Models
19.3.1 Network Model
19.3.2 Communication Model
19.3.3 Sink Mobility Model
19.4 The Data Aggregation using Mobile Sink (DAMS) Algorithm
19.4.1 Query Dissemination from the Mobile Sink
19.4.2 Query Propagation and Route Establishment
19.4.3 Data Aggregation and Forwarding
19.5 Results and Analysis
19.5.1 Impact of Network Size on Average Energy Consumption
19.5.2 Impact of Network Size on Average Packet Delivery Ratio
19.5.3 Impact of Network Size on Average Path Length
19.5.4 Impact of Network Size on Delay
19.6 Summary
References