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Kategorie szczegółowe BISAC

Qos Routing Algorithms for Wireless Sensor Networks

ISBN-13: 9789811527227 / Angielski / Miękka / 2021 / 165 str.

K. R. Venugopal; Shiv Prakash T; M. Kumaraswamy
Qos Routing Algorithms for Wireless Sensor Networks K. R. Venugopal Shiv Prakash T M. Kumaraswamy 9789811527227 Springer - książkaWidoczna okładka, to zdjęcie poglądowe, a rzeczywista szata graficzna może różnić się od prezentowanej.

Qos Routing Algorithms for Wireless Sensor Networks

ISBN-13: 9789811527227 / Angielski / Miękka / 2021 / 165 str.

K. R. Venugopal; Shiv Prakash T; M. Kumaraswamy
cena 403,47 zł
(netto: 384,26 VAT:  5%)

Najniższa cena z 30 dni: 385,52 zł
Termin realizacji zamówienia:
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Darmowa dostawa!
inne wydania
Kategorie:
Informatyka, Internet
Kategorie BISAC:
Computers > Networking - Hardware
Computers > Programming - Algorithms
Computers > Security - General
Wydawca:
Springer
Język:
Angielski
ISBN-13:
9789811527227
Rok wydania:
2021
Wydanie:
2020
Ilość stron:
165
Waga:
0.27 kg
Wymiary:
23.39 x 15.6 x 1.04
Oprawa:
Miękka
Wolumenów:
01
Dodatkowe informacje:
Wydanie ilustrowane

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 Protocols 
1.1.2 Contention MAC Protocols 
1.1.3 Hybrid MAC Protocols 
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 Protocol 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 Protocol 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
Protocol 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 Protocol (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 

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.

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.



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