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E-grāmata: Optimal Coverage in Wireless Sensor Networks

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This book will serve as a reference, presenting state-of-the-art research on theoretical aspects of optimal sensor coverage problems. Readers will find it a useful tool for furthering developments on theory and applications of optimal coverage; much of the content can serve as material for advanced topics courses at the graduate level. The book is well versed with the hottest research topics such as Lifetime of Coverage, Weighted Sensor Cover, k-Coverage, Heterogeneous Sensors, Barrier, Sweep and Partial Coverage, Mobile Sensors, Camera Sensors and Energy-Harvesting Sensors, and more. Topics are introduced in a natural order from simple covers to connected covers, to the lifetime problem. Later, the book begins revisiting earlier problems ranging from the introduction of weights to coverage by k sensors and partial coverage, and from sensor heterogeneity to novel problems such as the barrier coverage problem. The book ends with coverage of mobile sensors, camera sensors, energy-harvesting sensors, underwater sensors, and crowdsensing.

Recenzijas

Optimal Coverage in wireless sensor networks is an highly interesting source of information on theoretical aspects of optimal sensor networks coverage and connectivity problems. Without doubt it can be suggested as a reference textbook, presenting mainly theoretical but also partially practical problems being currently hot research subjects. (Józef Woniak, zbMATH 1486.90002, 2022)

1 Introduction
1(6)
1.1 Sensor and Sensor Network
1(2)
1.2 Sensing Model
3(1)
1.3 Communication Model
4(3)
2 Fundamental Issues
7(16)
2.1 Coverage
7(7)
2.2 Connectivity
14(2)
2.3 Energy Efficiency
16(1)
2.4 Deployment
17(2)
2.5 Approximation
19(4)
3 Sensor Cover
23(10)
3.1 Motivation and Overview
23(1)
3.2 Complexity
24(2)
3.3 Planar Expansion Theorem
26(3)
3.4 PTAS
29(4)
4 Connected Sensor Cover
33(34)
4.1 Motivation and Overview
33(1)
4.2 NP-Hardness
34(2)
4.3 0(r)-Approximation
36(1)
4.4 Network Steiner Tree
37(13)
4.4.1 LP Relaxation for NST
37(3)
4.4.2 The Algorithm
40(1)
4.4.3 Bridge Lemma
40(3)
4.4.4 Performance Ratio
43(7)
4.5 Metric Approximation
50(4)
4.6 Randomized O(log2 n log m)-Approximation
54(7)
4.7 O((RS//Rc)2)-Approximation
61(6)
5 Lifetime of Coverage
67(20)
5.1 Motivation and Overview
67(3)
5.2 Complexity
70(1)
5.3 Garg-Kdnemann Method
71(5)
5.4 Lifetime of Connected Coverage
76(6)
5.5 Weighted Connected Sensor Cover
82(3)
5.6 A Framework of Calnescu
85(2)
6 Weighted Sensor Cover
87(30)
6.1 Motivation and Overview
87(1)
6.2 Partition: 28-Approximation
88(10)
6.3 Double Partition: 6-Approximation
98(4)
6.4 Jigsaw Puzzle: 4-Approximation
102(5)
6.5 Magic Transformation: 3.63-Approximation
107(8)
6.6 PTAS
115(2)
7 It-Coverage
117(18)
7.1 Motivation and Overview
117(1)
7.2 Reduction to Weighted Sensor k-Cover
118(1)
7.3 Parity Strip Multi-Cover
119(6)
7.4 (4 + ε)-Approximation
125(4)
7.5 (3 + ε)-Approximation
129(6)
8 Heterogeneous Sensors
135(18)
8.1 Motivation and Overview
135(2)
8.2 Minimum Weight Set Multi-Cover
137(3)
8.3 Minimum Weight Disk Multi-Cover
140(8)
8.3.1 Shallow Cell Complexity and £-Net
141(2)
8.3.2 E-Net and Minimum Cardinality Disk Cover
143(1)
8.3.3 Quasi-Uniform Sampling and Minimum Weight Disk Cover
144(3)
8.3.4 Minimum Weight Disk Multi-Cover
147(1)
8.4 Minimum Power Cover
148(2)
8.5 Composite Event Coverage
150(3)
9 Grid-Based Deployment
153(6)
9.1 Motivation and Overview
153(1)
9.2 Coverage with Connectivity
154(1)
9.3 Coverage with Localization
155(4)
10 Barrier Coverage
159(24)
10.1 Motivation and Overview
159(4)
10.2 Disjoint Barrier Covers
163(2)
10.3 Secure Schedule with Homogeneous Sensors
165(6)
10.4 Secure Schedule with Heterogeneous Sensors
171(2)
10.5 Quality
173(6)
10.6 Weak Barrier Cover and Local Barrier Cover
179(4)
11 Sweep-Coverage
183(10)
11.1 Motivation and Overview
183(1)
11.2 Complexity
184(1)
11.3 Min-Sensor Sweep-Coverage
185(2)
11.4 Min-Sweep-Period Sweep-Coverage
187(3)
11.5 Variations
190(3)
12 Partial Coverage
193(10)
12.1 Motivation and Overview
193(1)
12.2 Geometric Maximum Coverage
194(2)
12.3 Setfc-Cover
196(2)
12.4 Minimum Weight Partial Set Multi-Cover
198(2)
12.5 Minimum Partial Sensor Cover
200(2)
12.6 P-Percent Coverage
202(1)
13 Probabilistic Coverage
203(6)
13.1 Motivation and Overview
203(1)
13.2 Random Deployment
204(2)
13.3 Probabilistic Sensing Model
206(3)
14 Mobile Sensors
209(18)
14.1 Motivation and Overview
209(2)
14.2 An Observation on Cascade Healing Paths
211(2)
14.3 Maximum Flow
213(2)
14.4 Greedy Is Exponentially Bad
215(1)
14.5 Online Algorithm with Tight Competitive Ratio
216(8)
14.6 Consider Longest Moving Distance, Again
224(1)
14.7 Remark
225(2)
15 Camera Sensors
227(18)
15.1 Motivation and Overview
227(3)
15.2 Sensing Direction Selection
230(1)
15.3 Group Set Cover
231(9)
15.4 Directional Targets
240(2)
15.5 Target Area
242(3)
16 Energy-Harvesting Sensors
245(12)
16.1 Motivation and Overview
245(1)
16.2 Mule Scheduling
246(5)
16.3 Sleep/Wakeup Scheduling
251(1)
16.4 Hybrid Systems
252(1)
16.5 Energy-Data Dual Coverage
253(4)
17 Underwater Sensors
257(4)
17.1 Motivation and Overview
257(1)
17.2 3D Coverage
257(2)
17.3 Underwater Barrier
259(2)
18 Crowdsensing
261(6)
18.1 Motivation and Overview
261(1)
18.2 Time Coverage
262(2)
18.3 Reward Mechanism
264(1)
18.4 Continuous Coverage
265(2)
Bibliography 267