Wireless sensor networks: an information processing approach
Saved in:
| Main Author: | |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Amsterdam [u.a.]
Elsevier
2004
|
| Series: | The Morgan Kaufmann series in networking
|
| Subjects: | |
| Online Access: | Table of contents Publisher description Inhaltsverzeichnis |
| Item Description: | Includes bibliographical references (p. 323-345) and index |
| Physical Description: | XVII, 358 S. Ill., graph. Darst. 25 cm |
| ISBN: | 1558609148 9781558609143 |
Staff View
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| 245 | 1 | 0 | |a Wireless sensor networks |b an information processing approach |c Feng Zhao ; Leonidas J. Guibas |
| 264 | 1 | |a Amsterdam [u.a.] |b Elsevier |c 2004 | |
| 300 | |a XVII, 358 S. |b Ill., graph. Darst. |c 25 cm | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
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| 490 | 0 | |a The Morgan Kaufmann series in networking | |
| 500 | |a Includes bibliographical references (p. 323-345) and index | ||
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| 650 | 7 | |a Réseaux locaux sans fil |2 ram | |
| 650 | 7 | |a Systèmes de communication sans fil |2 ram | |
| 650 | 4 | |a Sensor networks | |
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| 700 | 1 | |a Guibas, Leonidas J. |e Sonstige |4 oth | |
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Record in the Search Index
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|---|---|
| adam_text | Contents
Preface
xiii
Introduction
1
1.1
Unique
Constraints and
Challenges
2
1.2
Advantages of Sensor
Networks
6
1.2.1
Energy Advantage
7
1.2.2
Detection Advantage
8
1.3
Sensor Network Applications
9
13.1
Habitat Monitoring
10
1.3.2
Tracking Chemical Plumes
12
1.3.3
Smart Transportation
13
1.4
Collaborative Processing
16
1.5
Key Definitions of Sensor Networks
17
1.6
The Rest of the Book
20
2
Contents
Canonical Problem: Localization and Tracking
23
2.1
A Tracking Scenario
25
2.2
Problem Formulation
27
2.2.1
Sensing Model
28
2.2.2
Collaborative Localization
30
2.2.3
Bayesian State Estimation
32
2.3
Distributed Representation and Inference of States
38
2.3.1
Impact of Choice of Representation
38
2.3.2
Design Desiderata in Distributed Tracking
42
2.4
Tracking Multiple Objects
45
2.4.1
State-Space Decomposition
45
2.4.2
Data Association
48
2.5
Sensor Models
51
2.6
Performance Comparison and Metrics
58
2.7
Summary
61
■P Networking Sensors
63
3.1
Key Assumptions
63
3.2
Medium Access Control
65
3.2.1
The
S
-МАС
Protocol
66
3.2.2
IEEE
802.15.4
Standard and ZigBee
67
3.3
General Issues
68
4
3.4 Geographie, Energy-
A ware
Routing 70
3.4.1 Unicast Geographie Routing 72
3.4.2 Routing
on a Curve
81
3.4.3
Energy-Minimizing Broadcast
83
3.4.4
Energy-Aware Routing to a Region
87
3.5
Attribute-Based Routing
91
3.5.1 Directed Diffusion
92
3.5.2
Rumor Routing
97
3.5.3
Geographic Hash Tables
99
3.6
Summary
101
Infrastructure Establishment
103
4.1
Topology Control
103
4.2
Clustering
106
4.3
Time Synchronization
107
4.3.1
Clocks and Communication Delays
109
4.3.2
Interval Methods 111
4.3.3
Reference Broadcasts
115
4.4
Localization and Localization Services
117
4.4.1
Ranging Techniques
119
4.4.2
Range-Based Localization Algorithms
120
4.4.3
Other Localization Algorithms
125
4.4.4
Location Services
127
4.5
Summary
132
s
Sensor
Tasking and Control
135
5.1
Task-Driven Sensing
136
5.2
Roles of Sensor Nodes and Utilities
138
5.3
Information-Based Sensor Tasking
142
5.3.1
Sensor Selection
142
S3.2
IDSQ: Information-Driven Sensor Querying
147
5.3.3
Cluster Leader-Based Protocol
152
5.3.4
Sensor Tasking in Tracking Relations
162
5.4
Joint Routing and Information Aggregation
167
5.4.1
Moving Center of Aggregation
168
5.4.2
Multistep Information-Directed Routing
174
5.4.3
Sensor Group Management
179
5.4.4
Case Study: Sensing Global Phenomena
185
5.5
Summary
187
Sensor Network Databases
189
6.1
Sensor Database Challenges
192
6.2
Querying the Physical Environment
195
6.3
Query Interfaces
197
6.3.1
Cougar Sensor Database and Abstract Data Types
198
6.3.2
Probabilistic Queries
199
6.4
High-Level Database Organization
200
6.5
In-Network Aggregation
203
6.5.1
Query Propagation and Aggregation
203
6.5.2
TinyDB Query Processing
205
6.5.3
Query Processing Scheduling and Optimization
207
6.6
Data-Centric Storage
211
6.7
Data Indices and Range Queries
213
6.7.1
One-Dimensional Indices
215
6.7.2
Multidimensional Indices for Orthogonal Range
Searching
217
6.7.3 Nonorthogonal
Range Searching
221
6.8
Distributed Hierarchical Aggregation
223
6.8.1
Multiresolution Summarization
224
6.8.2
Partitioning the Summaries
225
6.8.3
Fractional Cascading
227
6.8.4
Locality-Preserving Hashing
230
6.9
Temporal Data
232
6.9.1
Data Aging
233
6.9.2
Indexing Motion Data
234
6.10
Summary
236
Sensor Network Platforms and Tools
239
7.1
Sensor Node Hardware
240
7.1.1
Berkeley Motes
242
7.2
Sensor Network Programming Challenges
245
7.3
Node-Level Software Platforms
247
7.3.1
Operating System: TinyOS
248
7.3.2
Imperative
Language: nesC
252
7.3.3
Dataflow-Style Language: TinyGALS
260
7.4
Node-Level Simulators
266
7.4.1
The ns-2 Simulator and its Sensor Network
Extensions
269
7.4.2
The Simulator TOSSIM
271
5.
S
Programming Beyond Individual Nodes: State-Centric
Programming
272
7.5.1
Collaboration Groups
274
7.5.2
PIECES: A State-Centric Design Framework
278
7.5.3
Multitarget Tracking Problem Revisited
282
7.6
Summary
287
Applications and Future Directions
291
8.1
A Summary of the Book
291
8.2
Emerging Applications
294
8.3
Future Research Directions
301
8.3.1
Secure Embedded Systems
301
8.3.2
Programming Models and Embedded Operating
Systems
301
8.3.3
Management of Collaborative Groups
302
8.3.4
Lightweight Signal Processing
303
8.3.5
Networks of High-Data-Rate Sensors
303
8.3.6
Google® for the Physical World
304
8.3.7
Closing the Loop with Actuators
305
8.3.8
Distributed Information Architecture
305
8.4
Conclusion
306
|
| adam_txt |
Contents
Preface
xiii
Introduction
1
1.1
Unique
Constraints and
Challenges
2
1.2
Advantages of Sensor
Networks
6
1.2.1
Energy Advantage
7
1.2.2
Detection Advantage
8
1.3
Sensor Network Applications
9
13.1
Habitat Monitoring
10
1.3.2
Tracking Chemical Plumes
12
1.3.3
Smart Transportation
13
1.4
Collaborative Processing
16
1.5
Key Definitions of Sensor Networks
17
1.6
The Rest of the Book
20
2
Contents
Canonical Problem: Localization and Tracking
23
2.1
A Tracking Scenario
25
2.2
Problem Formulation
27
2.2.1
Sensing Model
28
2.2.2
Collaborative Localization
30
2.2.3
Bayesian State Estimation
32
2.3
Distributed Representation and Inference of States
38
2.3.1
Impact of Choice of Representation
38
2.3.2
Design Desiderata in Distributed Tracking
42
2.4
Tracking Multiple Objects
45
2.4.1
State-Space Decomposition
45
2.4.2
Data Association
48
2.5
Sensor Models
51
2.6
Performance Comparison and Metrics
58
2.7
Summary
61
■P Networking Sensors
63
3.1
Key Assumptions
63
3.2
Medium Access Control
65
3.2.1
The
S
-МАС
Protocol
66
3.2.2
IEEE
802.15.4
Standard and ZigBee
67
3.3
General Issues
68
4
3.4 Geographie, Energy-
A ware
Routing 70
3.4.1 Unicast Geographie Routing 72
3.4.2 Routing
on a Curve
81
3.4.3
Energy-Minimizing Broadcast
83
3.4.4
Energy-Aware Routing to a Region
87
3.5
Attribute-Based Routing
91
3.5.1 Directed Diffusion
92
3.5.2
Rumor Routing
97
3.5.3
Geographic Hash Tables
99
3.6
Summary
101
Infrastructure Establishment
103
4.1
Topology Control
103
4.2
Clustering
106
4.3
Time Synchronization
107
4.3.1
Clocks and Communication Delays
109
4.3.2
Interval Methods 111
4.3.3
Reference Broadcasts
115
4.4
Localization and Localization Services
117
4.4.1
Ranging Techniques
119
4.4.2
Range-Based Localization Algorithms
120
4.4.3
Other Localization Algorithms
125
4.4.4
Location Services
127
4.5
Summary
132
s
Sensor
Tasking and Control
135
5.1
Task-Driven Sensing
136
5.2
Roles of Sensor Nodes and Utilities
138
5.3
Information-Based Sensor Tasking
142
5.3.1
Sensor Selection
142
S3.2
IDSQ: Information-Driven Sensor Querying
147
5.3.3
Cluster Leader-Based Protocol
152
5.3.4
Sensor Tasking in Tracking Relations
162
5.4
Joint Routing and Information Aggregation
167
5.4.1
Moving Center of Aggregation
168
5.4.2
Multistep Information-Directed Routing
174
5.4.3
Sensor Group Management
179
5.4.4
Case Study: Sensing Global Phenomena
185
5.5
Summary
187
Sensor Network Databases
189
6.1
Sensor Database Challenges
192
6.2
Querying the Physical Environment
195
6.3
Query Interfaces
197
6.3.1
Cougar Sensor Database and Abstract Data Types
198
6.3.2
Probabilistic Queries
199
6.4
High-Level Database Organization
200
6.5
In-Network Aggregation
203
6.5.1
Query Propagation and Aggregation
203
6.5.2
TinyDB Query Processing
205
6.5.3
Query Processing Scheduling and Optimization
207
6.6
Data-Centric Storage
211
6.7
Data Indices and Range Queries
213
6.7.1
One-Dimensional Indices
215
6.7.2
Multidimensional Indices for Orthogonal Range
Searching
217
6.7.3 Nonorthogonal
Range Searching
221
6.8
Distributed Hierarchical Aggregation
223
6.8.1
Multiresolution Summarization
224
6.8.2
Partitioning the Summaries
225
6.8.3
Fractional Cascading
227
6.8.4
Locality-Preserving Hashing
230
6.9
Temporal Data
232
6.9.1
Data Aging
233
6.9.2
Indexing Motion Data
234
6.10
Summary
236
Sensor Network Platforms and Tools
239
7.1
Sensor Node Hardware
240
7.1.1
Berkeley Motes
242
7.2
Sensor Network Programming Challenges
245
7.3
Node-Level Software Platforms
247
7.3.1
Operating System: TinyOS
248
7.3.2
Imperative
Language: nesC
252
7.3.3
Dataflow-Style Language: TinyGALS
260
7.4
Node-Level Simulators
266
7.4.1
The ns-2 Simulator and its Sensor Network
Extensions
269
7.4.2
The Simulator TOSSIM
271
5.
S
Programming Beyond Individual Nodes: State-Centric
Programming
272
7.5.1
Collaboration Groups
274
7.5.2
PIECES: A State-Centric Design Framework
278
7.5.3
Multitarget Tracking Problem Revisited
282
7.6
Summary
287
Applications and Future Directions
291
8.1
A Summary of the Book
291
8.2
Emerging Applications
294
8.3
Future Research Directions
301
8.3.1
Secure Embedded Systems
301
8.3.2
Programming Models and Embedded Operating
Systems
301
8.3.3
Management of Collaborative Groups
302
8.3.4
Lightweight Signal Processing
303
8.3.5
Networks of High-Data-Rate Sensors
303
8.3.6
Google® for the Physical World
304
8.3.7
Closing the Loop with Actuators
305
8.3.8
Distributed Information Architecture
305
8.4
Conclusion
306 |
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| id | DE-604.BV021611699 |
| illustrated | Illustrated |
| index_date | 2024-07-02T14:50:50Z |
| indexdate | 2024-07-09T20:39:52Z |
| institution | BVB |
| isbn | 1558609148 9781558609143 |
| language | English |
| lccn | 2004301905 |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-014826904 |
| oclc_num | 491669943 |
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| owner | DE-20 DE-91 DE-BY-TUM DE-739 |
| owner_facet | DE-20 DE-91 DE-BY-TUM DE-739 |
| physical | XVII, 358 S. Ill., graph. Darst. 25 cm |
| publishDate | 2004 |
| publishDateSearch | 2004 |
| publishDateSort | 2004 |
| publisher | Elsevier |
| record_format | marc |
| series2 | The Morgan Kaufmann series in networking |
| spelling | Zhao, Feng Verfasser aut Wireless sensor networks an information processing approach Feng Zhao ; Leonidas J. Guibas Amsterdam [u.a.] Elsevier 2004 XVII, 358 S. Ill., graph. Darst. 25 cm txt rdacontent n rdamedia nc rdacarrier The Morgan Kaufmann series in networking Includes bibliographical references (p. 323-345) and index Capteurs (technologie) ram Réseaux locaux sans fil ram Systèmes de communication sans fil ram Sensor networks Wireless LANs Mobilfunk (DE-588)4170280-3 gnd rswk-swf Mobilfunk (DE-588)4170280-3 s DE-604 Guibas, Leonidas J. Sonstige oth http://www.loc.gov/catdir/toc/els051/2004301905.html Table of contents http://www.loc.gov/catdir/description/els051/2004301905.html Publisher description Digitalisierung UB Passau application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014826904&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Zhao, Feng Wireless sensor networks an information processing approach Capteurs (technologie) ram Réseaux locaux sans fil ram Systèmes de communication sans fil ram Sensor networks Wireless LANs Mobilfunk (DE-588)4170280-3 gnd |
| subject_GND | (DE-588)4170280-3 |
| title | Wireless sensor networks an information processing approach |
| title_auth | Wireless sensor networks an information processing approach |
| title_exact_search | Wireless sensor networks an information processing approach |
| title_exact_search_txtP | Wireless sensor networks an information processing approach |
| title_full | Wireless sensor networks an information processing approach Feng Zhao ; Leonidas J. Guibas |
| title_fullStr | Wireless sensor networks an information processing approach Feng Zhao ; Leonidas J. Guibas |
| title_full_unstemmed | Wireless sensor networks an information processing approach Feng Zhao ; Leonidas J. Guibas |
| title_short | Wireless sensor networks |
| title_sort | wireless sensor networks an information processing approach |
| title_sub | an information processing approach |
| topic | Capteurs (technologie) ram Réseaux locaux sans fil ram Systèmes de communication sans fil ram Sensor networks Wireless LANs Mobilfunk (DE-588)4170280-3 gnd |
| topic_facet | Capteurs (technologie) Réseaux locaux sans fil Systèmes de communication sans fil Sensor networks Wireless LANs Mobilfunk |
| url | http://www.loc.gov/catdir/toc/els051/2004301905.html http://www.loc.gov/catdir/description/els051/2004301905.html http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014826904&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT zhaofeng wirelesssensornetworksaninformationprocessingapproach AT guibasleonidasj wirelesssensornetworksaninformationprocessingapproach |