James Aspnes, Christian Scheideler, Anish Arora, Samuel Madden9783540730897, 3540730893
The 27 revised full papers presented were carefully reviewed and selected from 71 submissions. The papers class in three tracks covering the areas of algorithms, applications, and systems, thus bridging the gap between theory and practice and between the broader field of distributed computing and the specific issues arising in sensor networks and related systems.
Table of contents :
Title……Page 3
Preface……Page 5
Organization……Page 7
Table of Contents……Page 11
Introduction……Page 14
Virtual Vision……Page 15
Distributed Control in Camera Sensor Networks……Page 16
Related Work……Page 17
Local Vision Routines……Page 19
Camera Node Behaviors……Page 20
Sensor Network Model……Page 21
Coalition Formation……Page 22
Conflict Resolution……Page 23
Node Failures and Communication Errors……Page 25
Computing Camera Node Relevance……Page 27
Results……Page 28
Discussion……Page 30
Conclusion……Page 31
Introduction……Page 34
System Models and Assumptions……Page 35
The Baseline Approach……Page 37
Enabling Privilege Delegation……Page 39
Enabling Efficient Broadcast Query……Page 41
Simulation Evaluation……Page 45
Related Work……Page 46
Conclusion and Open Problems……Page 47
Introduction……Page 49
Spatial Complexity of Wireless Channels……Page 51
Greedy Forwarding Based on ETX-Distance……Page 52
Virtual Distance Based Greedy Forwarding……Page 53
ETX Embedding……Page 54
Sample a Wireless Sensor Network with Beacons……Page 56
Performance Evaluation……Page 57
Evaluate the ETX-Embedding in TOSSIM……Page 58
Related Work……Page 59
Conclusion……Page 60
Introduction……Page 63
Packet Reliability v.s. Event Throughput……Page 65
Hop-by-Hop Recovery Based on Out-of-Sequence Mechanism……Page 66
Sink Centric Transport Protocol……Page 67
Packet Loss Detection and Notification……Page 68
Packet Retransmission……Page 69
Performance Evaluation……Page 70
Impact of Packet Inject Rate……Page 71
Impact of the Hop Distances……Page 73
Related Work……Page 74
Conclusion……Page 75
Introduction……Page 77
Related Work……Page 79
Alarm-System Scenario……Page 80
MAC Protocol……Page 81
Algorithms……Page 82
Alarm Forwarding……Page 83
Node Status Observation……Page 84
Startup……Page 85
Analytical……Page 86
Simulation……Page 88
Conclusions……Page 92
Introduction……Page 95
Motivation……Page 97
Related Work……Page 98
Description……Page 99
Theoretic Framework……Page 100
Boolean Model……Page 101
Engineering Ramifications……Page 102
Experimental Results……Page 103
Proof of Theorem 1……Page 105
Introduction……Page 109
Overview of MGDL Algorithm……Page 111
Local Map Computation……Page 113
Transformation Procedure……Page 114
Mobile Measurement Techniques……Page 115
Simulation Configuration……Page 117
Localization Accuracy……Page 119
Communication Overhead……Page 120
References……Page 121
Introduction……Page 123
Homogeneous Application Nodes……Page 126
Heterogeneous Application Nodes……Page 131
Heterogeneous Small Sensors……Page 132
Performance Studies……Page 134
Conclusion……Page 135
Introduction……Page 137
Preliminaries……Page 138
Related Work……Page 139
Centralized Algorithms……Page 140
One-Hop Approximation……Page 142
Multi-hop Approximation……Page 145
Experimental Results……Page 147
Scalability……Page 148
Network Dynamics……Page 151
Conclusion and Outlook……Page 152
Introduction……Page 155
Related Work……Page 157
Scope of the Fault Diagnosis Tool……Page 159
Data Collection Component……Page 160
Data Analysis Component……Page 162
Case Study: EnviroTrack……Page 163
Failure of the Tracking Protocol……Page 164
Failure Diagnosis Scenario……Page 165
Interpretation of the Rules……Page 166
Conclusion……Page 167
Introduction……Page 171
Services……Page 172
Architecture……Page 173
Query Processing……Page 174
Implementation……Page 176
Experimental Results……Page 178
Single Sensor Network……Page 179
Multiple Sensor Networks……Page 182
Related Work……Page 184
Conclusion……Page 185
Introduction……Page 187
System Overview……Page 189
Semantic Model of Data Sources and PEs……Page 190
Descriptions of Data Sources……Page 191
Descriptions of PEs……Page 193
Semantic Composition of Applications……Page 194
Connecting a Stream to a PE……Page 195
Automatic Composition of Applications……Page 196
Experiments……Page 197
Related Work……Page 199
Conclusion……Page 200
Introduction……Page 202
Programming Model……Page 204
Runtime System……Page 205
Compilation of Data-Driven Macroprograms: Overview……Page 206
Compilation Framework……Page 208
Compilation Modules……Page 209
Demonstration……Page 212
Discussion……Page 214
Concluding Remarks……Page 216
Introduction……Page 218
Deployment Support Network (DSN)……Page 220
Packet Decoder……Page 221
Data Stream Processor……Page 222
Case Study: Data Gathering Applications……Page 223
Problems and Indicators……Page 224
Application-Specific Operators……Page 225
Operator Graph……Page 227
Evaluation……Page 229
Related Work……Page 232
Conclusions……Page 233
Introduction……Page 236
Related Work……Page 237
Bayesian Classifier Method……Page 238
A Method Based on the Statistics of Differences Between Sensor Measurements……Page 240
Statistical Inference……Page 241
Statistical Anomalies: Error and Event Detection……Page 244
Inference of Missing Readings……Page 245
Application to Ecological Data from Sevilleta LTER Site……Page 246
Discussion and Outlook……Page 249
Introduction……Page 253
Processing at Sensors……Page 255
Processing at Fusion Center……Page 259
Performance Analysis and Results……Page 263
Conclusions and Future Work……Page 264
Introduction……Page 266
CORIE Data Assimilation Framework……Page 269
Problem Formulation……Page 270
Sensor Selection Using Genetic Algorithm……Page 272
Experimental Results……Page 273
Experimental Design……Page 274
Results and Analysis……Page 275
Related Work……Page 276
Future Work……Page 277
Conclusion……Page 278
Introduction……Page 280
The Data Salmon Protocol……Page 283
The Greedy Data Salmon Protocol……Page 284
Proof of Optimality……Page 285
Simulation Results……Page 287
Discussion……Page 290
Concluding Remarks……Page 291
Introduction……Page 294
System Model……Page 296
Push and Pull Model……Page 297
Formulation of the Optimization Problem……Page 299
Theoretical Analysis……Page 300
Optimal Diamond Size……Page 301
Push Scope Verification……Page 302
Dynamic Balancing of Push and Pull……Page 303
Traffic Network Simulations……Page 304
Simulation Results……Page 305
Conclusions……Page 306
Introduction……Page 308
Preliminaries and Problem Formulation……Page 310
Single-Sensor Fields……Page 311
Multiple-Sensor Fields……Page 314
Defining Steiner Points……Page 315
Description and Analysis of the Algorithm……Page 317
Improving the Running Time……Page 319
Conclusion……Page 320
Introduction……Page 322
Model……Page 324
Geometric Preprocessing……Page 325
Assigning Probabilities in a Graph……Page 326
Assigning Probabilities in Continuous Space……Page 328
Algorithm……Page 329
Deterministic Algorithm……Page 330
Simulation Experiments……Page 331
Conclusions and Further Work……Page 333
Introduction……Page 337
Overview and Fundamentals……Page 339
Hilbert Space Representation……Page 341
Primary Subspace……Page 342
Sensor Selection……Page 343
Greedy Algorithm……Page 344
Evaluation……Page 346
References……Page 350
Introduction……Page 351
System Model……Page 353
Total Energy Minimization for Collaborative Relaying with Perfect CSI……Page 354
Optimal Quantization for Optimal Collaborative Relaying……Page 355
Preliminaries……Page 356
QBS and QBR: Independent Basestation-Source and Basestation-Relay Quantization Algorithms……Page 357
Algorithm $QBS(k_s)$……Page 358
Joint Source/Relay Quantization……Page 359
2-Factor Approximation for Joint Quantization……Page 360
Fully Polynomial Approximation Scheme……Page 361
Conclusions……Page 365
Introduction……Page 367
Motivation……Page 369
Problem Formulation……Page 370
Group Merging……Page 372
Performance Evaluation……Page 374
Under Ideal Radio Propagation Model……Page 375
Under Irregular Radio Propagation Model……Page 377
Related Work……Page 378
Conclusion……Page 379
Introduction……Page 381
An Overview of the $DOSA$ Approach……Page 382
LMAC: A Lightweight Medium Access Control Protocol……Page 383
$DOSA:$ A Distributed and Self-organizing Scheduling Algorithm……Page 384
Dependency of $DOSA$ on LMAC……Page 385
General Operation of $DOSA$……Page 386
Performance of $DOSA$……Page 390
Coping with a Dead Node……Page 391
Coping with a New Node……Page 392
Details of Implementation and Results……Page 395
Related Work……Page 397
Conclusion and Future Work……Page 398
Introduction……Page 399
Motivating Application……Page 400
COMPASS Overview……Page 401
Design Principles……Page 402
Contention-Based Protocols……Page 403
Schedule-Based Protocols……Page 404
Medium Access Scheduling in a Hierarchy……Page 405
Intra-cluster Scheduling……Page 407
Evaluation……Page 411
Conclusions and Future Work……Page 414
Introduction……Page 417
Our Contribution……Page 419
Related Work……Page 420
A Naive, Brute-Force Algorithm……Page 421
Small Synopsis of the Network Topology……Page 422
Faster $O(1)$-Approximations……Page 424
Simple, Distributed Algorithms with Good Performance……Page 427
$(1+epsilon)$-Approximation with Running Time Polynomial in $k$ (and $1/epsilon$) ?……Page 428
Author Index……Page 430
Reviews
There are no reviews yet.