distributed incremental data stream mining for wireless sensor network hakilo ahmed sabit

208 Pages·2013·2.4 MB·English

DISTRIBUTED INCREMENTAL DATA STREAM MINING FOR
WIRELESS SENSOR NETWORK

HAKILO AHMED SABIT

A thesis submitted to
Auckland University of Technology
in fulfilment of the requirements for the degree of
Doctor of Philosophy (PhD)

2013
School of Engineering
CONTENTS

1. INTRODUCTION ......................................................................................................................... 1
1.1. BACKGROUND TO THE RESEARCH ............................................................................................. 1
1.1.1. Association ........................................................................................................................... 2
1.1.2. Classification ......................................................................................................................... 2
1.1.3. Prediction ............................................................................................................................. 3
1.1.4. Sequential Patterns .............................................................................................................. 3
1.1.5. Clustering .............................................................................................................................. 3
1.1.6. Wireless Sensor Network Background .................................................................................. 4
1.2. MOTIVATION ............................................................................................................................. 5
1.3. RESEARCH PROBLEM ................................................................................................................. 6
1.4. CONTRIBUTIONS ....................................................................................................................... 7
1.5. OUTLINE OF THE THESIS ............................................................................................................ 8
1.6. PUBLICATIONS ........................................................................................................................... 9
1.7. CHAPTER SUMMARY ............................................................................................................... 10
2. LITERATURE REVIEW ................................................................................................................ 11
2.1. INTRODUCTION ....................................................................................................................... 11
2.2. WIRELESS SENSOR NETWORK INTRODUCTION ....................................................................... 11
2.2.1. Hardware Platform ............................................................................................................. 13
2.2.1.1. Sensor Energizing .....................................................................................................................13
2.2.1.2. Power Mode Settings ...............................................................................................................14
2.2.1.3. Optimal Transmission Power Setting .......................................................................................14
2.2.1.4. Duty Cycling .............................................................................................................................14
2.2.2. Operating System ............................................................................................................... 15
2.2.3. WSN Protocol Stack ............................................................................................................ 15
2.2.3.1. IEEE 802.15.4/ ZigBee ..............................................................................................................16
2.2.3.2. 6LoWPAN .................................................................................................................................17
2.2.4. Protocol Level Energy Conservation ................................................................................... 18
2.2.5. Application Level Energy Conservation ............................................................................... 19
2.3. DATA STREAM MINING............................................................................................................ 19
2.3.1. Frequent pattern mining .................................................................................................... 21
2.3.2. Classification Mining .......................................................................................................... 22
2.3.3. Outlier Detection ................................................................................................................ 23
2.3.4. Stream Clustering ............................................................................................................... 23
2.4. DISTRIBUTED TECHNIQUES FOR WSN DATA STREAM MINING ................................................ 24
2.5. CHAPTER SUMMARY ............................................................................................................... 28
ii
3. RESEARCH TOOLS AND MATERIALS .......................................................................................... 29
3.1. TRUETIME SIMULATOR ........................................................................................................... 29
3.1.1. The TrueTime Kernel ........................................................................................................... 31
3.1.1.1. Tasks ........................................................................................................................................33
3.1.1.2. Code Function ..........................................................................................................................34
3.1.1.3. Code Segments ........................................................................................................................34
3.1.1.4. Configuring Simulation ............................................................................................................35
3.1.1.4. Scheduling Hooks .....................................................................................................................35
3.1.1.5. Data Logging ............................................................................................................................36
3.1.1.6. Monitors ..................................................................................................................................36
3.1.2. The TrueTime Wireless Network ......................................................................................... 36
3.1.3. The TrueTime Battery ......................................................................................................... 37
3.1.4. Limitations of TrueTime ...................................................................................................... 39
3.2. TI’S CC2530 ZNP-MINI KIT ........................................................................................................ 39
3.2.1. CC2530................................................................................................................................ 39
3.2.2. MSP430F2274 ..................................................................................................................... 43
3.3. SHT15 – DIGITAL HUMIDITY SENSOR (RH&T) .......................................................................... 45
3.4. SEN-08942 WEATHER METER .................................................................................................. 47
3.5. CONCLUSION ........................................................................................................................... 49
4. DISTRIBUTED INCREMENTAL DATA STREAM MINING WIRELESS SENSOR NETWORK FRAMEWORK
50
4.1. INTRODUCTION ....................................................................................................................... 50
4.2. DISTRIBUTED INCREMENTAL DATA STREAM MINING ............................................................. 51
4.3. NETWORK ARCHITECTURE FOR DISTRIBUTED INCREMENTAL DATA STREAM MINING ........... 51
4.4. DISTRIBUTED INCREMENTAL DATA STREAM MINING FRAMEWORK ...................................... 53
4.4.1. Sensor Nodes Processing .................................................................................................... 53
4.4.2. Cluster Head Processing ..................................................................................................... 56
4.4.3. Sink Processing ................................................................................................................... 59
5. DEVELOPMENT OF SUBTRACTIVE FUZZY CLUSTER MEANS (SUBFCM) ALGORITHM .................... 60
5.1. CLUSTERING ............................................................................................................................ 60
5.2. DATA STREAM MINING ALGORITHM ....................................................................................... 61
5.3. SUBTRACTIVE CLUSTERING METHOD ...................................................................................... 62
5.4. FUZZY C-MEANS CLUSTERING ................................................................................................. 65
5.5. THE SUBFCM ALGORITHM ....................................................................................................... 68
5.6. IMPLEMENTATION OF SUBFCM .............................................................................................. 72
5.6.1. Computational Complexity of the SUBFCM Algorithm ....................................................... 76
5.6.1.1. Sensor node Computational Complexity .................................................................................77
5.6.1.2. Sensor node Communication Complexity ................................................................................78
5.6.1.3. Sensor node Energy Consumption ...........................................................................................78
5.6.1.4. Cluster Head Computational Complexity .................................................................................79
5.6.1.5. Cluster Head Communication Complexity ...............................................................................80
5.6.1.6. Cluster Head Energy Consumption ..........................................................................................80
5.7. DISCUSSION ............................................................................................................................. 80
6. MODELLING AND SIMULATION OF THE DISTRIBUTED INCREMENTAL DATA STREAM MINING
WSN 81
6.1. DATA STREAM ACQUISITION (SOURCES) ................................................................................. 81
6.2. WIRELESS SENSOR NODE MODEL ............................................................................................ 86
6.3. THE WIRELESS NETWORK MODEL ........................................................................................... 89
6.4. DATA STREAM MINING TASK MODELS .................................................................................... 90
iii
6.4.1. Sensor Nodes sub-task Model ............................................................................................ 91
6.4.2. Cluster Heads sub-task Model ............................................................................................ 96
6.4.3. The Sink sub-task Model ..................................................................................................... 99
6.5. SYSTEM MODEL SIMULATION ............................................................................................... 101
6.6. DISCUSSION ........................................................................................................................... 105
7. RESULTS AND ANALYSIS ......................................................................................................... 106
7.1. SIMULATION RESULTS ........................................................................................................... 106
7.2. SIMULATION SETUP ............................................................................................................... 106
7.3. SIMULATION ENVIRONMENT AND DATASETS ....................................................................... 107
7.4. SIMULATION AND ANALYSIS ................................................................................................. 107
7.5. SIMULATIONS 1 ..................................................................................................................... 108
7.5.1. One-Dimensional (1D) Stream Analysis ............................................................................ 108
7.5.2. Two-Dimensional (2D) Stream Analysis ............................................................................ 112
7.5.3. Three-Dimensional (3D) Stream Analysis ......................................................................... 116
7.5.4. Four-Dimensional (4D) Stream Analysis ........................................................................... 119
7.5.5. Stream Rate Analysis ........................................................................................................ 121
7.6. SIMULATIONS 2 ..................................................................................................................... 122
7.6.1. Uniform Cluster Density Analysis ...................................................................................... 123
7.6.2. Non-uniform Cluster Density Analysis .............................................................................. 128
7.7. SIMULATION 3 ....................................................................................................................... 129
7.7.1. Average Energy Consumption .......................................................................................... 129
7.7.2. Average Data Delivery Delay ............................................................................................ 133
7.7.3. Packet Delivery Ratio ........................................................................................................ 134
7.8. CONCLUSIONS ....................................................................................................................... 136
8. CASE STUDY: MICRO-SCALE FOREST FIRE WEATHER INDEX AND SENSOR NETWORK ............... 137
8.1. INTRODUCTION ..................................................................................................................... 137
8.2. FWI SYSTEM ........................................................................................................................... 138
8.2.1. Fine fuel moisture code (FFMC) ........................................................................................ 140
8.2.2. DUFF MOISTURE CODE (DMC) ......................................................................................................... 140
8.2.3. Drought Code (DC) ............................................................................................................ 141
8.2.4. Initial Spread Index(ISI) ..................................................................................................... 142
8.2.5. Buildup Index (BUI) ........................................................................................................... 142
8.2.6. Fire Weather Index (FWI) ................................................................................................. 143
8.3. LIMITATIONS OF THE STANDARD FWI SYSTEM ...................................................................... 145
8.4. THE MICRO-SCALE FWI SYSTEM ............................................................................................ 146
8.4.1. The Weather Sensor Nodes .............................................................................................. 147
8.4.2. Siting and Exposure of the Sensors ................................................................................... 149
8.5. THE FIRE WEATHER NETWORK .............................................................................................. 152
8.6. FWI INDICES PROCESSING ALGORITHM ................................................................................ 153
8.7. THE NODES TASK SUBDIVISION ............................................................................................. 154
8.8. THE MICRO-SCALE FWI SYSTEM DATA MODEL ......................................................................... 157
8.9. THE MICRO-SCALE FWI SYSTEM SIMULATION MODEL .............................................................. 158
8.10. SIMULATIONS AND RESULTS ................................................................................................. 161
8.10.1. Micro-scale FWI System Model Validation .................................................................. 161
8.10.2. End-to-End Delay ......................................................................................................... 166
8.10.3. Packet Loss .................................................................................................................. 167
8.10.4. Energy Consumption .................................................................................................... 168
8.11. CONCLUSIONS ....................................................................................................................... 169
iv
9. CONCLUSIONS AND FUTURE WORK ........................................................................................ 170
9.1. CONCLUSIONS ....................................................................................................................... 170
9.3. FUTURE WORK ...................................................................................................................... 173
9.3.1. LIMITATIONS ..................................................................................................................... 174
REFERENCES ................................................................................................................................... 175

v
Declaration

“I hereby declare that this submission is my own work and that, to the best of my
knowledge and belief, it contains no material previously published or written by
another person (except where explicitly defined in the acknowledgements), nor
material which to a substantial extent has been submitted for the award of any other
degree or diploma of a university or other institution of higher learning.”

Auckland, 2013

___________
Hakilo Sabit

vi
LIST OF FIGURES

Figure 3.1: TrueTime Block Library. ................................................................................ 31
Figure 3.2: The TrueTime Block Mask Dialog. ................................................................. 33
Figure 3.3: Code Segment. .............................................................................................. 34
Figure 3.4: The TrueTime Wireless Network Block mask dialog. .................................... 38
Figure 3.5: CC2530ZNP-Mini Kit. ..................................................................................... 40
Figure 3.6: CC2530ZNP board. ........................................................................................ 41
Figure 3.7: CC2530 ZNP Block Diagram. .......................................................................... 42
Figure 3.8: MSP430F2274 Functional Block Diagram. .................................................... 45
Figure 3.9: SHT15 Digital Humidity Sensor. .................................................................... 47
Figure 3.10: SEN-08942 Weather meter. ........................................................................ 48
Figure 4.1: The hierarchical two-tiered WSN architecture for the distributed
incremental data stream mining framework. ................................................................. 52
Figure 4.2: Graphical depiction of data stream and sliding window. ............................. 55
Figure 5.1: The objective function minimization. ........................................................... 74
Figure 5.2: 2D classification of the data points from weather database. ....................... 75
Figure 5.3: 3D classification of the data points from weather database. ....................... 75
Figure 6.2: The sensor node data stream source model. ............................................... 83
Figure 6.1: Flow chart of the sensor data stream source process. ................................. 83
Figure 6.3: Flow chart of the cluster head data stream source process. ........................ 84
Figure 6.4: The TrueTime wireless sensor node model. ................................................. 87
Figure 6.5: The TrueTime cluster head node model. ...................................................... 88
Figure 6.6: The TrueTime sink node model. ................................................................... 88
Figure 6.7: The TrueTime Wireless Network Model. ...................................................... 90
vii
Figure 6.8: The sensor node sub-task model flowcharts. ............................................... 93
Figure 6.9: The cluster head sub-task model flowcharts. ............................................... 97
Figure 6.10: The sink sub-task model flowcharts. ........................................................ 100
Figure 6.11: The general distributed incremental data stream mining system model.103
Figure 6.12: Centralized flat multi-hop stream clustering architecture network. ........ 103
Figure 6.13: Centralized cluster-based stream clustering network. ............................. 104
Figure 7.1: Cluster heads first sliding window snapshots. ............................................ 110
Figure 7.2: The sliding windows combined to form the first stream set. ..................... 111
Figure 7.3: Cluster centers extracted during 144 simulation steps. ............................. 111
Figure 7.4: Average cluster deviations. ......................................................................... 112
Figure 7.5: Cluster heads first sliding windows snapshot. ............................................ 114
Figure 7.6: Stream sets and clusters from first simulation step. .................................. 114
Figure 7.7: Average cluster deviations with respect to K-Means for 2D streams. ....... 115
Figure 7.8: Average cluster deviations with respect to FCM for 2D streams. .............. 115
Figure 7.9: Cluster heads first sliding windows snapshot. ............................................ 117
Figure 7.10: Average cluster deviations with respect to K-Means for 3D streams. ..... 118
Figure 7.11: Average cluster deviations with respect to FCM for 3D streams. ............ 118
Figure 7.12: Average cluster deviations with respect to K-Means for 4D streams. ..... 119
Figure 7.13: Average cluster deviations with respect to FCM for 4D streams. ............ 120
Figure 7.14: Average cluster deviation variation with stream period. ......................... 121
Figure 7.15: Average cluster deviation with varying cluster densities at 1sec stream
period. ........................................................................................................................... 124
Figure 7.16: Average cluster deviation with varying cluster densities at 5sec stream
period. ........................................................................................................................... 125
Figure 7.17: Average cluster deviation with varying cluster densities at 10sec stream
period. ........................................................................................................................... 126
Figure 7.18: Average cluster deviation with varying cluster densities at 15sec stream
period. ........................................................................................................................... 127
Figure 7.19: Average cluster deviation with varying cluster densities at 20sec stream
period. ........................................................................................................................... 127
Figure 7.20: Average of cluster deviations for different stream periods. .................... 128
Figure 7.21: Average cluster deviation for non-uniform cluster density. ..................... 129
viii
Figure 7.22: Sensor nodes and cluster heads average energy consumption. .............. 131
Figure 7.23: Sensor nodes average energy consumption. ............................................ 132
Figure 7.24: cluster heads average energy consumption. ............................................ 132
Figure 7.25: Packet delivery delay variation with cluster density. ............................... 134
Figure 7.26: Packet delivery ratio of sensor node-to-cluster head. ............................. 135
Figure 7.27: packet delivery ratio of cluster head-to-sink. ........................................... 136
Figure 8.1: The general structure of the FWI system. .................................................. 144
Figure 8.2: Wireless sensor node architecture. ............................................................ 148
Figure 8.3: Wind speed and direction sensors siting and exposure. ............................ 150
Figure 8.4: The Micro-scale FWI system WSN architecture.......................................... 151
Figure 8.5: The fire weather network architecture. ..................................................... 153
Figure 8.6: Virtual clusters of fire hazard rating or intensity mapped onto the nodes
locations. ....................................................................................................................... 156
Figure 8.7: The stream of weather tuples. .................................................................... 157
Figure 8.8: The Micro-scale FWI system weather sensor node sub-model. ................. 159
Figure 8.9: The Micro-scale FWI system cluster head sub-model. ............................... 160
Figure 8.10: The Micro-scale FWI system sink sub-model. ........................................... 160
Figure 8.11: The Canterbury weather network map. ................................................... 163
Figure 8.12: The Micro-scale FWI system model representing the Canterbury weather
network. ........................................................................................................................ 163
Figure 8.13: Micro-scale vs Actual FFMC comparison. ................................................. 164
Figure 8.14: Micro-scale vs Actual DMC comparison. .................................................. 164
Figure 8.15: Micro-scale vs Actual DC comparison. ...................................................... 164
Figure 8.16: Micro-scale vs Actual ISI comparison. ....................................................... 165
Figure 8.17: Micro-scale vs Actual BUI comparison. ..................................................... 165
Figure 8.18: Micro-scale vs Actual FWI comparison. .................................................... 165
Figure 8.19: end-to-end delay of the model. ................................................................ 166
Figure 8.20: end-to-end delay of the model. ................................................................ 167
Figure 8.21: pacet loss performance. ........................................................................... 168
Figure 8.22: Remaining battery power of sensors and cluster heads. ......................... 169

ix
LIST OF TABLES

Table 3.1: Humidity conversion coefficients. .................................................................. 46
Table 3.2: Temperature conversion coefficients. ........................................................... 47
Table 5.1: Sample of weather database. ........................................................................ 73
Table 6.1: The TrueTime wireless network parameters setting. .................................... 90
Table 7.1: uniform cluster density setup. ..................................................................... 122
Table 7.2: non-uniform cluster density setup. .............................................................. 122
Table 8.1: Fire danger severity rating on FWI scale. ..................................................... 144
Table 8.2: The simulation model parameters settings. ................................................ 159

x