Real-time wireless sensor-actuator network for cyber-physical systems

318 Pages·2014·7.75 MB·English

Washington University in St. Louis
School of Engineering and Applied Science
Department of Computer Science and Engineering
Dissertation Examination Committee:
Chenyang Lu, Chair
Kunal Agrawal
Yixin Chen
Christopher Gill
Humberto Gonzalez
Jie Liu
Real-Time Wireless Sensor-Actuator Networks for Cyber-Physical Systems
by
Abusayeed Saifullah
A dissertation presented to the Graduate School of Arts and Sciences
of Washington University in partial fulfillment of the
requirements for the degree of
Doctor of Philosophy
December 2013
Saint Louis, Missouri
(cid:13)c 2013, Abusayeed Saifullah
Contents
List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . viii
List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xi
Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xii
Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiv
1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
2 Real-Time Wireless: Dynamic Scheduling . . . . . . . . . . . . . . . . . . . 3
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
2.2 WirelessHART Network Model . . . . . . . . . . . . . . . . . . . . . . . . . 5
2.3 Problem Formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.4 Necessary Condition for Schedulability . . . . . . . . . . . . . . . . . . . . . 9
2.5 Optimal Branch-and-Bound Scheduling . . . . . . . . . . . . . . . . . . . . . 12
2.6 Conflict-aware Least Laxity First . . . . . . . . . . . . . . . . . . . . . . . . 14
2.7 Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
2.7.1 Simulations with Random Topologies . . . . . . . . . . . . . . . . . . 19
2.7.2 Simulations with Testbed Topologies . . . . . . . . . . . . . . . . . . 22
2.8 Related Works . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
2.9 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
3 Real-Time Wireless: Delay Analysis for Fixed Priority Scheduling . . . 26
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
3.2 Related Works . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
3.3 Network Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
3.4 End-to-End Scheduling Problem . . . . . . . . . . . . . . . . . . . . . . . . . 31
3.5 End-to-end Delay Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
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3.5.1 Delay due to Channel Contention . . . . . . . . . . . . . . . . . . . . 34
3.5.2 Delay due to Transmission Conflicts . . . . . . . . . . . . . . . . . . . 37
3.5.3 A Tighter Bound on Conflict Delay . . . . . . . . . . . . . . . . . . . 40
3.5.4 End-to-End Delay Bound . . . . . . . . . . . . . . . . . . . . . . . . 44
3.6 Delay Analysis in Polynomial Time . . . . . . . . . . . . . . . . . . . . . . . 48
3.7 Extending to Graph Routing Model . . . . . . . . . . . . . . . . . . . . . . . 49
3.8 Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
3.8.1 Simulation Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
3.8.2 Simulations with Testbed Topologies . . . . . . . . . . . . . . . . . . 54
3.8.3 Simulations with Random Topologies . . . . . . . . . . . . . . . . . . 57
3.9 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
4 Real-Time Wireless: Delay Analysis for Reliable Graph Routing. . . . . 60
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
4.2 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
4.3 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
4.3.1 Network Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
4.3.2 Flow Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
4.4 Fixed Priority Scheduling . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
4.5 Delay Analysis under Reliable Graph Routing . . . . . . . . . . . . . . . . . 69
4.5.1 Problem Formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
4.5.2 Transmission Conflict Delay under Graph Routing . . . . . . . . . . . 70
4.5.3 Channel Contention Delay under Graph Routing . . . . . . . . . . . 75
4.5.4 End-to-End Delay Bound . . . . . . . . . . . . . . . . . . . . . . . . 78
4.6 A Probabilistic End-to-End Delay Analysis . . . . . . . . . . . . . . . . . . . 79
4.7 Experiment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
4.7.1 Testbed Experiment . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
4.7.2 Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
4.8 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
5 Real-Time Wireless: Priority Assignment for Fixed Priority Scheduling 88
5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
5.2 WirelessHART Network Model . . . . . . . . . . . . . . . . . . . . . . . . . 90
5.3 Problem Definition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
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5.4 End-to-End Delay Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
5.4.1 Class-1 Schedulability Test . . . . . . . . . . . . . . . . . . . . . . . . 94
5.4.2 Class-2 Schedulability Test . . . . . . . . . . . . . . . . . . . . . . . . 96
5.5 Priority Assignment Using Local Search . . . . . . . . . . . . . . . . . . . . 96
5.5.1 Upper Bound of Worst Case End-to-End Delay . . . . . . . . . . . . 98
5.5.2 Lower Bound of Worst Case End-to-End Delay . . . . . . . . . . . . 101
5.5.3 Local Search Framework . . . . . . . . . . . . . . . . . . . . . . . . . 103
5.5.4 Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106
5.6 Priority Assignment Using Heuristic Search . . . . . . . . . . . . . . . . . . . 107
5.7 Performance Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108
5.7.1 Simulations with Testbed Topologies . . . . . . . . . . . . . . . . . . 109
5.7.2 Simulations with Random Topologies . . . . . . . . . . . . . . . . . . 111
5.8 Related Works . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
5.9 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
6 Near Optimal Rate Selection for Wireless Control Systems . . . . . . . . 115
6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116
6.2 Related Works . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118
6.3 Control Network Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120
6.4 Control Loop Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121
6.5 Formulation of the Rate Selection Problem . . . . . . . . . . . . . . . . . . . 123
6.6 Subgradient Method for Rate Selection . . . . . . . . . . . . . . . . . . . . . 125
6.7 Greedy Heuristic for Rate Selection . . . . . . . . . . . . . . . . . . . . . . . 127
6.8 Rate Selection Using a penalty approach with simulated annealing . . . . . . 129
6.9 Rate Selection Through Convex Optimization . . . . . . . . . . . . . . . . . 131
6.9.1 Gradient Descent Method . . . . . . . . . . . . . . . . . . . . . . . . 136
6.9.2 Interior Point Method . . . . . . . . . . . . . . . . . . . . . . . . . . 137
6.10 Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138
6.10.1 Simulation Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139
6.10.2 Performance Study of Four Methods . . . . . . . . . . . . . . . . . . 140
6.10.3 SA based Constant Factor Penalty Method Versus Adaptive Penalty
Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144
6.10.4 Evaluating the Interior Point Method . . . . . . . . . . . . . . . . . . 145
6.11 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147
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7 Distributed Channel Allocation Protocols for Wireless Sensor Networks 150
7.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151
7.2 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153
7.3 Network Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155
7.4 Problem Formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 156
7.5 Interference-free Channel Allocation . . . . . . . . . . . . . . . . . . . . . . . 159
7.5.1 Receiver-based Channel Allocation . . . . . . . . . . . . . . . . . . . 159
7.5.2 Link-based Channel Allocation . . . . . . . . . . . . . . . . . . . . . 162
7.6 MinMax Channel Allocation . . . . . . . . . . . . . . . . . . . . . . . . . . . 165
7.7 Distributed Link Scheduling . . . . . . . . . . . . . . . . . . . . . . . . . . . 168
7.8 Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170
7.8.1 Interference-free Channel Allocation . . . . . . . . . . . . . . . . . . . 171
7.8.2 MinMax Channel Allocation . . . . . . . . . . . . . . . . . . . . . . . 172
7.8.3 Latency under MinMax Channel Allocation . . . . . . . . . . . . . . 174
7.8.4 Channel Allocation Message Overhead . . . . . . . . . . . . . . . . . 176
7.9 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177
8 CapNet: A Real-Time Wireless Management Network for Data Center
Power Capping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178
8.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178
8.2 The Case for Wireless DCM (CapNet) . . . . . . . . . . . . . . . . . . . . . 181
8.2.1 Cost Comparison with Wired DCM . . . . . . . . . . . . . . . . . . . 181
8.2.2 Choice of Wireless - IEEE 802.15.4 . . . . . . . . . . . . . . . . . . . 182
8.2.3 Radio Environment inside Racks . . . . . . . . . . . . . . . . . . . . 182
8.3 CapNet Design Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 185
8.3.1 The Power Capping Problem . . . . . . . . . . . . . . . . . . . . . . 185
8.3.2 Power Capping over Wireless DCM . . . . . . . . . . . . . . . . . . . 187
8.3.3 A Naive Periodic Protocol . . . . . . . . . . . . . . . . . . . . . . . . 188
8.3.4 Event-Driven CapNet . . . . . . . . . . . . . . . . . . . . . . . . . . . 188
8.4 Power Capping Protocol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 189
8.4.1 Detection Phase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191
8.4.2 Aggregation Phase . . . . . . . . . . . . . . . . . . . . . . . . . . . . 192
8.4.3 Control Phase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 192
8.4.4 Latency Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193
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8.5 Experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 194
8.5.1 Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 194
8.5.2 Workload Traces . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195
8.5.3 Experimental Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195
8.5.4 Power Peak Analysis of Data Centers . . . . . . . . . . . . . . . . . . 197
8.5.5 Power Capping Results . . . . . . . . . . . . . . . . . . . . . . . . . . 200
8.6 Discussions and Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . 209
8.7 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209
8.8 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 210
9 Multi-core Real-Time Scheduling for Generalized Parallel Task Models 211
9.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 212
9.2 Parallel Synchronous Task Model . . . . . . . . . . . . . . . . . . . . . . . . 214
9.3 Task Decomposition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 217
9.3.1 Terminology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 217
9.3.2 Decomposition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 218
9.3.3 Density Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227
9.4 Global EDF Scheduling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 229
9.5 Partitioned Deadline Monotonic Scheduling . . . . . . . . . . . . . . . . . . 232
9.5.1 FBB-FFD based Partitioned DM Algorithm for Decomposed Tasks . 232
9.5.2 Analysis for the FBB-FFD based Partitioned DM Algorithm . . . . . 235
9.6 Generalizing to a Unit-node DAG Task Model . . . . . . . . . . . . . . . . . 239
9.7 Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 240
9.7.1 Task Generation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 240
9.7.2 Simulation Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 241
9.7.3 Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 242
9.8 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 247
9.9 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 249
10 Parallel Real-Time Scheduling of DAGs . . . . . . . . . . . . . . . . . . . . 250
10.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 251
10.2 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 253
10.3 Parallel Task Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255
10.4 Task Decomposition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 256
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10.4.1 Terminology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 258
10.4.2 Decomposition Algorithm . . . . . . . . . . . . . . . . . . . . . . . . 259
10.4.3 Density Analysis after Decomposition . . . . . . . . . . . . . . . . . . 268
10.4.4 Implementation Considerations . . . . . . . . . . . . . . . . . . . . . 270
10.5 Preemptive EDF Scheduling . . . . . . . . . . . . . . . . . . . . . . . . . . . 271
10.6 Non-Preemptive EDF Scheduling . . . . . . . . . . . . . . . . . . . . . . . . 274
10.7 Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 278
10.7.1 Task and Task Set Generation . . . . . . . . . . . . . . . . . . . . . . 278
10.7.2 Experimental Methodology . . . . . . . . . . . . . . . . . . . . . . . . 280
10.7.3 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 281
10.8 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 285
11 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 286
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 289
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List of Figures
2.1 Reduction from edge-coloring . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.2 Scheduling with the B&B and C-LLF under varying network sizes . . . . . . 17
2.3 Schedulable ratio of C-LLF and baselines . . . . . . . . . . . . . . . . . . . . 19
2.4 Comparison under varying network sizes . . . . . . . . . . . . . . . . . . . . 20
2.5 Execution time of C-LLF under varying number of routes (γ) . . . . . . . . . 21
2.6 Scheduling by C-LLF under varying network sizes . . . . . . . . . . . . . . . 22
2.7 The testbed topology with a transmission power of 0 dBm . . . . . . . . . . 23
2.8 Scheduling with the B&B, C-LLF, and baselines under varying number of
sources and destinations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
2.9 Schedulable ratio under different power level . . . . . . . . . . . . . . . . . . 24
3.1 An example when F can be delayed by F . . . . . . . . . . . . . . . . . . . 39
k i
3.2 Schedulability without retransmission on testbed topology . . . . . . . . . . 51
3.3 Pessimism ratio without retransmission on testbed topology . . . . . . . . . 53
3.4 Schedulability with retransmission on testbed topology . . . . . . . . . . . . 55
3.5 Pessimism ratio with retransmission on testbed topology . . . . . . . . . . . 57
3.6 Schedulability with retransmission and redundant routes on testbed topology 58
3.7 Schedulability on random topology . . . . . . . . . . . . . . . . . . . . . . . 58
3.8 Schedulability with retransmission and redundant routes on random topology 59
4.1 Routing in the sensing phase of F and F (the numbers beside each link
i h
indicate the time slots allocated to the link.) . . . . . . . . . . . . . . . . . . 68
4.2 Testbed topology (access points are colored in blue) . . . . . . . . . . . . . . 81
4.3 Delay and reliability on testbed . . . . . . . . . . . . . . . . . . . . . . . . . 81
4.4 Worst case delay analysis performance in simulation . . . . . . . . . . . . . . 84
4.5 Acceptance rate under probabilistic delay bound . . . . . . . . . . . . . . . . 86
4.6 Pessimism ratio for 30 flows under probabilistic bound . . . . . . . . . . . . 86
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5.1 Priority assignment f at a node . . . . . . . . . . . . . . . . . . . . . . . . . 98
5.2 Performance under varying deadlines . . . . . . . . . . . . . . . . . . . . . . 110
5.3 Performance under varying number of sources and destinations . . . . . . . . 111
5.4 Performance under varying network sizes . . . . . . . . . . . . . . . . . . . . 112
6.1 Surface of the dual function in 6.6 . . . . . . . . . . . . . . . . . . . . . . . 127
6.2 End-to-end delay bounds on testbed topology . . . . . . . . . . . . . . . . . 134
6.3 Surface of the primal function of Problem in 6.8 . . . . . . . . . . . . . . . . 135
6.4 Testbed topology at transmission power of -5 dBm (the gateway is colored in
blue) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139
6.5 Performance comparison on topology at transmission power -5 dBm . . . . . 140
6.6 Performance comparison on topology at transmission power -3 dBm . . . . . 141
6.7 Performance comparison on topology at transmission power -1 dBm . . . . . 142
6.8 Performance comparison on topology at transmission power 0 dBm . . . . . 143
6.9 Performance comparison of Adaptive Vs Constant Penalty SA . . . . . . . . 144
6.10 Interior Point Method versus Gradient Method for Convex Optimization . . 146
6.11 Interior Point Method versus Adaptive Penalty Method . . . . . . . . . . . . 148
7.1 IC graph and receiver-based conflict graph . . . . . . . . . . . . . . . . . . . 160
7.2 Link-based channel allocation . . . . . . . . . . . . . . . . . . . . . . . . . . 163
7.3 Link-based conflict graph G of G . . . . . . . . . . . . . . . . . . . . . . . . 164
L
7.4 IC graph and schedule conflict graph . . . . . . . . . . . . . . . . . . . . . . 169
7.5 Channel allocation on testbed topologies to remove all interferences . . . . . 171
7.6 MinMax channel allocation on testbed topology with -5 dBm Tx power . . . 172
7.7 MinMax channel allocation on random topologies . . . . . . . . . . . . . . . 173
7.8 Network performance on testbed topology at -5 dBm . . . . . . . . . . . . . 174
7.9 Network performance on random topology of 400 sensor nodes . . . . . . . . 175
7.10 Comparison of message cost for channel allocation and one round of data
collection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 176
8.1 Mote placed in bottom sled . . . . . . . . . . . . . . . . . . . . . . . . . . . 183
8.2 Downward signal strength and PRR in bottom sled . . . . . . . . . . . . . . 184
8.3 The trip curve of Rockwell Allen-Bradley 1489-A circuit breaker at 40◦C [23].
X-axis is oversubscription magnitude. Y-axis is trip time. . . . . . . . . . . . 186
8.4 Wireless DCM architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187
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