LMI-Based congestion control algorithms for wireless sensor networks

 Preface. 6                                                               

Chapter1- Congestion control approaches applied to wireless sensor networks  1

1-1- Introduction. 2

1-2- Congestion control schemes in wsns: an overview.. 6

1-2-1- Congestion detection. 6

1-2-2- Congestion notification. 9

1-2-3- Congestion mitigation. 10

1-2-3-1- Traffic control 11

1-2-3-2- Resource control 12

1-2-3-3- Traffic and resource control 13

1-2-3-4- Fairness-based congestion control 13

1-2-3-5- Priority- aware congestion control 13

1-2-3-6- End to end or hop by hop congestion control 13

1-2-3-7- Energy efficient congestion control 13

1-2-3-8- Reliability- based congestion control 14

1-2-3-9- Queue- assisted congestion control schemes. 14

1-2-3-10- Centralized or distributed congestion control 14

1-2-3-11- Generic or cross layer congestion control 14

1-2-3-12- Content-aware congestion control 14

1-2-3-13- Soft computing- based congestion control 15

1-2-3-13-1- Fuzzy logic- based congestion control 15

1-2-3-13-2- Games theory-based congestion control 16

1-2-3-13-3- Swarm intelligence- based congestion control 17

1-2-3-13-4- Learning automata- based congestion control 18

1-2-3-13-5- Machine learning- based congestion control 19

1-3- The evaluation metrics. 20

1-4- Key issues in congestion control in wsns. 22

1-5- Future directions. 23

Chapter 2- A distributed power control scheme for cellular networks in the presence of channel uncertainties  29

2-1-Introduction. 30

2-2- Radio channel with uncertainties. 31

2-2-1-Path loss. 31

2-2-2-Shadowing. 31

2-2-3- Rayleigh fading. 32

2-3- The existing DPC schemes. 32

2-4- The DPC scheme. 33

2-5- The concluding remarks in DPC.. 41

Chapter3- A predictive congestion control scheme in WSNs. 43

3-1-Introduction. 44

3-2- An overview of DPCC.. 45

3-3- The performance metrics. 47

3-4-The adaptive congestion control 48

3-4-1- Rate selection based on buffer occupancy. 48

3-4-2- Back-off interval selection. 52

3-4-2-1- Adaptive back-off interval selection. 54

3-4-2-2- Rate propagation. 58

3-4-3- Fair scheduling. 59

3-4-3-1- Dynamic weght adaptation. 60

3-4-3-2- Fairness and throughput guarantee. 60

3-5- The concluding remarks. 61

Chapter 4- Robust decentralized adaptive non-quadratic congestion control algorithm for a class of delayed networks. 63

4-1- Introduction. 64

4-2- Comparison of DPCC and RDANQCC.. 66

4-3- Preliminaries. 68

4-3-1- Model description. 68

4-3-3- Non-quadratic Lyapunov functions. 72

4-4- The main results. 72

4-4-1- The RDANQCC design. 73

4-4-2- The varying desired queue size. 79

4-4-3- The algorithm of RDANQCC in WSNS. 82

4-5- Performance analysis. 83

4-5-1- Performance analysis using MATLAB.. 84

4-5-2- Performance analysis using OPNET simulator 90

4-5-3- Performance analysis using TOSSIM simulator 91

4-6- The concluding remarks. 97

Chapter 5- Novel congestion control algorithms for a class of delayed networks  99

5-1- Introduction. 100

5-2- Comparison of DNCQLCC and DPCC.. 101

5-3- The main results. 102

5-4- Performance analysis. 110

5-4-1- Performance analysis using MATLAB.. 110

5-4-2- Performance analysis using OPNET simulator 114

5-4-3- Performance analysis using TOSSIM simulator 115

5-5- The concluding remarks. 120

Chapter 6- Lmi-based congestion control algorithms for a delayed network  121

6-1-Introduction. 122

6-2- Comparison of DPCC, RDANQCC and LCC.. 123

6-3- The main results. 124

6-4- Performance analysis. 129

6-4-1- Performance analysis using MATLAB.. 129

6-4-2- Performance analysis using OPNET simulator 132

6-4-3- Performance analysis using TOSSIM simulator 133

6-5- The concluding remarks. 137

Chapter7- Nonmonotonic-based congestion control schemes for a delayed nonlinear network  139

7-1-Introduction. 140

7-2- Comparison of DPCC, RDANQCC, DNCQLCC, LCC and ADNCQLCC   140

7-3- The main results. 142

7-4- Performance analysis. 150

7-4-1- Performance analysis using MATLAB.. 150

7-4-2- Performance analysis using OPNET simulator 153

7-4-3- Performance analysis using TOSSIM simulator 154

7-5- The concluding remarks. 158

References. 160

                                                                Appendix. 161

 

 

Preface

 

The purpose of this book is to initiate the newcomers into the congestion control issue of wireless sensor networks as one of the growing fields in networks. WSNs are a special category of wireless ad-hoc networks where their performance is highly affected by application, life time, storage capacity, processing power, topology changes, the communication medium and bandwidth. These limitations necessitate an effective data transport control considering quality of service, energy efficiency, and congestion control. Congestion is an important issue in wireless networks. Congestion in WSNs badly effects loss rate, channel quality, link utilization, number of retransmissions, traffic flow, network life time, delay, energy and throughput. Due to the dominant role of WSNs, more efficient congestion control algorithms are needed.

 

Chapter1 lays the information on congestion control approaches applied to wireless sensor networks. The chapter includes introduction and key issues in congestion detection, notification and mitigation where the congestion mitigation is divided in different categories. Finally, the evaluation metrics and the key issues regarding congestion control approaches applied to wireless sensor networks are presented and the future directions are detailed.

 

Chapter 2 addresses the distributed power control for cellular networks in the presence of channel uncertainties where the radio channel with uncertainties, the existing DPC schemes, the DPC algorithm and the concluding remarks in DPC are presented.

 

In Chapter 3, the predictive congestion control protocol for WSNs is summarized where an overview of DPCC, the performance metrics, the adaptive congestion control consisting of rate selection based on buffer occupancy, back-off interval selection and fair scheduling are detailed and finally the concluding remarks are presented.

 

Chapter 4 presents an overview of robust decentralized adaptive non-Quadratic congestion control algorithm for a class of delayed networks where it is first compared with DPCC, followed by some preliminaries in case of model description, the adaptive and predictive controller and non-quadratic Lyapunov functions. Afterwards, the main results are presented where the RDANQCC design, the varying desired queue length and the algorithm of RDANQCC in WSN are detailed. Thereafter, the performance analysis which is accomplished using different simulators and the concluding remarks are presented.

Chapter 5 details the novel congestion control algorithms for a class of delayed networks, namely, DCQLCC, DNCQLCC and DNCQLCC with guaranteed decay rate. First comparison of DNCQLCC and DPCC is presented, afterwards, the main results, performance analysis and the concluding remarks are given.

 

Chapter 6 details the LMI-based congestion control algorithms for a delayed network, namely LCC schemes. First the comparison of DPCC, RDANQCC and LCC is presented, afterwards, the main results, performance analysis and the concluding remarks are given.

 

Chapter 7 describes the nonmonotonic-based congestion control schemes for a delayed nonlinear network, namely, ADNCQLCC, ADCQLCC and GADNCQLCC. First comparison of DPCC, RDANQCC, DNCQLCC, LCC and ADNCQLCC is presented, afterwards, the main results, performance analysis and the concluding remarks are given.

 

The book surveys the most recent technical works that readers can refer for the most up-to-date development of LMI- based congestion control schemes in wireless sensor networks. The book should be useful as graduate level course in electrical and computer engineering for MSc and Ph.D. students. The book is also useful for software, hardware, and system engineers in the wireless sensor network designing and operation.

 

Shoorangiz Shams Shamsabad Farahani

Assistant professor, Department of Electrical Engineering, Islamshahr branch, Islamic Azad University, Islamshahr, Iran