||A New Zero-Knowledge Routing in Delay Tolerant Mobile Ad Hoc Networks
||Department of Computer Science and Information Engineering
Queueing Petri Net
在本篇論文，先對隨意移動網路的現況與發展作探討，接著討論更具挑戰性的延時容忍網路(DTN)。最後，再嘗試由生活中有趣的例子，來做為發展的靈感。而提出在零知識的場景下，新的路由方法。我們知道，在奧林匹克運動會場上，四百公尺接力賽的平均個人速度往往比單人跑百米的速度更快！本人試著將這種特性引入到零知識的路由場景中：藉著「接力傳遞消息」應該會比「單一人傳遞消息」會有更好的效果，來提昇訊息投遞率，並且減少重覆訊息的數量！本文已發展出一個有趣的方法，稱為「OOPFE」，而且已經用NS2模擬器來驗證。結果顯示，新的路由特別適合在網路場景較大，或是源節點的移動速度較慢的場景。更進一步，本人也研究此路由在遇到封包丟失問題時，對路由效能的影響情形。並且，也應用佇列派翠網路(QPN, Queueing Petri Net)的工具，塑造路由方法的模式，來觀察DTN路由方法，在隨意移動模式下，兩個重要的評估尺度。
||Recently, many scholars have invested a lot of times in a hot research topic, DTNs. There are many interesting routing protocols be developed. However, about zero-knowledge routing, fewer breakthroughs can make their ways for novel developments. Especially in resource-restricted and limited the amount of replication messages, there are extremely difficulties to design routing strategies for selecting a suitable path based on insufficient knowledge. In this paper, we observe the situation in daily life to get an inspiration for development idea. In the 400-meter relay race of the World Olympic Game, the average speed is faster than that of the individual 400-meters race. I have tried to use the characteristics and further research by the way of “relay-delivering message” to tackle the tradeoff for increasing the delivery ratio and decreasing the number of duplication in the zero-knowledge scenarios. I have developed an interesting method, named “OOPFE”, and have used NS2 simulator to verify. Furthermore, I have studied the reasons of impact routing performance about packet drop problems. The results show that the new routing method suitable for the size of network scenarios is bigger or the speed of source node is slower. At last, I also use the tools of “Queueing Petri Net” to build the model of the different routing method and to observe two important metrics for random waypoint mobility in DTNs.
||TABLE OF CONTENTS
LIST OF FIGURES VII
LIST OF TABLES XI
Chapter 1 Introduction - 1 -
1.1 Routing problems in DTNs and Motivation - 2 -
1.2 Contributions - 3 -
1.3 Thesis Structure - 4 -
Chapter 2 Related Works - 5 -
2.1 Introduce the wireless Ad Hoc Networks - 5 -
2.1.1 The concepts and features in MANET - 5 -
2.1.2 The applications in mobile ad hoc network - 8 -
2.1.3 The major research institutions and new application areas in mobile ad hoc network - 10 -
2.2 The routing protocols in mobile ad hoc network) - 11 -
2.3 The concepts and features in DTNs - 16 -
2.3.1 The problems in DTNs - 16 -
2.3.2 Applications must be afraid of delay in DTNs - 17 -
2.3.3 Applications and features in DTNs - 18 -
2.3.4 The application of common features and characteristics in DTNs - 20 -
2.3.5 The simple classification based on different numbers of copy messages in DTN - 22 -
2.4 The routing algorithm in DTNs - 23 -
2.4.1 "Direct Transfer" routing method and wireless sensor networks - 23 -
2.4.2 First contact routing and two-hop routing - 24 -
2.4.3 The exchange mechanism in epidemic routing - 25 -
2.4.4 Probability associated with the routing protocol - 26 -
2.4.5 Adapter mechanism associated routing - 27 -
2.4.6 Compare the flooding problems between MANETs and the epidemic routing in DTNs - 28 -
188.8.131.52 The differences in scenarios - 28 -
184.108.40.206 The differences in methods - 29 -
220.127.116.11 There are different present for broadcast storm problem - 29 -
18.104.22.168 The metrics are different - 30 -
22.214.171.124 The major problems occur in Epidemic DTN-routing - 30 -
Chapter 3: From the viewpoints of distributed system to discuss the routing problem and the design idea of this thesis - 32 -
3.1 The CAP Theorem in distributed system - 32 -
3.2 Attention to Availability and Partition Tolerance - 34 -
3.3 Multi-copy, consistency, single-copy and Head-of-Line blocking problems - 36 -
3.3.1 Multi-copy and don't need consistency problem - 36 -
3.3.2 Resolve the single-copy and HOL problems - 36 -
3.3.3 The interesting issues between single-copy and multi-copy - 38 -
Chapter 4 OOP and OOPFE-Routing Scheme - 39 -
4.1 OOP-Routing Scheme - 39 -
4.1.1 The 1’st step, OB (One Broadcast) process - 40 -
4.1.2 The 2’nd step, OC (One Copy) process - 41 -
4.1.3 The 3’rd step, PS (Persistent Storage) process - 41 -
4.2 OOPFE-Routing Method - 41 -
4.3 The algorithm of OOPFE-Routing - 42 -
4.3.1 Algorithm-part A: Processing the received packet - 42 -
4.3.2 Algorithm-part B: Achieve anti-entropy session - 45 -
Chapter 5 Network Simulator, Visualization tools and Mobile pattern generator - 46 -
5.1 About NS2 - 46 -
5.2 NS2 wireless simulator architecture - 48 -
5.3 The process flow of NS2 - 49 -
5.4 The usage of NS2 - 50 -
5.5 The visualization tools: Nam - 51 -
5.6 Random Waypoint Model mobility generator inNS2 - 52 -
5.6.1 Mobile Mobility - 52 -
5.6.2 The Mobile Mobility generator: Setdest - 53 -
Chapter 6 Simulation and performance evaluation - 54 -
6.1 RWP Mobility Model - 54 -
6.2 Simulation setup - 55 -
6.3 Result - 56 -
Chapter 7 Analysis for OOPFE-Routing - 63 -
7.1 In 1’st phase (OB) - 63 -
7.2 In 2’nd phase (OC) - 64 -
7.3 In 3’rd phase (PS) - 66 -
7.4 Compare with Two-Hop Routing - 66 -
Chapter 8 Using NS2 to Analyze the Packet Drop Problem - 68 -
8.1 Introduction of Packet Drop Problem - 68 -
8.1.1 The problem of buffer queue in DTN - 68 -
8.1.2 Packet drop problems - 69 -
8.1.3 Dropped packets in ns2 - 71 -
8.2 Basic compare with tradition routing method - 72 -
8.3 Advance compare the result in hop-limit is 20 - 72 -
8.4 Conclusions - 79 -
Chapter 9 Using QPN to model two important metrics of routing protocol in DTN - 81 -
9.1 What’s PN (Petri Nets)? What’s QPN? - 81 -
9.1.1 The define of Petri Nets - 81 -
9.1.2 The network model of Petri Nets - 82 -
9.1.3 Queueing theory (Queueing Models) - 84 -
9.1.4 QPN is Queueing model + Petri Net model - 85 -
9.1.5 The current simulation tool of QPN - 86 -
9.1.6 The related researches to use PN Model in Ad-Hoc Networks - 87 -
9.2 Using QPN to model routing in RWP mobility - 87 -
9.2.1 Random Waypoint mobility - 87 -
9.2.2 The definition of IMT and CT - 88 -
9.2.3 System Model - 89 -
9.2.4 To get and analyze the parameters for the IMT and CT in DTN - 89 -
126.96.36.199 To compare the literatures with our simulation results for IMT - 89 -
188.8.131.52 To compare the literatures with our simulation results for CT - 91 -
9.2.5 Using QPN to express the IMT and CT - 92 -
9.3 Using QPN to model the Direct-Routing in DTN - 94 -
9.3.1 Consider the link time will be insufficient and need a retransmission mechanism - 95 -
9.3.2 Don’t consider the link time will be insufficient - 98 -
9.4 Using QPN to model two known multi-hop routing in DTN - 101 -
9.4.1 Using QPN to model 2Hop Routing in DTN - 101 -
9.4.2 Using QPN to model Epidemic Routing in DTN - 104 -
9.5 Using QPN to model OOPFE Routing in DTN - 107 -
9.5.1 First case, we consider no any neighbor node in “One broadcast” process - 107 -
184.108.40.206 The basic Markov state transition diagram for OOPFE routing - 108 -
220.127.116.11 The method to transfer the Markov state transition diagram into QPN for Latency - 109 -
18.104.22.168 The method to simulate the Delivery ratio in QPN - 112 -
9.5.2 Second case, we consider the numbers of neighbor nodes in “One broadcast” process - 119 -
22.214.171.124 The basic Markov state transition diagram for OOPFE routing - 119 -
126.96.36.199 The method to transfer the Markov state transition diagram of OOPFE routing into QPN for Latency - 121 -
9.6 Small Conclusion and Future works - 123 -
Chapter 10 Discussion in OOPFE-Routing - 125 -
Chapter 11 Conclusions & Future Work - 128 -
References - 129 -
LIST OF FIGURES
Figure 1. A classification of the method of zero-knowledge routing - 2 -
Figure 2. Example of the intermittent connect network - 3 -
Figure 3. The classification of the famous ad hoc routing protocols - 12 -
Figure 4. The more detail classification of the famous ad hoc routing protocols - 13 -
Figure 5. The classification of the ad hoc clustering algorithm routing methods - 15 -
Figure 6. Anti-entropy session - 25 -
Figure 7. HOL problem and Persistent storage - 37 -
Figure 8. A New message is entering the system - 39 -
Figure 9. OB process, only one broadcast - 39 -
Figure 10. OC process, only one copy - 40 -
Figure 11. PS process, hold on the message in PS - 40 -
Figure 12. A challenge problem in OC-process - 41 -
Figure 13. The architecture of the ns2 wireless simulator - 48 -
Figure 14. ns2 simulation process flow - 50 -
Figure 15. Scenario snapshots for RWP Model (The Epidemic-Routing is Running) - 54 -
Figure 16. Simulation results in RWP Model (Dist.=40m, 6 Hop-limit) - 58 -
Figure 17. The simulation results for different hop-limit in RWP Model (Dist.=40m) - 59 -
Figure 18. The simulation results of the average numbers of hop count in different hop-count limit (RWP Model, Dist.=40m) - 62 -
Figure 19. Average number of neighbors in source node - 64 -
Figure 20. Area can be copied in Two-Hop Routing - 67 -
Figure 21. Area can be copied in OOPFE-Routing - 67 -
Figure 22. Three types of packet-drop-problems - 70 -
Figure 23. Simulation results in RWP Model (Dist.=40m, 20 Hops) - 74 -
Figure 24. Compare the detail reasons in the collision reason - 76 -
Figure 25. Compare the numbers of Drop-By-ARP in four different routings - 76 -
Figure 26. The Hop-count for Packet-ID from 1 to 30 in different routing - 78 -
Figure 27. The Hop-count for Packet-ID from 1951 to 1980 in different routing - 78 -
Figure 28. The basic units of Petri Nets - 82 -
Figure 29. A brief description for Enabled and Marking in Petri Net - 83 -
Figure 30. A simple Firing Example - 83 -
Figure 31. A simple schematic diagram of Queueing Model - 84 -
Figure 32. The composition of Queue Place - 86 -
Figure 33. The mobile schematic graphics of Random Waypoint Mobility - 88 -
Figure 34. The mean First IMT of 50 nodes in ns2 simulation - 91 -
Figure 35. The mean CT of 50 nodes in ns2 simulation - 92 -
Figure 36. The lifetime distribution of CT of 50 nodes in ns2 simulation. (The approximate relative average is 16 m/s) - 92 -
Figure 37. The simple simulation for mobile model in QPME - 94 -
Figure 38 (a) (b) (c) (d). Consider the impact on Link time in QPN - 98 -
Figure 39. The result includes the "Never Meet Ratio" of QPN - 100 -
Figure 40. Using the Probe of QMEP to catch the statistical results of Latency - 100 -
Figure 41. Two-hop multi-copy protocol transition diagram of the Markov chain for the number of copies - 102 -
Figure 42. The experiment of 2Hop (N=3+1) in QPME. The Latency is 409 - 103 -
Figure 43. The experiment of 2Hop (N=6+1) in QPME. The Latency is 300 - 104 -
Figure 44. Unrestricted multi-copy protocol: transition diagram of the Markov chain for the number of copies - 104 -
Figure 45. The experiment of Epidemic (N=6+1) in QPME. The Latency is 261 - 105 -
Figure 46. To compare the values of theory with our simulation in QPME for 2Hop-routing and Epidemic routing. - 107 -
Figure 47. The Markov chain transition diagram and omit “One broadcast” process in OOPFE routing - 109 -
Figure 48(a). Another equivalent Petri Net expression for 2Hop. The N = 2 +1. And Imt1, Imt2 set 1λ, 2λ, 3λ - 111 -
Figure 48(b). Another equivalent Petri Net expression for 2Hop. N =3 +1. And Imt1, Imt2, Imt3 set 1λ, 2λ, 3λ - 112 -
Figure 49(a). Using QPME to express the Delivery ratio for 2Hop routing. The value of msgTTL sets to twice of the average inter-meeting times. It is 968. The results of Latency fell to 358.56 from 482.24 - 113 -
Figure 49(b). Using QPME to express the Delivery ratio for 2Hop routing. The results of Delivery ratio fell to 0.87 - 114 -
Figure 49(c). Using QPME to express the Delivery ratio for 2Hop routing. The value of msgTTL sets to 2000 sec. The results of Latency fell to 0.9913 - 115 -
Figure 50(a). Using QPME to express the Delivery ratio for Direct-routing. The value of msgTTL sets to 2000 - 118 -
Figure 50(b). Using QPME to express the Delivery ratio for Direct-routing. The value of msgTTL sets to twice of IMT - 119 -
Figure 51. The Markov chain transition diagram and consider “One broadcast” process in OOPFE routing. The number of m in this figure is neighbor’s nodes; the range is from 0 to 1 - 121 -
Figure 52. Using QPME to observe the Latency in OOPFE routing - 123 -
Figure 53. Including 26 nodes whose speed can be randomly selected from 0.1 to 0.2m/sec - 126 -
LIST OF TABLES
Table I. Simulation Model Parameters - 55 -
Table II. Simulation Network Parameters - 55 -
Table III. After sending 1980 messages, the numbers of received packets of the traditional routing methods - 72 -
Table IV. The different packet loss reasons comparison table of 4 different routing protocols - 76 -
Table V. The values of theory and the values of experimental in QPME for the numbers of nodes are from 2 to 7 in two routing method - 106 -
Table VI. Compare the Latency and Delivery Ratio changes between the msgTTL are twice of IMT or 2000 for 2Hop routing. (N=2+1, at this time, Epidemic and 2hop are same.) - 114 -
Table VII. Observe the changes of Latency and Delivery ratio for the values of msgTTL is 2*484.3 and 2000 in 2Hop routing. ( Note: the distribution of msgTTLis Uniform) - 116 -
Table VIII. Observe the changes of Latency and Delivery ratio for the values of msgTTL is 2*484.3 and 2000 in Direct-routing - 117 -
Table IX. OOPFE routing, N=3+1, observe the Latency - 122 -
Table X. Compare four different Routing methods from four indicators - 126 -
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