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Exploitation of Path Diversity in Cooperative Multi-Hop Wireless Networks Dissertation Committee Department of Electrical and Computing Engineering University.

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Presentation on theme: "Exploitation of Path Diversity in Cooperative Multi-Hop Wireless Networks Dissertation Committee Department of Electrical and Computing Engineering University."— Presentation transcript:

1 Exploitation of Path Diversity in Cooperative Multi-Hop Wireless Networks Dissertation Committee Department of Electrical and Computing Engineering University of Delaware Dr. Cimini Dr. Cotton Dr. Shen Dr. Morris (ECE Department) (CIS Department) (CERDEC) Candidate Chair : Jonghyun Kim : Dr. Bohacek

2 Introduction and challenges Aggressive path quality monitoring  BSP Efficient path quality monitoring  LBSP Opportunistic forwarding  LBSP2, LOSP, LMOSP Conclusion and future work Outline

3 Introduction and challenges Mobility Modeling 2004 ~ 2009 4 papers Mobility Modeling 2004 ~ 2009 4 papers Cooperative Path Diversity 2005 ~ present 4 papers Cooperative Path Diversity 2005 ~ present 4 papers Channel Activity Analysis 2007 ~ 2009 1 paper Channel Activity Analysis 2007 ~ 2009 1 paper User Perceptual Quality Evaluation 2008 ~ 2009 0 paper User Perceptual Quality Evaluation 2008 ~ 2009 0 paper Application Traffic Identification & Modeling 2008 ~ 2011 1 paper Application Traffic Identification & Modeling 2008 ~ 2011 1 paper Research

4 Routing Technique Proactive (e.g., OLSR) Reactive (e.g., AODV) Introduction and challenges

5 : Routing control packet transmission : No transmission Proactive

6 Introduction and challenges : Routing control packet transmission : No transmission Reactive

7 Introduction and challenges : data packet from transport layer Reactive

8 Introduction and challenges Routing Technique Proactive (e.g., OLSR) Reactive (e.g., AODV) Single path (e.g., AODV) Multiple paths (e.g., AOMDV)

9 Introduction and challenges Single path B A

10 Introduction and challenges Multiple paths B A

11 Introduction and challenges Routing Technique Proactive (e.g., OLSR) Reactive (e.g., AODV) Single path (e.g., AODV) Multiple paths (e.g., AOMDV) Cooperative path diversity (BSP, LBSP, LOSP, LMOSP)

12 Cooperative path diversity BA Introduction and challenges

13 Cooperative path diversity BA One possible path Introduction and challenges

14 Cooperative path diversity BA Another possible path Introduction and challenges

15 Cooperative path diversity B Many possible paths A Introduction and challenges

16 Cooperative path diversity B Best path A Introduction and challenges

17 Cooperative path diversity Nodes are moving Link quality varies Best path varies Path quality varies Introduction and challenges

18 Challenges  How to define the path quality based on channel conditions?  How to monitor the time-varying path quality to determine the best path cooperatively?

19 Overview Cooperative path diversity (BSP, LBSP, LOSP, LMOSP) Aggressive path quality monitoring (BSP) Efficient path quality monitoring (LBSP) Introduction and challenges Opportunistic forwarding with path qualities (LOSP, LMOSP)

20 Introduction and challenges Aggressive path quality monitoring  BSP Efficient path quality monitoring  LBSP Opportunistic forwarding  LBSP2, LOSP, LMOSP Conclusion and future work Outline

21 Aggressive path quality monitoring Objectives  Define path quality  Monitor path quality aggressively/ideally to investigate maximally possible benefits offered by path diversity routing  Protocol proposed : BSP (best-select protocol)

22 Path quality  Depends on channel conditions (e.g., channel loss, SNR, transmit power) Aggressive path quality monitoring  Depends on protocol designer’s routing objectives Maximize the minimum SNR along the path  (max-min SNR) Maximize delivery probability Maximize throughput Minimize end-to-end delay Minimize total power Minimize total energy

23 Dynamic programming  Achieves routing objectives = cost-to-go from node (n,i) to destination Aggressive path quality monitoring

24 Dynamic programming  Achieves routing objectives = cost-to-go from node (n,i) to destination Relay-set 3Relay-set 2Relay-set 1Relay-set 0 Aggressive path quality monitoring

25 Dynamic programming  Achieves routing objectives 0,1 1,1 1,2 2,1 2,2 3,1 Relay-set 3Relay-set 2Relay-set 1Relay-set 0 src dst = cost-to-go from node (n,i) to destination Aggressive path quality monitoring

26 Dynamic programming  Achieves routing objectives src dst 0,1 1,1 1,2 2,1 2,2 3,1 = cost-to-go from node (n,i) to destination Aggressive path quality monitoring

27 Dynamic programming  Achieves routing objectives 0,1 1,1 1,2 2,1 2,2 3,1 = cost-to-go from node (n,i) to destination 30 20 J (1,1) = 30 J (1,2) = 20 Aggressive path quality monitoring

28 Dynamic programming  Achieves routing objectives 0,1 1,1 1,2 2,1 2,2 3,1 = cost-to-go from node (n,i) to destination 30 20 J (1,1) = 30 J (1,2) = 20 J (2,1) = 20 20 Aggressive path quality monitoring

29 Dynamic programming  Achieves routing objectives 0,1 1,1 1,2 2,1 2,2 3,1 = cost-to-go from node (n,i) to destination 30 20 J (1,1) = 30 J (1,2) = 20 J (2,1) = 20 10 J (2,1) = 10 20 Aggressive path quality monitoring

30 Dynamic programming  Achieves routing objectives 0,1 1,1 1,2 2,1 2,2 3,1 = cost-to-go from node (n,i) to destination 30 20 J (2,1) = 20 10 20 Aggressive path quality monitoring

31 Dynamic programming  Achieves routing objectives 0,1 1,1 1,2 2,1 2,2 3,1 = cost-to-go from node (n,i) to destination 30 20 J (2,1) = 20 10 20 Aggressive path quality monitoring

32 Dynamic programming  Achieves routing objectives 0,1 1,1 1,2 2,1 2,2 3,1 = cost-to-go from node (n,i) to destination Aggressive path quality monitoring

33 Dynamic programming  Achieves routing objectives = cost-to-go from node (n,i) to destination Previous step’s cost-to-go Stage information Aggressive path quality monitoring

34 Dynamic programming  Achieves routing objectives = cost-to-go from node (n,i) to destination 0,1 1,1 1,2 2,1 2,2 3,1 J (1,1) = 30 J (1,2) = 20 10 20 Aggressive path quality monitoring

35 Dynamic programming  Achieves routing objectives = cost-to-go from node (n,i) to destination 0,1 1,1 1,2 2,1 2,2 3,1 J (1,1) = 30 J (1,2) = 20 10 20 Aggressive path quality monitoring

36 Max-min SNR Aggressive path quality monitoring

37 Max delivery probability Aggressive path quality monitoring

38 Max delivery probability Aggressive path quality monitoring

39 Max delivery probability Aggressive path quality monitoring n,i n-1,I n-1 (1) n-1,I n-1 (2) n-1,I n-1 (3)

40 Max delivery probability Aggressive path quality monitoring n,i n-1,I n-1 (1) n-1,I n-1 (2) n-1,I n-1 (3)

41 Max delivery probability Aggressive path quality monitoring n-1,I n-1 (1) n-1,I n-1 (2) n-1,I n-1 (3) n,i

42 Max throughput Aggressive path quality monitoring

43 Min end-to-end delay Aggressive path quality monitoring

44 Min total power Aggressive path quality monitoring

45 Min total energy Aggressive path quality monitoring

46 Construction of relay-sets 0,1 1,1 1,2 2,1 2,2 3,1 AODV finds a traditional single path Aggressive path quality monitoring

47 Construction of relay-sets 0,1 1,1 1,2 2,1 2,2 3,1 Relay-set 3Relay-set 2Relay-set 1Relay-set 0 Aggressive path quality monitoring

48 Construction of relay-sets 0,1 1,1 1,2 2,1 2,2 3,1 Relay-set 3Relay-set 2Relay-set 1Relay-set 0 Aggressive path quality monitoring

49 Construction of relay-sets 0,1 1,1 1,2 2,1 2,2 3,1 Relay-set 3Relay-set 2Relay-set 1Relay-set 0 Aggressive path quality monitoring

50 Construction of relay-sets 0,1 1,1 1,2 2,1 2,2 3,1 Relay-set 3Relay-set 2Relay-set 1Relay-set 0 Aggressive path quality monitoring

51 Path quality monitoring 0,1 1,1 1,2 2,1 2,2 3,1 CIEREQ (channel info exchange request) CIEREP (channel info exchange reply) Relay-set 3Relay-set 2Relay-set 1Relay-set 0 Aggressive path quality monitoring

52 Path quality monitoring 0,1 1,1 1,2 2,1 2,2 3,1 CIEREQ : data frame Aggressive path quality monitoring

53 Path quality monitoring 0,1 1,1 1,2 2,1 2,2 3,1 CIEREP Path qualities between relay-set 3 and 2 are monitored Aggressive path quality monitoring

54 Path quality monitoring 0,1 1,1 1,2 2,1 2,2 3,1 data Aggressive path quality monitoring

55 Path quality monitoring 0,1 1,1 1,2 2,1 2,2 3,1 CIEREQ Aggressive path quality monitoring

56 Path quality monitoring 0,1 1,1 1,2 2,1 2,2 3,1 CIEREP Path qualities between relay-set 2 and 1 are monitored Aggressive path quality monitoring

57 Path quality monitoring 0,1 1,1 1,2 2,1 2,2 3,1 Assume that Aggressive path quality monitoring

58 Path quality monitoring 0,1 1,1 1,2 2,1 2,2 3,1 data Path qualities are monitored every packet transmission Aggressive path quality monitoring

59 Path quality monitoring 0,1 1,1 1,2 2,1 2,2 3,1 Aggressive path quality monitoring

60 Simulation  UDelModels : Urban city, mobility, channel models  Numerical analysis Ideally construct relay-sets and receive CIEREQ/CIEREP  Packet level simulation QualNet network simulator CBR traffic (1024 bytes per second)  Comparison between J single and J diversity J single : source’s J along the single path found initially J diversity : source’s J along the best path among all paths Aggressive path quality monitoring

61 Results : benefits of path diversity Aggressive path quality monitoring 246810 0 5 15 20 25 30 Sparse Dense 2 4 6 8 10 2468 0 Sparse Dense 2468 10 0 5 15 Sparse Dense 246810 0 5 15 Sparse Dense 246810 0 1 2 3 4 Sparse Dense 246810 0 1 2 3 Sparse Dense Max delivery prob.Max throughput J diversity / J single Max-min SNR J diversity — J single J diversity / J single Min powerMin energyMin delay J diversity / J single

62 Results : path selection differences Aggressive path quality monitoring 2468 10 0 0.2 0.4 0.6 0.8 1 Fraction of relays shared Minimum relay-set size max-min SNR max throughput min total powermin energy min end-to-end delay max delivery probability vs.

63 Introduction and challenges Aggressive path quality monitoring  BSP Efficient path quality monitoring  LBSP Opportunistic forwarding  LBSP2, LOSP, LMOSP Conclusion and future work Outline

64 Efficient path quality monitoring Objectives  Monitor path quality efficiently to reduce overhead J broadcast, J -test, power control  Robust routing function Automatic path stretching and shrinking  Protocol proposed : LBSP (local BSP)

65 Path quality monitoring : J broadcast 0,1 1,1 1,2 2,1 2,2 3,1 JBC ( J broadcast) Relay-set 3Relay-set 2Relay-set 1Relay-set 0 Efficient path quality monitoring

66 Path quality monitoring : J broadcast 0,1 1,1 1,2 2,1 2,2 3,1 Efficient path quality monitoring

67 Path quality monitoring : J broadcast 0,1 1,1 1,2 2,1 2,2 3,1 Efficient path quality monitoring JBC Path qualities between relay-set 1 and 0 are monitored

68 Path quality monitoring : J broadcast 0,1 1,1 1,2 2,1 2,2 3,1 Efficient path quality monitoring JBC Path qualities between relay-set 2 and 1 are monitored

69 Path quality monitoring : J broadcast 0,1 1,1 1,2 2,1 2,2 3,1 Efficient path quality monitoring JBC Path qualities between relay-set 3 and 2 are monitored

70 Path quality monitoring : J broadcast 0,1 1,1 1,2 2,1 2,2 3,1 Efficient path quality monitoring : best path Next hop best node

71 Path quality monitoring : J broadcast  When this J -broadcast occurs? When current best path quality degradation is experienced. Efficient path quality monitoring 0,1 1,22,2 3,1 src dst

72 Path quality monitoring : J broadcast  When this J -broadcast occurs? When current best path quality degradation is experienced. Efficient path quality monitoring Reference path quality for the first data frame Path quality for the subsequent data frame

73 Efficient path quality monitoring Path quality monitoring : J -test  n-1,1 n-1,3 n-1,2 JBC n,i JBC

74 Efficient path quality monitoring Path quality monitoring : J -test  n-1,1 n-1,3 n-1,2n,i If,

75 Efficient path quality monitoring Path quality monitoring : J -test  n-1,1 n-1,3 n-1,2 broadcast JBC JBC relay-set ( n+1) Avoid broadcasting lower path quality than n,i

76 Efficient path quality monitoring Path quality monitoring : power control  Efficient path quality advertisement Higher path quality Lower path quality Higher power Lower power  n,1n,1 n,3n,3 n,2n,2n+1,i

77 Efficient path quality monitoring Path quality monitoring : power control  Efficient path quality advertisement Higher path quality Lower path quality Higher power Lower power  Exploit the “near-far” problem

78 Efficient path quality monitoring Path quality monitoring : power control

79 Efficient path quality monitoring Path quality monitoring : power control n,1n,1 n,3n,3 n,2n,2n+1,i 17dBm 12dBm 10dBm

80 Efficient path quality monitoring Path quality monitoring : power control n,1n,1 n,3n,3 n,2n,2n+1,i 17dBm 12dBm 10dBm JBC

81 Efficient path quality monitoring Automatic path stretching and shrinking  Stretching 0,1 1,1 1,2 2,1 2,2 3,1 Relay-set 3Relay-set 2Relay-set 1Relay-set 0 A : Current active best path

82 Efficient path quality monitoring Automatic path stretching and shrinking  Stretching 0,1 1,1 1,2 2,1 2,2 3,1 Relay-set 3Relay-set 2Relay-set 1Relay-set 0 A

83 Efficient path quality monitoring Automatic path stretching and shrinking  Stretching 0,1 1,1 1,2 2,1 2,2 3,1 Relay-set 3Relay-set 2Relay-set 1Relay-set 0 A

84 Efficient path quality monitoring Automatic path stretching and shrinking  Stretching 0,1 1,1 1,2 2,1 2,2 4,1 Relay-set 3Relay-set 2Relay-set 1Relay-set 0 3,1 Relay-set 4

85 Efficient path quality monitoring Automatic path stretching and shrinking  Shrinking 0,1 1,1 1,2 2,1 2,2 3,1 Relay-set 3Relay-set 2Relay-set 1Relay-set 0 : Current active best path

86 Efficient path quality monitoring Automatic path stretching and shrinking  Shrinking 0,1 1,1 1,2 2,1 2,2 3,1 Relay-set 3Relay-set 2Relay-set 1Relay-set 0

87 Efficient path quality monitoring Automatic path stretching and shrinking  Shrinking 0,1 1,1 1,2 2,1 2,2 3,1 Relay-set 3Relay-set 2Relay-set 1Relay-set 0

88 Efficient path quality monitoring Automatic path stretching and shrinking  Shrinking 0,1 1,1 1,2 2,1 2,2 2,3 Relay-set 3Relay-set 2Relay-set 1Relay-set 0

89 Efficient path quality monitoring Numerical analysis : setting sourcedestination 50m100m 50m relay-set 2relay-set 1relay-set 3relay-set 0

90 Efficient path quality monitoring Numerical analysis : results 25 nodes per relay-set 20 nodes per relay-set 15 nodes per relay-set 10 nodes per relay-set 5 nodes per relay-set 01020304050 60 70 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8 Solid line Dashed line : optimal : LBSP Chips per symbol Improvement in SNR (dB) ( J diversity — J single )

91 Efficient path quality monitoring Numerical analysis : results Chips per symbol Improvement in SNR (dB) no power control and no J -test no power control but with J -test with power control but no J -test with power control and J -test 0102030405060 70 0 1 2 3 4 5 6 7 8

92 Efficient path quality monitoring Numerical analysis : results Chips per symbol Improvement in SNR (dB) 010203040506070 4.5 5 5.5 6 6.5 7 7.5 MAX_POWER – TARGET_POWER 5 dB 7 dB 10 dB 15 dB* 20 dB

93 Efficient path quality monitoring Packet level simulation : setting  UDelModels : Urban city, mobility, channel models  Simulator : QualNet CBR traffic (1024 bytes per 50 ms for 5 min)

94 Efficient path quality monitoring Packet simulation : results Packet delivery ratio 12345 96 96.5 97 97.5 98 98.5 99 99.5 100 AODV AOMDV LBSP confidence interval # of new route searches 12345 0 10 20 30 40 50 60 70 AODV AOMDV LBSP End-to-end delay (ms) 12345 5 10 15 20 25 30 35 40 45 AODV AOMDV LBSP J diversity — J single 12345 -0.5 0 0.5 1 1.5 2 2.5 3 3.5 AODV AOMDV

95 Efficient path quality monitoring Packet simulation : results 123 45 4 6 8 10 12 14 16 18 20 22 Routing overhead ratio AODV AOMDV Efficiency 12345 97.5 97.6 97.7 97.8 97.9 98 98.1 98.2 98.3 98.4 98.5 AODV AOMDV LBSP # of new route searches 12345 1 1.05 1.1 1.15 1.2 1.25 1.3 1.35 1.4 1.45 1.5 Without automatic path stretching and shrinking With automatic path stretching and shrinking

96 Introduction and challenges Aggressive path quality monitoring  BSP Efficient path quality monitoring  LBSP Opportunistic forwarding  LBSP2, LOSP, LMOSP Conclusion and future work Outline

97 Opportunistic forwarding Objectives  Compare opportunistic forwarding (OF) and deterministic forwarding (DF) to see if path diversity is better exploited by OF or DF. Without node mobility With node mobility  Protocol proposed LOSP (local opportunistic-select protocol) LMOSP (local monitoring-added OSP)

98 Opportunistic forwarding How it works? IN1 IN2T IN3 : data frame : transmitter : intended node T IN

99 Opportunistic forwarding How it works? IN1 IN2T IN3

100 Opportunistic forwarding How it works? IN1 IN2T IN3 Priority : IN1 > IN2 > IN3

101 Opportunistic forwarding Agreement IN1 IN2T IN3 ACK : overhearing

102 Opportunistic forwarding Agreement IN1 IN2T IN3 ACKACK : overhearing

103 Opportunistic forwarding Agreement IN1 IN2T IN3 ACK : overhearing obstacle

104 Opportunistic forwarding List of priority nodes pn tnT bn Preferred node Target node Backup node Priority : pn > tn > bn LPN = {pn, tn, bn}

105 Opportunistic forwarding List of priority nodes T pn tn bn Preferred node Backup node Target node

106 Opportunistic forwarding List of priority nodes  Target node Make the most progress to the destination  The node that achieves max-min SNR  Preferred node Make better progress to the destination  The node that has larger cost-to-go  Backup node Make some progress to the destination  The node that has smaller cost-to-go

107 Opportunistic forwarding Sequence of nodes  Deterministic forwarding (src, tn, tn, tn, tn, dst)  Opportunistic forwarding (src, tn, pn, pn, tn, dst) (src, tn, bn, pn, tn, dst) …

108 Opportunistic forwarding Bit-rate

109 Opportunistic forwarding Protocols to be compared  Deterministic forwarding LBSP (local best-select protocol)  Efficient path quality monitoring, automatic path stretching and shrinking, route recovery  Opportunistic forwarding LOSP (local opportunistic-select protocol)  One time J broadcast to construct LPN for each route failure, no route recovery  Opportunistic forwarding with the path quality degradation detection LMOSP (local monitoring-added OSP)  Path quality monitoring is added like LBSP, mixture of OF and DF

110 Opportunistic forwarding Sequence of nodes  Deterministic forwarding (src, tn, tn, tn, tn, dst)  Opportunistic forwarding (src, tn, pn, pn, tn, dst) (src, tn, bn, pn, tn, dst) …

111 Opportunistic forwarding Radio model Packet error probability nominal steep steepest shallowest shallower shallow SNR (dB) -50510152025 10 -4 10 -3 10 -2 10 10 0 2 Mbps

112 Opportunistic forwarding Packet level simulation : setting  UDelModels : Urban city, mobility, channel models  Simulator : QualNet CBR traffic (512bytes per 50 ms for 5 min)

113 Opportunistic forwarding Results : performance of the first data packet 12345 1.5 2 2.5 3 3.5 4 LBSPv2LOSPLMOSP nominalsteepsteepest shallowershallow shallowest 12345 1.5 2 2.5 3 3.5 4 12345 1.5 2 2.5 3 3.5 4 scenario number bit-rate (Mbps) (no node mobility)

114 Opportunistic forwarding Results : performance of the first data packet nominalsteepsteepest shallowershallow shallowest 12345 22 23 24 25 26 27 scenario number 12345 22 23 24 25 26 27 12345 22 23 24 25 26 27 SNR (dB) LBSPv2LOSPLMOSP (no node mobility)

115 Opportunistic forwarding Results : performance before the first route failure (node mobility involved) nominalsteepsteepest shallowershallow shallowest scenario number LBSPv2LOSPLMOSP 12345 1.5 2 2.5 3 3.5 12345 1.5 2 2.5 3 3.5 bit-rate (Mbps) 12345 1.5 2 2.5 3 3.5

116 Opportunistic forwarding Results : performance before the first route failure (node mobility involved) nominalsteepsteepest shallowershallow shallowest scenario number LBSPv2LOSPLMOSP SNR (dB) 12345 22 24 26 28 30 12345 22 24 26 28 30 12345 22 24 26 28 30

117 Opportunistic forwarding Results : performance during the connection lifetime nominalsteepsteepest shallowershallow shallowest scenario number LBSPv2LOSPLMOSP packet delivery ratio 12345 0.985 0.99 0.995 1 12345 0.985 0.99 0.995 1 12345 0.985 0.99 0.995 1

118 Opportunistic forwarding Results : performance during the connection lifetime nominalsteepsteepest shallowershallow shallowest LBSPv2LOSPLMOSP Route failure rate scenario number 12345 0 0.05 0.1 0.15 0.2 0.25 0.3 12345 0 0.05 0.1 0.15 0.2 0.25 0.3 12345 0 0.05 0.1 0.15 0.2 0.25 0.3

119 Opportunistic forwarding Results : performance during the connection lifetime nominalsteepsteepest shallowershallow shallowest LBSPv2LOSPLMOSP Efficiency scenario number 12345 0.88 0.9 0.92 0.94 0.96 0.98 1 12345 0.88 0.9 0.92 0.94 0.96 0.98 1 12345 0.88 0.9 0.92 0.94 0.96 0.98 1 duration that user data packets are transmitted duration that any packet including overhead is transmitted Efficiency =

120 Opportunistic forwarding Conclusion  Without mobility (e.g., stationary mesh network) Opportunistic forwarding is preferred except for the overhead  With mobility Deterministic forwarding is preferred Path diversity is better exploited by deterministic forwarding

121 Introduction and challenges Aggressive path quality monitoring  BSP Efficient path quality monitoring  LBSP Opportunistic forwarding  LBSP2, LOSP, LMOSP Conclusion and future work Outline

122 Conclusions  The significant benefits of path diversity are possible using aggressive path quality monitoring.  Reducing overhead and advertising path quality efficiently are possible using the proposed novel techniques, still maintaining high benefits.  Path diversity is better exploited by deterministic forwarding with node mobility. Conclusions and future work

123 Future work  Estimate the dynamics of channel by observing ongoing channel activity.  Achieve fast estimation of link/path qualities from the channel dynamic estimation. i.e., given the estimated current channel state, estimate link/path qualities.  Develop models of channel evolution. Conclusions and future work

124 Schedule Conclusions and future work DateTask 11/11/2011 ∼ 11/20/2011 Packet level simulation 11/21/2011 ∼ 12/31/2011 Real channel measurement 12/16/2011 ∼ 12/31/2011 Develop models of channel evolution 01/01/2012 ∼ 01/15/2012 Writing up all findings 12/01/2011 ∼ 01/31/2012 Proofreading the whole thesis

125 Thanks

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