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13 A E N 1..N 6 A E k = 5m, 1m, 15m, 2m
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30 Operating Mode Current (mah) ATMega1281V, full operation 6 (7.37 MHz) ATMega1281V, sleep.1 Radio, receive 16 Radio, transmit (1 mw power) 17 Radio, sleep.1 Serial flash memory, write 15 Serial flash memory, read 4 Serial flash memory, sleep.2 Table 2.1: Current consumption of various system components and operations for an IRIS OEM Crossbow node.
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34 source attacker destination RREQ RREP Figure 2.1: Illustration of a black-hole attack. The malicious node, in red, claims to have a shorter route to the destination compared to the ones offered by its neighbors. So, the malicious node attracts the traffic from the source to the destination.
35 source attacker destination RREQ RREP Figure 2.2: Illustration of a Sybil attack in multi-path routing. The malicious node, in red, presents two different identities, giving the impression to the source node that there exist two different paths to the destination. So, the malicious node will attract all the traffic from source to destination.
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39 TBO A = K A(src) TBO B = K B(N B, K A (src)) TBO C = K C(N C, K B (N B, K A (src))) TBO D = K D (N D, K C (N C, K B (N B, K A (src)))) TBO A TBO B TBO C TBO D A B C D E TBO A TBO B TBO C TBO D Figure 2.3: ANODR TBO: Anonymous route discovery from node A to node E. A < RREQ, tr dest, onion > tr dest onion X N X K X N X K X X D N D < RREP, N D, onion >
40 X N X N P revioushop N X N P revioushop N X N N A B C D E N 1 N 2 N 3 N 4 N 5 N 6 N 1 N 2 N 2 N 3 N 3 N 4 N 4 N 5 N 5 N 6 Figure 2.4: ANODR TBO: Using route pseudonyms N 1..N 6 to route messages from A to E.
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42 i < K A (A, data), ID Ai, checksum > K A (A, data) A K A ID Ai A i checksum A B t A m B id At A K A B
43 t A id At B A m B B id At B A m A B A δ t δ t
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46 n m (n 1) m n (n 1) m 1,.16 16,
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49 p p c < 1 p > p c p < p c p c p
50 p p C T max
51 d d min = d d min
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53 T max T max
54 p p
55 m k p = 1 m = 1 k = 1 p =.65 m p k
56 5m, 1m, 15m, 2m
57 Avg. Internode Distance Avg. Neighbors Network Diameter MAC TX Success Ratio = 5m = 1m = 15m = 2m Table 3.1: Characteristics of the considered network configurations. m p p {%, 1%, 2%,..., 1%} m {, 1, 2, 3} p m {5m, 1m, 15m, 2m} k p m p m m = p p
58 1 Receivers (% Nodes).8.6 5m.4 1m.2 15m 2m m 1m 15m 2m m 1m 15m 2m m 1m 15m 2m Forwarders (% Nodes) m.4 1m.2 15m 2m m 1m 15m 2m m 1m 15m 2m m 1m 15m 2m dissemination time (sec) m 1m 15m 2m m 1m 15m 2m m 1m 15m 2m m 1m 15m 2m Fwd. p Fwd. p Fwd. p Fwd. p (i): m= (j): m=1 (k): m=2 (l): m=3 Figure 3.1: Performance of Gossip3. We vary the parameters p and m in networks with inter-node distance: 5m, 1m, 15m, 2m. Latency represents the time, in seconds, to cover 9% of the nodes. m 1 p = 2m m = 1 p = 1 p = m = 3
59 p m p p p p p = p =.1 p =.2 p =.3 p =.1 m = 1 p m p p
60 p p = 5m = 1m p p k k k = 1 k k = k = 1 = 5m : p =.1, m = 1 = 1m : p =.2, m = 1 = 15m : p =.3, m = 1 = 2m : p =.6, m = 3 k = 1 = 5m k = 1 k = k = 1
61 k= k=1 k= k=1 1 1 Receivers (% Nodes) Forwarders (% Nodes) Avg. Node Distance (Δ) Avg. Node Distance (Δ) (a): Coverage (b): Forwarders k= k=1 Latency (s) Avg. Node Distance (Δ) (c): Latency to reach 9% coverage Figure 3.2: Evaluation of parameter k for uniform networks of various densities.
62 Receivers (% Nodes) m 1m.2 15m 2m Forwarding Ratio m 1m 15m 2m Delay Factor Delay Factor (a): Coverage (b): Forwarding ratio Latency (s) m 1m 15m 2m Delay Factor (c): Latency Figure 3.3: Performance of Gossip3 for various values of delay factor.
63 p =.65, m = 1, k = 1 = 5m p =.1 = 2m m = 3 m = 1
64 p p p m > k = p < 1m p =.1 1m 15m p =.2 > 15m p =.4 m = 1 15m m = 3 > 15m
65 Final Forwarding Probability m 6m 7m 8m 9m 1m 15m 2m p(n) Neighborhood Size, N Figure 3.4: The resulting forwarding ratio per node of Gossip3 with optimal parameters in function of neighborhood size. Dots represent nodes and colors represent the network density. p p p p(n) = 1.87 e 5 N 2.3 N p(n) p
66 p curr = p(n curr ) N curr p curr p(n) N j i P RR(i, j) k N(i) = P RR(i, k) k {nodes in i s radio range} m m = 1 m = 1 m 3 = 2m
67 m = 3 = 1m m N N i i i 3 i N i N j N i N j N min i N N min N min = 8 N min
68 = 5m = 1m = 15m = 2m p m k Table 3.2: Parameters of optimal Gossip3 configuration for the considered uniform networks. N min (i) (ii) p =.65 m = 1 k = 1 = 5m, 1m, 15m, 2m k =
69 Adaptive Optimal Default Adaptive Optimal Default 1 1 Receivers (% nodes) Forwarders (% nodes) Avg. Node Distance (Δ) Avg. Node Distance (Δ) (a): Coverage (b): Forwarders Adaptive Optimal Default Adaptive Optimal Default Forwarding ratio Time (s) Avg. Node Distance (Δ) Avg. Node Distance (Δ) (c): Forwarding ratio (d): Latency Figure 3.5: Performance of various Gossip3 configurations in uniform networks with inter-node distance = 5m, 1m, 15m, 2m. = 2m 8% m = 1.65 = 2m
70 % nodes % nodes % nodes Number of Neighbors Number of Neighbors Number of Neighbors (a): N=64 (b): N=128 (c): N= % nodes % nodes Number of Neighbors (d): N=512 Number of Neighbors (e): N=124 Figure 3.6: Histogram of degree distribution for various network sizes. p =.65 = 2m = 1m = 15m = 2m
71 Adaptive Default Adaptive Default 1 1 Receivers (% Nodes) Forwarders (% Nodes) Network Size (N) Network Size (N) (a): Coverage (b): Forwarders Adaptive Default Adaptive Default 1 2 Forwarding Ratio Time (s) Network Size (N) Network Size (N) (c): Forwarding ratio (d): Latency Figure 3.7: Performance of default and adaptive Gossip3 for various network sizes. N =
72 35 Y 3 25 B 2 15 A C Figure 3.8: Non-uniform network topology. Nodes A, B and C act as sources while the rest of the nodes generate continuously synthetic packets to emulate high traffic at the MAC layer. X 128 N = 256 N = p =.65 p =.1
73 Adaptive Default Adaptive Default Receivers (% Nodes) A B C latency (s) A B C Source Node Source Node (a): Coverage (b): Latency Figure 3.9: Performance of default and adaptive Gossip3 in a non-uniform network. Latency represents the average time it takes to reach 8% coverage. Y X (a): Gossip3 Y X (b): Adaptive Gossip3 Figure 3.1: Resulting forwarding ratio of nodes in a non-uniform network represented as color-coded circles.
74 Adaptive Default Forwarders (% Nodes) A B C Source Node Figure 3.11: Fraction of forwarders, grouped by source node, for default and adaptive Gossip3 in a non-uniform network.
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78 Packets delivered Packets sent Figure 4.1: Representation of the congestion problem at the MAC layer.
79 B A C A C A B C A B A B B
80 A B C Figure 4.2: Hidden terminal problem. B B A
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84 Type Collision Avoidance Energyaware Data rate Adaptive to mobility Adaptive to density IEEE CSMA RTS-CTS/ None No High Yes Yes, limited Sift CSMA RTS-CTS No High No Yes CSMA- ARC CSMA Implicit No Low No Yes B-MAC CSMA RTS-CTS/ Implicit Yes Low Yes Yes S-MAC CSMA RTS-CTS Yes Low No No LMAC TDMA Scheduling Yes Fixed No No MLMAC TDMA Scheduling Yes Fixed Yes No GMAC TDMA None Yes Low Yes Yes Z-MAC TDMA/ CSMA Scheduling Yes Low No No Table 4.1: Comparative summary of MAC protocols.
85 ρ s = N/ρ N
86 Parameter Value Topology APP Layer NET Layer MAC Layer Network Size (N) 1 Nodes Distribution random Network Diameter 4 Number of Messages 1 Message Generation Rate (ρ) 1-1 mps Protocol Gossip3 Fwd. Probability (p).3 Compensation factor (m) 1 Flooding Hops (k) Protocol CSMA exp. back-off MinBE 3, 8 Table 4.2: Experimental settings divided by protocol stacks = 15m 2 BE 1 BE
87 Receivers (% Nodes) minbe = 3.2 minbe = Forwarding Ratio.6 minbe = 3 minbe = Message Generation Rate (mps) Message Generation Rate (mps) (a): Coverage (b): Forwarding Ratio Figure 4.3: Performance of Gossip3 configured with optimal parameters Evaluation of two different MAC configurations in function of message generation rate. 32µs BE minbe BE minbe minbe minbe = 3 minbe = 8 minbe = 3 minbe = 8 p =.3
88 p =.3 minbe = 3 minbe = 8 minbe = 3 minbe = 8 minbe = 3 minbe = 8 minbe = 8 minbe = 3 minbe = 8 minbe = 3 minbe
89 4 probabilistic compensation # Rebroadcasts (x1) Message Generation Rate (mps) (a): minbe = 3 4 probabilistic compensation # Rebroadcasts (x1) Message Generation Rate (mps) (b): minbe = 8 Figure 4.4: Distribution of rebroadcasts in function of message generation rate. In Gossip3 newly received packets are either rebroadcast probabilistically, at first, or, shortly after, if found to be not redundant enough. We have adopted Gossip3 with optimal parameters, p=.3,m=1,k= and network size N = 1.
90 1 1 Time (s) 1.1 minbe = minbe = Message Generation Rate (mps) Figure 4.5: Latency of Gossip3 to disseminate messages to 9% of the nodes. minbe = 3 minbe = 8 minbe = 3 minbe = 8 minbe = 3 minbe = 8 minbe = 3 minbe = 8
91 4 4 # Packets (x1) transmissions collisions # Packets (x1) transmissions collisions Message Generation Rate (mps) Message Generation Rate (mps) (a): minbe=3 (b): minbe=8 Figure 4.6: Number of transmissions and collisions at the MAC layer Evaluation of two different MAC configurations in function of message generation rate # Packets minbe = 3 minbe = Message Generation Rate (mps) Figure 4.7: Number of packet overflow at the MAC layer in function of message generation rate. minbe
92 minbe
93 i j Q opt ij = RX ij T X i RX ij j i T X i i i j Q opt ij q ij = Q ij Q opt ij Q ij = RX ij T X i i j Q opt ij i j G G = i N G i G i i G i = T X i q i q i i n(i) q i = 1 n(i) j n(i) q ij
94 Φ Φ = ( N i=1 r i ) 2 N N i=1 r i 2 r i i r i = simulation time = 5, 1, 15, 2m minbe minbe minbe G i
95 Goodput (x1) constant exponential MinBE MinBE MinBE MinBE (a): = 5m (b): = 1m (c): = 15m (d): = 2m Figure 4.8: Network goodput for grid topologies. minbe minbe minbe minbe minbe = 5m = 5m = 5m minbe = 7
96 Time (s) constant exponential MinBE MinBE MinBE MinBE (a): = 5m (b): = 1m (c): = 15m (d): = 2m Figure 4.9: One-hop packet latency for grid topology. Φ constant exponential MinBE MinBE MinBE MinBE (a): = 5m (b): = 1m (c): = 15m (d): = 2m Figure 4.1: Fairness Index Φ for grid topologies. Φ minbe = 5m minbe = 7, 8, 9 = 5m = 5m
97 % Nodes Exponential CW % Nodes Exponential CW % Nodes Constant CW % Nodes Constant CW Number of Transmissions (a): = 5m Number of Transmissions (b): = 1m % Nodes Exponential CW % Nodes Exponential CW % Nodes Constant CW % Nodes Constant CW Number of Transmissions (c): = 15m Number of Transmissions (d): = 2m Figure 4.11: Distribution of transmitted packets in grid topologies.
98 Number of Nodes Grid Random Neighbors Neighbors Neighbors Neighbors (a): = 5m (b): = 1m (c): = 15m (d): = 2m Figure 4.12: Degree distribution of nodes for grid and random topologies of various densities. minbe minbe = 1.5 minbe = 7
99 Goodput (x1) constant exponential MinBE MinBE MinBE MinBE (a): = 5m (b): = 1m (c): = 15m (d): = 2m Figure 4.13: Network goodput for random topologies. Time (sec) constant exponential MinBE MinBE MinBE MinBE (a): = 5 (b): = 1 (c): = 15 (d): = 2 Figure 4.14: One-hop packet latency for random topologies. minbe = 1.5 minbe = 7 minbe minbe minbe minbe
100 % Nodes Exponential CW % Nodes Exponential CW % Nodes Constant CW Goodput (a): = 5m % Nodes Constant CW Goodput (b): = 1m % Nodes Exponential CW % Nodes Exponential CW % Nodes Constant CW % Nodes Constant CW Goodput (c): = 15m Goodput (d): = 2m Figure 4.15: Goodput distribution for random topologies.
101 Φ constant exponential MinBE MinBE MinBE MinBE (a): = 5m (b): = 1m (c): = 15m (d): = 2m Figure 4.16: Fairness index Φ for random topologies. minbe minbe minbe
102 Δ = 5m Δ = 2m 3 2 Y X Figure 4.17: Non-uniform random topology. = 5m = 2m
103 16 14 Δ=5m Δ=2m 12 Goodput (x1) MinBE Combinations (sparse, dense) Figure 4.18: Network goodput for dual CSMA configuration. minbe minbe minbe minbe minbe minbe = 9.5 minbe minbe = 8.5 minbe = 12.5
104 % Nodes % Nodes MinBE = 11.5, 8 MinBE = 11.5, 8.5 Δ = 5m Δ = 2m Δ = 5m Δ = 2m % Nodes % Nodes MinBE = 11.5, 9 MinBE = 11.5, 9.5 Δ = 5m Δ = 2m Δ = 5m Δ = 2m Goodput Figure 4.19: Goodput distribution for dual CSMA configuration. Varying the minbe of the nodes in the sparse area. minbe = 9.5 minbe minbe minbe minbe = 8
105 % Nodes MinBE = 1, 9 dense sparse % Nodes MinBE = 1.5, 9 dense sparse % Nodes MinBE = 11, 9 dense sparse % Nodes MinBE = 11.5, 9 dense sparse % Nodes MinBE = 12, 9 dense sparse Goodput Figure 4.2: Goodput distribution for dual CSMA configuration. Varying the minbe of the nodes in the dense area. minbe
106 16 14 Δ=5m Δ=2m 12 Goodput (x1) MinBE Figure 4.21: Network goodput for single CSMA configuration. minbe minbe minbe minbe minbe = 1 minbe minbe minbe
107 % Nodes MinBE = 8 dense sparse % Nodes MinBE = 8 dense sparse % Nodes MinBE = 9 dense sparse % Nodes MinBE = 9 dense sparse % Nodes MinBE = 1 dense sparse % Nodes MinBE = 1 dense sparse % Nodes MinBE = 11 dense sparse % Nodes MinBE = 11 dense sparse % Nodes MinBE = 12 dense sparse % Nodes MinBE = 12 dense sparse Goodput (a): Goodput distribution TX Success Ratio (b): TX Success ratio Figure 4.22: Distribution of goodput and transmission success ratio for single CSMA configuration.
108 minbe minbe = 8 minbe minbe = 11.5 minbe = 9
109 A B C Figure 4.23: Illustration of the problem of interference. The interference range is depicted with dashed lines whereas the transmission range with filled circle.
110 B A C B B A C
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115 Parameter Value Uniform Topology Network Size (N) 529 Nodes Distribution random Inter-node Distance ( ) 15m APP Layer Number of Messages 1 NET Layer Config 1 Protocol Gossip3 Fwd. Probability (p).. 1 Compensation factor (m) 1 Flooding Hops (k) NET Layer Config 2 Protocol Adaptive Gossip3 MAC Layer Protocol CSMA Backoff constant MinBE Table 5.1: Experimental settings divided by protocol stacks
116 GOSSIP3: Fwd Probability GOSSIP3: Fwd Probability CSMA: MinBE (a): Coverage CSMA: MinBE (b): Fraction of forwarders GOSSIP3: Fwd Probability GOSSIP3: Fwd Probability CSMA: MinBE (c): Forwarding Ratio CSMA: MinBE (d): Latency 9% coverage Figure 5.1: Impact of CSMA and default Gossip3 parameters on message dissemination with synthetic traffic. Network size is 529 and nodes are distributed randomly with average inter-node distance = 15m. minbe = 15m = 5m, 1m, 2m minbe p minbe 1 p p.7 minbe = 8.5
117 minbe minbe 1 p p =.1 p =.2 p =.3 minbe minbe minbe p p p minbe minbe p minbe p minbe = 1, 1.5 p =.3 minbe minbe < 9 minbe minbe
118 Fraction coverage forwarders avg.fwd.ratio Time (s) coverage 7% coverage 8% coverage 9% MAC: minbe MAC: minbe (a): Dissemination Performance (b): Dissemination latency Figure 5.2: Impact of CSMA parameter, minbe, on message dissemination through adaptive Gossip3. Network size is 529 and nodes are distributed randomly with average inter-node distance = 15m. minbe minbe minbe minbe = 1 minbe = 1.5 = 15m
119 Parameter Value Topology Network Size (N) 529 Nodes Distribution random Inter-node Distance ( ) 15m APP Layer Source nodes 529 Messages sent by each source 5 Message Insertion Rate (network) 1, 5, 1, 15 msg/s Period of inserting new message 52.9, 1.6, 5.3, 3.5 s NET Layer Protocol Adaptive Gossip3 MAC Layer Protocol CSMA Backoff constant MinBE Buffer Size 2 Table 5.2: Experimental settings divided by protocol stacks. = 15m minbe minbe >= 1
120 minbe=8 minbe=9 minbe=1 minbe=11 minbe=12 minbe=8 minbe=9 minbe=1 minbe=11 minbe= coverage (% nodes) fwd ratio msg insertion rate (mps) msg insertion rate (mps) (a): Coverage (b): Fwd probability # rebroadcasts (x1) time (s) msg insertion rate (mps) msg insertion rate (mps) (c): Num. Rebroadcasts (d): Dissemination Latency # buffer overflow (x1) msg insertion rate (mps) (e): Buffer overflow Figure 5.3: Performance of adaptive Gossip3. Evaluation of various configurations of the CSMA with various message generation rates. Nodes are randomly distributed with average inter-node distance = 15m.
121 minbe minbe = 8 minbe = 1 minbe minbe minbe minbe minbe = 12 minbe = 9 minbe = 12 minbe = 9 minbe = 9 minbe = 12 minbe = 9 minbe = 1 2 minbe
122 GOSSIP3: fwd probability FILE u 5:($8/1): GOSSIP3: fwd probability FILE using 5:($8/1): CSMA: minbe CSMA: minbe (a): Coverage (b): Forwarders GOSSIP3: fwd probability FILE using 5:($8/1): GOSSIP3: fwd probability FILE using 5:($8/1): CSMA: minbe CSMA: minbe (c): Forwarding Ratio (d): Latency 9% coverage Figure 5.4: Impact of CSMA and Gossip3 parameters on message dissemination. Message generation rate is fixed to 5 mps. Network size is 529 and nodes are distributed randomly with inter-node distance = 15m.
123 p p = p minbe minbe = 1 p =.2 minbe = 12 p =.2 p minbe p
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PEDAMACS: Power efficient and delay aware medium access protocol for sensor networks
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