Energy-Aware Synchronization in Wireless Sensor Networks Yanos Saravanos Major Advisor: Dr. Robert...
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Transcript of Energy-Aware Synchronization in Wireless Sensor Networks Yanos Saravanos Major Advisor: Dr. Robert...
Energy-Aware Synchronization in Wireless Sensor NetworksYanos Saravanos
Major Advisor: Dr. Robert AklDepartment of Computer Science and Engineering
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Outline
Background on wireless sensor networks Flooding to create network topology Existing synchronization algorithms
Reference Broadcast Synchronization (RBS) Timing-sync Protocol for Sensor Networks (TPSN)
Hybrid algorithms Flooding Synchronization Root node re-election
Results Conclusions
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Wireless Sensors
Physically small sensing unit Battery Processor
Slow Drift
Radio/antenna Sensor modules
Covert Short battery life
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Applications
Temperature Fire detection Brake usage
Humidity Flood detection
Pressure Object tracking
Animal movement and migrations
Vehicle tracking
Noise levels Search and rescue efforts Locating a sniper’s
position Contamination levels
Monitoring pollution levels Chemical/biological agent
detection Mechanical stress on
supporting structures
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Wireless Sensor Network (WSN) Network using many
wireless sensors Dropped from a plane
to monitor area Random placement
Sensors build hierarchical network once deployed
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Wireless Communication
Signal strength decays over distance
PT: initial power of transmission d: distance from transmitter c: path loss coefficient
TR c
PP
d
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Network Flooding
Broadcast packet from root node If packet received for the first time
Set Parent on Tree = Source of message Change Source field to MyId Increment HopCount field Rebroadcast packet
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Network Flooding
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Motivation for Time Synchronization Most applications require some synchronization accuracy
Fire and flood tracking Animal movement Vehicle movement Gunshot detection
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Existing Synchronization Solutions Global Positioning System (GPS)
Power-hungry Network Time Protocol (NTP)
Computationally infeasible for wireless sensors
Reference Broadcast Synchronization (RBS) Receiver-receiver synchronization
Timing-sync Protocol for Sensor Networks (TPSN) Transmitter-receiver synchronization
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Reference Broadcast Synchronization Receiver-to-receiver synchronization
Two stages Transmitter broadcasts clock time Receivers exchange observations
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RBS Synchronization
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RBS Energy Usage
Given n receivers:
Transmissions grow as O(n) Receptions grow as O(n2)
21
1
( 1)
2 2
RBS
n
RBSi
TX n
n n n nRX n i n
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Timing-sync Protocol for Sensor Networks Traditional handshake approach
Timestamp at the MAC layer
Two stages Level Discovery Phase (Flooding) Synchronization Phase
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TPSN Model – Level Discovery Phase Assign root (level 0) node Broadcast level_discovery packet Nodes 1 hop away assigned to level 1
Ignore all subsequent level_discovery packets Broadcast level_discovery packet …
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TPSN Model – Synchronization Phase
( 2 1) ( 4 3)
2( 2 1) ( 4 3)
2
T T T T
T T T Td
Each node (A) broadcasts synchronization_pulse Timestamped at T1
Node B receives pulse at T2, broadcasts ack at T3
Node A receives ack at T4
Δ is clock drift
d is propagation delay
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TPSN Synchronization
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TPSN Energy Usage
Given n receivers:
Transmissions and receptions grow as O(n)
Large energy savings over RBS for large n Less efficient for small n
1
2TPSN
TPSN
TX n
RX n
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Sources of Packet Delay
Send time: time to create the packet Access time: delay until channel is accessible Transmission time: time each bit takes to get onto physical
medium Reception time: time to receive bits off physical medium Receive time: time to reconstruct packet
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Uncertainties
4 1 4
4 1 4
1
2A B UC UC UC A B
TPSN t t t
A B UC UC A BRBS t D t t
Error D S P R RD
Error D P R RD
Sender uncertainty RBS removes it completely Minimized in TPSN by timestamping at MAC layer
Propagation/receiver uncertainties, and relative local clock drifts TPSN outperforms RBS by factor of 2
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Accuracy Comparison
TPSN RBS
Avg error (μs) 16.9 29.1
Worst-case error (μs) 44 93
Best-case error (μs) 0 0
% time error < avg 64 53
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Hybrid Summary
Complete system for WSN operation Three stages
Build hierarchical tree with flooding Transmitters know how many receivers are connected
Periodically synchronize sensors Re-elect new root when current one dies
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Hybrid Flooding Algorithm
Broadcast flood_packet from root node If current_node receives flood_packet
Set parent of current_node to source of broadcast Set current_node_level to parent’s node level + 1 Rebroadcast flood with current_node_ID and
current_node_level Broadcast ack_packet with current_node_ID Ignore subsequent flood_packets
Else If current_node receives ack_packet Increment num_receivers
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Hybrid Synchronization
RBS best for small n, TPSN best for large n Calculate optimal cutoff value to choose RBS
or TPSN algorithm (receiver_threshold) Transmissions and receptions draw different
current
where α is reception-to-transmission current ratio
,RBS RBS TPSN TPSNTX RX TX RX
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Hybrid Synchronization
Equate energies of both RBS and TPSN
Solve equation to find receiver_threshold
2
2
2
2
1 22
12
224
23 0
n nn n a n
n nn
n n n
n n
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Reception-to-Transmission Ratio Mica2DOT architecture
TX: 25 mA RX: 8 mA
α=0.32 n=4.4
MicaZ architecture TX: 14.0 mA RX: 19.7 mA
α=1.41 n=3.4
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Hybrid Synchronization Algorithm If num_receivers < receiver_threshold
Transmitter broadcasts sync_request For each receiver
Record local time of reception for sync_request Broadcast observation_packet Receive observation_packet from other receivers
Else Transmitter broadcasts sync_request For each receiver
Record local time of reception for sync_request Broadcast ack_packet to transmitter with local time
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Hybrid Synchronization
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Hybrid Root Election Algorithm If root node’s power allows 1 more TX
Broadcast elect_packet with cur_node_ID If cur_node_level == 2 and receives elect_packet
from root Broadcast elect_packet with cur_node_ID,
cur_node_power If cur_node receives elect_packet and elect_packet_power
>= cur_node_power Set elect_packet_ID to root node
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Simulation Results
Two sets of simulations Change the sensor architecture Change the number of sensors in network
1000m x 1000m Path loss coefficient = 3.5 20 networks per simulation
Assume perfect directional antennas Minimum number of receptions
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Sensor Synchronization Simulations Verify the hybrid synchronization algorithm
works with several sensor architectures Run RBS, TPSN, hybrid using optimal
receiver_threshold Run hybrid using non-optimal receiver_threshold
values Change sensor architecture
Used 500 sensors per network
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Sensor Synchronization Simulations Mica2DOT
TX: 25 mA RX: 8 mA
α=0.32 n=4.4
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Sensor Synchronization Simulations MicaZ
TX: 17.4 mA RX: 19.7 mA
α=1.41 n=3.4
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Sensor Synchronization Simulations Hypothetical
TX: 25 mA RX: 2.7 mA
α=0.11 n=6.1
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Sensor Synchronization Simulations Hypothetical
TX: 25 mA RX: 0.7 mA
α=0.03 n=10.3
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Synchronization Simulations forVariable Network Size Verify the hybrid synchronization algorithm
works with various network sizes Run RBS, TPSN, hybrid using optimal
receiver_threshold Run hybrid using non-optimal receiver_threshold
values Change number of sensors deployed in network
Used Mica2DOT architecture
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Synchronization Simulations for 250 Sensors
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Synchronization Simulations for 500 Sensors
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Synchronization Simulations for 750 Sensors
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Synchronization Simulations for 1000 Sensors
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Synchronization Simulations for 1250 Sensors
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Synchronization Simulations for 1500 Sensors
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Network Size Simulations
Sensors 250 500 750 1000 1250 1500
RBS 446 1046 1844 2762 3756 5060
TPSN 511 983 1434 1885 2331 2770
Hybrid 404 828 1253 1672 2095 2514
RBS Savings 9.29% 20.79% 32.04% 39.46% 44.22% 50.31%
TPSN Savings 20.80% 15.73% 12.65% 11.28% 10.11% 9.23%
Hybrid saves up to 50% over RBS, up to 20% over TPSN Hybrid is still more efficient in networks favoring either RBS or
TPSN
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Conclusions
Synchronization is necessary for most sensor networks to operate effectively
Both TPSN and RBS synchronize sensor clocks locate origin of gunshot blast
Neither TPSN nor RBS are designed for low energy usage
Hybrid algorithm adapts to any size network and saves energy over other algorithms
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Future Work
Physical implementation Localized re-flooding Non-uniform path loss coefficient Dropped packet analysis
Questions?