Reliable Bursty Convergecast in Wireless Sensor Networks
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April 19, 2023
Reliable Bursty Convergecast in Wireless Sensor Networks
Hongwei Zhang, Anish Arora Young-ri Choi, Mohamed Gouda
Thanks: Lites & ExScal teams
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Application context
A Line in the Sand (Lites)
field sensor network experiment for real-time target
detection, classification, and tracking
A target can be detected by tens of nodes
Traffic burst
Bursty convergecast
Deliver traffic bursts to a base station nearby
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Problem statement
Only 33.7% packets are delivered with the default
TinyOS messaging stack
Unable to support precise event classification
Our objectives
Close to 100% reliability
Close to optimal event goodput (real-time)
Experimental study for high fidelity
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Outline
Testbed
Limitations of two commonly used mechanisms
Protocol RBC
Experimental results
Concluding remarks
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Network setup
Network
49 MICA2s in a 7 X 7 grid
5 feet separation
Power level: 9 (for 2-hop
reliable communication
range)
Logical Grid Routing (LGR)
It uses reliable links
It spreads traffic uniformly
base station
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Traffic trace from Lites
Packets generated in a 7 X 7 subgrid, when a vehicle passes across the middle of the Lites network
Optimal event goodput:
6.66 packets/second0 5 10 150
20
40
60
80
100
Time (seconds)
# o
f pa
cke
ts g
en
era
ted
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Outline
Testbed
Limitations of two commonly used mechanisms
Protocol RBC
Experimental results
Concluding remarks
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Retransmission based packet recovery
At each hop, retransmit a packet if the corresponding
ACK is not received after a constant time
Synchronous explicit ack (SEA)
Explicit ACK immediately after packet reception
Shorter retransmission timer
Stop-and-wait implicit ack (SWIA)
Forwarded packet as an ACK
Longer retransmission timer
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SEA
Retransmission does not
help much, and may
even decrease reliability
and goodput
Similar observations
when adjusting
contention window of B-
MAC and using S-MAC
Retransmission-incurred
contention
Metrics RT= 0 RT= 1 RT= 2
Reliability (%) 51.05 54.74 54.63
Delay (sec) 0.21 0.25 0.26
Goodput (pkt/sec) 4.01 4.05 3.63
0 5 10 150
20
40
60
80
100
Time (seconds)
# o
f pa
cke
ts r
ece
ive
d RT = 0RT = 1RT = 2
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SWIA
Again, retransmission
does not help
Compared with SEA,
longer delay and lower
goodput/reliability
longer retransmission
timer & blocking flow
control
More ACK losses, and
thus more
unnecessary
retransmissions
Metrics RT= 0 RT= 1 RT= 2
Reliability (%) 43.09 31.76 46.5
Delay (sec) 0.35 8.81 18.77
Goodput (pkt/sec) 3.48 2.58 1.41
0 5 10 15 20 25 30 350
20
40
60
80
100
Time (seconds)
# o
f pa
cke
ts r
ece
ive
d RT = 0RT = 1RT = 2
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Outline
Testbed
Limitations of two commonly used mechanisms
Protocol RBC
Experimental results
Concluding remarks
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Protocol RBC
Differentiated contention control
Reduce channel contention caused by packet retransmissions
Window-less block ACK
Non-blocking flow control
Reduce ack loss
Fine-grained tuning of retransmission timers
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Window-less block ACK
Non-blocking window-less queue management Unlike sliding-window based black ACK, in order packet delivery
is not considered Packets have been timestamped
For block ACK, sender and receiver maintain the “order” in which packets have been transmitted
“order” is identified without using sliding-window, thus there is no upper bound on the number of un-ACKed packet transmissions
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Sender: queue management
static
physical queue
ranked
virtual queues (VQ)
VQ0 1 2
VQ1 3 4 5
VQM
VQM+1 6
high
low
occu
pie
dem
pty
ID of buffer/packet
M: max. # of retransmissions
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Sender: gets a packet from an upper layer
VQ0 1 2
VQ1 3 4 5
VQM
VQM+1 6
empty queue buffer?
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Sender: transmits a packet
VQ0 1
VQ1 3 4 5
VQM
VQM+1 6
2
1,
earlier later
2
order of transmission
fresher
older
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Receiver: loss detection
i i, j
if no packet loss, expecting packet
j
i’
=
no loss
some loss
i’ = j
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Receiver: block ACK
i j
i, j
k
i, k i, i
k’
i, k’
ACK replication !
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Sender: processes a block ACK
VQ0 1 2
VQ1 3 4 5
VQM
VQM+1 6
3, 5
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Differentiated contention control
Schedule channel access across nodes
Higher priority in channel access is given to
nodes having fresher packets
nodes having more queued packets
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Implementation of contention control
The rank of a node j = M - k, |VQk|, ID(j) , where
M: maximum number retransmissions per-hop
VQk: the highest-ranked non-empty virtual queue at j
ID(j): the ID of node j
A node with a larger rank value has higher priority
Neighboring nodes exchange their ranks Lower ranked nodes leave the floor to higher ranked ones
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Fine tuning retransmission timer
Timeout value: tradeoff between
delay in necessary retransmissions
probability of unnecessary retransmissions
In RBC
Dynamically estimate ACK delay
Conservatively choose timeout value; also
reset timers upon packet and ACK loss
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Outline
Testbed
Limitations of two commonly used mechanisms
Protocol RBC
Experimental results
Concluding remarks
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Event-wise
Retransmission helps
improve reliability and
goodput
close to optimal
goodput (6.37 vs.
6.66)
Compared with SWIA,
delay is significantly
reduced
1.72 vs. 18.77 seconds
Metrics RT= 0 RT= 1 RT= 2
Reliability (%) 56.21 83.16 95.26
Delay (sec) 0.21 1.18 1.72
Goodput (pkt/sec) 4.28 5.72 6.37
0 5 10 150
20
40
60
80
100
Time (seconds)
# o
f pa
cke
ts r
ece
ive
d RT = 0RT = 1RT = 2
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Distribution of packet generation and reception
RBC
Packet reception
smoothes out and almost
matches packet
generation
SEA
Many packets are lost
despite quick packet
reception
SWIA
Significant delay and
packet loss
0 10 20 30 400
20
40
60
80
100
Time (seconds)
# o
f pa
cke
ts
Lites traceSEASWIARBC
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Breakdown of RBC
Metrics RT= 0 RT= 1 RT= 2
Reliability (%)RBC 56.21 83.16 95.26
RBC-NoDiffCtrl 54.90 77.19 82.29
Latency (sec)RBC 0.21 1.18 1.72
RBC-NoDiffCtrl 0.22 1.12 1.52
Goodput
(pkt/sec)
RBC 4.28 5.72 6.37
RBC-NoDiffCtrl 4.04 4.13 4.12
RBC-NoDiffCtrl: RBC without Differentiated Contention Control
Contention control plays an increasingly important role as RT (thus channel contention) increases
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Field deployment
A Line in the Sand (Lites)
~ 100 MICA2’s
10 X 20 meter2 field
Sensors: magnetometer, micro impulse radar (MIR)
ExScal
~ 1,000 XSM’s, ~ 200 Stargates
288 X 1260 meter2 field
Sensors: passive infrared radar (PIR), acoustic
sensor, magnetometer
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Outline
Testbed
Limitations of two commonly used mechanisms
Protocol RBC
Experimental results
Concluding remarks
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Concluding remarks
With its unique traffic pattern and performance requirements, bursty convergecast
poses new challenges to error control Non-blocking packet delivery Retransmission scheduling
also offers opportunities E.g., reorder-tolerance
Other applications Continuous event convergecast Data aggregation
to use explicit ack
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