Staffetta is a duty-cycling mechanism that improves opportunistic data collection in wireless sensor networks. Staffetta dynamically adjusts each node’s wake-up frequency, such that nodes closer to the sink are more active than nodes at the edge of the network.
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Staffetta: Smart Duty-Cycling for Opportunistic Data Collection
1. 1Challenge the future
STAFFETTA: exploit duty-cycling
for opportunistic data collection
M.Cattani, A.Loukas, M.Zimmerling, M.Zuniga, K.Langendoen
2. 2Challenge the future
Data collection in WSN:
problem statement
sender
receiver
rendezvous time
Sink is a special node that collect all information and has no
resource constraints
Nodes deliver their data to the sink over a multi-hop path and
are battery powered à duty cycle their radio
Duty cycle makes communication expensive due to the time
and energy required by nodes to rendezvous
Collect data from a wireless network as fast as
possible under severe resource constraints
3. 3Challenge the future
Data collection in WSN:
existing solutions
Choose as forwarder the
closest node to the sink
(shortest path)
Not always the fastest route
Best paths are over-used
Tree-based routing
(unicast primitive) next-hop
4. 4Challenge the future
Data collection in WSN:
existing solutions
From a set of best forwarders,
choose the first one to wake
up (fastest path)
Not always the shortest route
Robustness due to path
diversity
Opportunistic routing
(anycast primitive)forwarder set
5. 5Challenge the future
Data collection in WSN:
existing solutions
Choose as forwarder the
closest node to the sink
(shortest path)
Not always the fastest route
Best paths are over-used
Tree-based routing
(unicast primitive)
From a set of best forwarders,
choose the first one to wake
up (fastest path)
Not always the shortest route
Robustness due to path
diversity
Opportunistic routing
(anycast primitive)
6. 6Challenge the future
Data collection in WSN:
Staffetta’s idea
Bias opportunistic choices towards nodes closer
to the sink (fast choices are also the shortest)
7. 7Challenge the future
Data collection in WSN:
Staffetta’s idea
S
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tree-based opportunistic opportunistic
with staffetta
rendezvous timerendezvous time rendezvous time
Bias opportunistic choices towards nodes closer
to the sink (fast choices are also the shortest)
can take time to reach best forwarder
8. 8Challenge the future
Data collection in WSN:
Staffetta’s idea
S
1
2
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4
tree-based opportunistic opportunistic
with staffetta
rendezvous timerendezvous time rendezvous time
Bias opportunistic choices towards nodes closer
to the sink (fast choices are also the shortest)
the more forwarders, the faster (but longer paths)
9. 9Challenge the future
Data collection in WSN:
Staffetta’s idea
S
1
2
3
4
tree-based opportunistic opportunistic
with staffetta
rendezvous timerendezvous time rendezvous time
Bias opportunistic choices towards nodes closer
to the sink (fast choices are also the shortest)
the more active, the faster the forwarding
11. 11Challenge the future
Staffetta mechanism
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1) Exploit relation between the activity of nodes
and rendezvous time to create a gradient
sink
12. 12Challenge the future
Staffetta mechanism
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1) Exploit relation between the activity of nodes
and rendezvous time to create a gradient
2) Use Activity Gradient to improve the efficiency
of opportunistic data collection protocols
13. 13Challenge the future
How to create an activity gradient
a) Give to nodes a fixed energy budget (DCmax)
b) Let nodes wake up as frequently as possible
c) In the presence of a sink, obtain an activity gradient
1) Exploit relation between the activity of nodes
and rendezvous time to create a gradient
14. 14Challenge the future
0
5
10
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25
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WakeupFreq.[Hz]
Without Staffetta With Staffetta
0
30
60
90
120
150
Fwd.delay[ms]
Rendezvous w/o Staffetta Rendezvous Staffetta Data Transmission
10
15
20
25
30
yCycle[%]
DCmax
How to create an activity gradient
1) Exploit relation between the activity of nodes
and rendezvous time to create a gradient
0
5
10
15
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WakeupFre
0
30
60
90
120
150
Fwd.delay[ms]
Rendezvous w/o Staffetta Rendezvous Staffetta Data Transmission
0
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DutyCycle[%]
DCmax
1 2 3 4 5
Hops from Sink
Topology
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S
15. 15Challenge the future
How to exploit an activity gradient
2) Use Activity Gradient to improve the efficiency
of opportunistic data collection protocols
Shorter forwarding delays
Biased opportunistic choices (more likely to reach good nodes)
Exploit temporal links
Handle high traffic loads around the sink
Increased adaptability to network dynamics
19. 19Challenge the future
Latency improvements
EDC ST.EDC QB ST.QB RW ST.RW
0
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20
30
EDC ST.EDC QB ST.QB RW ST.RW
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Staffetta achieves low latencies by reducing
the forwarding time and the path length
pathlength[hop]
latency[s]
20. 20Challenge the future
Delivery Ratio improvements
EDC ST.EDC QB ST.QB RW ST.RW
0
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100
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200
EDC ST.EDC QB ST.QB RW ST.RW
0
0.2
0.4
0.6
0.8
1
Staffetta improves the delivery ratio by
reducing queue backlog (but ...)
latency[s]
deliveryratio
21. 21Challenge the future
Duty Cycle improvements
EDC ST.EDC QB ST.QB RW ST.RW
0
5
10
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Staffetta reduces the energy consumption
even if it increases the nodes’ activity
wakeupfreq.[Hz]
dutycycle[%]
EDC ST.EDC QB ST.QB RW ST.RW
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27. 27Challenge the future
Conclusion
Staffetta’s simple rule is able to
• Achieve desired network lifetime
• Adapt to network changes
and generate an activity gradient that
• Biases opportunistic choices towards the sink
• Reduces latency, path length and energy consumption
github.com/cattanimarco/Staffetta-Sensys-2016