1. Tarun Banka Department of Computer Science Colorado State University
PSFQ: A Reliable Transport Protocol for Wireless Sensor Networks
Chieh-Yih Wan, Andrew T. Campbell, Lakshman Krishnamurthy
Tarun Banka
Department of Computer Science
Colorado State University
December 8, 2018

2. Motivation ?
Most Sensor Network applications don’t need reliable transport
New applications like re-tasking of sensors need reliable transport
Current sensor networks are application specific and optimized for that only
Future Sensor networks may be general purpose to some extent – ability to reprogram the functionality
December 8, 2018

3. Probability of successful delivery using End to End Model1
(1-p) 2
n-1
(1-p)n-1 n
(1-p)n
p is the error rate of wireless link
between two hops
December 8, 2018

4. Goals of PSFQ: Pump Slowly and Fetch Quickly
Recover from losses locally
Minimum signaling involved for Loss
Detection and Recovery
To operate correctly in high error prone
environment
Independent of the underlying routing
infrastructure
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5. Multi-Hop Packet Forwarding1 2 3 4
When No Link Loss – Multi-Hop Forwarding takes place
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6. Recovering from Errors2 4 3 1
2 lost
Recover 2
Error Recovery Control Messages are wasted
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7. How PSFQ Recovers from Errors “Store and Forward”2 3 1 4
2 lost
Recover 2
No wastage of the Error Recovery control messages
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8. PSFQ Pump Schedule Tmin Tmax 2 1 t
If not duplicate and in-order and TTL not 0
Cache and Schedule for Forwarding at time t (Tmin<t<Tmax)
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9. “Fetch Quickly” Operation2 1
2 lost 3
Tmin
Tmax Tr
Recover 2
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10. “Proactive Fetch”
Tproc 1 2
last-1
last
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11. Performance Evaluation
Compare with SRM (Scalable Reliable Multicast)
Performance Metrics
Average Delivery Ratio
Average Latency
Average Delivery Overhead
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12. Experimental Setup 2 Mbps CSMA/CA Channel Access
Tmax = 100ms Tmin = 50ms Tr = 20ms
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13. Error Tolerance
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14. Average Latency
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15. Communication Cost for Reliability
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16. Conclusion - PSFQ Light weight and Energy efficient Simple mechanism
Scalable and robust
Need to be tested for high bandwidth applications
Cache size limitation
December 8, 2018

17. Department of Computer Science Colorado State University
CODA: Congestion Detection and Avoidance in Sensor Networks Chieh-Yih Wan, Shane B. Eisenman, Andrew T. Campbell
Tarun Banka
Department of Computer Science
Colorado State University
December 8, 2018

18. What is CODA ? Energy efficient congestion control scheme
Three mechanisms are involved
Congestion Detection
Open-loop hop-by-hop backpressure
Closed-loop multi-source regulation
December 8, 2018

19. Congestion Detection
Accurate and efficient congestion detection is important
Buffer queue length or Buffer occupancy – not a good measure of the congestion.
Channel loading – sample channel at appropriate time to detect congestion.
Report rate/Fidelity measurement – slow, observed over a longer period
December 8, 2018

20. Open-Loop Hop-by-Hop Backpressure6 1 2 4 5 3
Congestion detected
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21. Closed Loop Multi-Source Regulation1 2
1,2,3
ACK
4,5,6
Congestion detected
7,8
Regulate bit is set
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22. CODA Performance – Cost Metrics
Average Energy Tax =
Total Packets dropped in sensor NW /
Total Packets received at Sink
Average Fidelity Penalty =
Measures difference between average number of packets delivered
at a sink using CODA and using ideal congestion scheme
December 8, 2018

23. Simulation Setup
Random Network Topologies with network size from 30 to 120 nodes
2Mbps IEEE MAC (RTS/CTS are disabled)
Directed Diffusion is used as routing core
Fixed Work load, 6 Sources and 3 Sinks
Source generate data at different rates.
Event Packet is 64 bytes and an interest packet is 36 bytes
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24. Simulation Results (Case 1: Dense Source , High Rate)
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25. Simulation Results (Case 2: Sparse Sources, Low Rate)
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26. Simulation Results Case 2: Sparse Source, Low Rate
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27. Simulation Results (Case 3: Sparse Sources, High Rate)
Network Size (#no of nodes)
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28. Conclusion CODA is a energy efficient protocol
Can deal with Persistent and Transient Hotspots
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29. Thank you Questions!
December 8, 2018