Tarun Banka Department of Computer Science Colorado State University

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Presentation transcript:

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

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

Probability of successful delivery using End to End Model 1 (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

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 December 8, 2018

Multi-Hop Packet Forwarding 1 2 3 4 When No Link Loss – Multi-Hop Forwarding takes place December 8, 2018

Recovering from Errors 2 4 3 1 2 lost Recover 2 Error Recovery Control Messages are wasted December 8, 2018

How PSFQ Recovers from Errors “Store and Forward” 2 3 1 4 2 lost Recover 2 No wastage of the Error Recovery control messages December 8, 2018

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) December 8, 2018

“Fetch Quickly” Operation 2 1 2 lost 3 Tmin Tmax Tr Recover 2 December 8, 2018

“Proactive Fetch” Tproc 1 2 last-1 last December 8, 2018

Performance Evaluation Compare with SRM (Scalable Reliable Multicast) Performance Metrics Average Delivery Ratio Average Latency Average Delivery Overhead December 8, 2018

Experimental Setup 2 Mbps CSMA/CA Channel Access Tmax = 100ms Tmin = 50ms Tr = 20ms December 8, 2018

Error Tolerance December 8, 2018

Average Latency December 8, 2018

Communication Cost for Reliability December 8, 2018

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

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

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

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

Open-Loop Hop-by-Hop Backpressure 6 1 2 4 5 3 Congestion detected December 8, 2018

Closed Loop Multi-Source Regulation 1 2 1,2,3 ACK 4,5,6 Congestion detected 7,8 Regulate bit is set December 8, 2018

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

Simulation Setup Random Network Topologies with network size from 30 to 120 nodes 2Mbps IEEE 802.11 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 December 8, 2018

Simulation Results (Case 1: Dense Source , High Rate) December 8, 2018

Simulation Results (Case 2: Sparse Sources, Low Rate) December 8, 2018

Simulation Results Case 2: Sparse Source, Low Rate December 8, 2018

Simulation Results (Case 3: Sparse Sources, High Rate) Network Size (#no of nodes) December 8, 2018

Conclusion CODA is a energy efficient protocol Can deal with Persistent and Transient Hotspots December 8, 2018

Thank you Questions! December 8, 2018