1. Rizwan Mumtaz RWTH Aachen University 2 nd COST0804 Training School Balearic Island University Analysis of WSN Routing Protocols for Multiple Traffic Patterns Presenter: Rizwan Mumtaz University of Trento, Italy & RWTH Aachen University Germany In collaboration with Fondazione Bruno Kessler (FBK) Supervisor: Prof. Gian Pietro Picco, Unitn Trento Second reader: Prof. Klaus Wehrle, RWTH Aachen Adviser: Dr. Amy L. Murphy, FBK

2. Rizwan Mumtaz RWTH Aachen University 2 nd COST0804 Training School Balearic Island University Background Wireless Sensor Networks (WSNs) are networks for collecting data from a large environments. Composed of spatially distributed miniature nodes equipped with various sensors e.g. temperature, pressure, sound, vibrations, light and motion sensors. Applications: – Sensing + CPU + Radio = Thousands of potential applications

3. Rizwan Mumtaz RWTH Aachen University 2 nd COST0804 Training School Balearic Island University Some applications Habitat Monitoring Seismic structural Response Building Monitoring Agriculture A Generic WSN

4. Rizwan Mumtaz RWTH Aachen University 2 nd COST0804 Training School Balearic Island University Challenges in WSNs Limited availability of sensor nodes’ resources in – Processing – Power – Memory – Storage Applications demands – High throughput requirements – Low power consumption/longer network life time How to handle these challenges? – Optimization needed across all layers of protocol stack Hardware Link Layer MAC Layer Routing Application

5. Rizwan Mumtaz RWTH Aachen University 2 nd COST0804 Training School Balearic Island University Energy Efficiency and Routing in WSNs Multiple rate applications: A scenario

6. Rizwan Mumtaz RWTH Aachen University 2 nd COST0804 Training School Balearic Island University The Problem, Existing Solutions & their limitations Temp monitoring: Sampled at the order of one message in several mins. CTP, MultihopLQI,Dozer, CentRoute etc.. Surveillance systems: Sampled at the order of several messages per second. Wisden, QCRA, IRFC, RCRT etc.. Compressed accelerometer bulk data, 100k byte in 10 mins. Packet s inter-related. Single packet loss jeopardize the whole bulk. RBC, KOALA, RMST, FLUSH etc.. Limitations: – All protocols support uniform data rate. – In presence of multiple rate traffic the protocols use conservative approach for resource utilization. E.g: Temperature readings and accelerometer data on collected from the same network.

7. Rizwan Mumtaz RWTH Aachen University 2 nd COST0804 Training School Balearic Island University Existing Solutions Low Rate E.g., temperature 1 msg per 10 min High Rate E.g., surveillance 3 msgs per sec Bulk Transfer E.g., accelerometer 100k (1422msgs) per 10 min CTP, MultihopLQI,Dozer, CentRoute etc Wisden, QCRA, IRFC, RCRT RBC, KOALA, RMST, FLUSH etc.. Limitations: – All protocols support uniform data rate. – In presence of multiple rate traffic the protocols use conservative approach for resource utilization. E.g: Temperature readings and accelerometer data on collected from the same network.

8. Rizwan Mumtaz RWTH Aachen University 2 nd COST0804 Training School Balearic Island University Traffic Patterns in WSNs Low-rate data – Send and received in the order of minutes. E.g. temperature monitoring of a building High rate data – Send and received in the order of seconds/milliseconds. E.g. military surveillance systems Bulk Transfers – Long bursts of contiguous data packets inter-related to each other – Different from high-rate data in the sense that all packets of a particular burst must be received or otherwise the entire burst is useless – Loss of single packet jeopardizes the whole burst – E.g. Accelerometer data Multiple Traffic Patterns – Different combination of the above.

9. Rizwan Mumtaz RWTH Aachen University 2 nd COST0804 Training School Balearic Island University Thesis Goals and Outline Understand and analyze how/when do low-rate protocols fail for bulk transfer. – Analysis of Collection Tree Protocol Investigate the performance of a protocol designed for multiple traffic patterns. – Analysis of PLEX Combined Analysis

10. Rizwan Mumtaz RWTH Aachen University 2 nd COST0804 Training School Balearic Island University Outline Background of the topic Thesis Goals Experimental Methodology The Collection Tree Protocol – Analysis of Collection Tree Protocol PLEX: An alternate solution – Analysis of PLEX Conclusions Q & A

11. Rizwan Mumtaz RWTH Aachen University 2 nd COST0804 Training School Balearic Island University Experimental Methodology Testbed at FBK TelosB motes RatLab at FBK 50 TelosB motes TinyOS 2.x system RatLab at FBK 50 TelosB motes TinyOS 2.x system Analysis of CTP Criteria for Analysis – Application packet delivery ratio – Burst delivery ratio – Power consumption Criteria for Analysis – Application packet delivery ratio – Burst delivery ratio – Power consumption

12. Rizwan Mumtaz RWTH Aachen University 2 nd COST0804 Training School Balearic Island University Widely regarded as a reference protocol for performing data collection in WSNs Specifications provided in TinyOS 2.x platform Key Functionalities: – Provides “best effort anycast datagram communication to one of the collection roots in a network ” – Uses a tree based network topology to collect the data from the network at sink(s) – Uses broad cast beacons in an adaptive fashion (Trickle Algorithm) to discover topology rooted at one or more sink(s) – Build tree with good links – Uses ETX as a cost metric for routing paths – Repair broken links on demand Collection Tree Protocol (CTP) Collection Tree

13. Rizwan Mumtaz RWTH Aachen University 2 nd COST0804 Training School Balearic Island University Case –I: Uniform data-rate Analysis Testbed Settings – 1 sink – 49 source nodes – Max diameter of network = 4 hops Experimental Settings – MAC Protocol CSMA Box-MAC with sleep intervals of 50ms, 250ms, 500msec – Application packet sending rate (Inter-Packet Interval (IPI): 10sec, 30sec, 5min Analysis of CTP

14. Rizwan Mumtaz RWTH Aachen University 2 nd COST0804 Training School Balearic Island University LPL = 250ms, IPI = 10sec Average Throughput Table: CTP Avg. Throughput Analysis of CTP CTP Delivery Ratio over time Time (sec) Avg. Delivery Ratio Fluctuating throughput but stays above 90% Control overhead and duty cycle details are in the thesis. Uniform rate

15. Rizwan Mumtaz RWTH Aachen University 2 nd COST0804 Training School Balearic Island University Control Overhead LPL = 250ms, IPI = 10sec Retransmissions rate Analysis of CTP application vs control pkts Time (sec) No. of Retransmissions IPI No. of Beacons Time (sec) No. of messages No. of Retransmissions Node ID Control overhead Node 10 has a poor link to parent Adaptive beaconing rate at startup and on demand Uniform rate

16. Rizwan Mumtaz RWTH Aachen University 2 nd COST0804 Training School Balearic Island University Energy Consumption (Duty Cycle) Observations: Duty cycle is higher for smaller IPI decreases with increased sleep intervals Observations: Duty cycle is higher for smaller IPI decreases with increased sleep intervals Avg. Duty Cycles Analysis of CTP Uniform rate

17. Rizwan Mumtaz RWTH Aachen University 2 nd COST0804 Training School Balearic Island University Case –II Multiple Traffic Patterns Testbed Settings – 1 sink – 49 source nodes – Max diameter of network = 4 hops Experimental Settings – Box-MAC with sleep interval = 250ms – IPI for low rate data = 60sec – Burst after every 90sec – Burst size = 50 packets – Number of Burst generating sources: 0, 4, 8, ……… – All other nodes as low rate sources. Analysis of CTP

18. Rizwan Mumtaz RWTH Aachen University 2 nd COST0804 Training School Balearic Island University Burst Delivery Ratio Avg. Delivery Ratio Analysis of CTP Overall packet delivery ratio Normal/Bursty Avg. Delivery Ratio (%) Normal/Bursty Very good overall throughput 0% packet loss 2% packet loss 4% packet loss 6% packet loss 8% packet loss Poor Burst delivery CTP fails for burst transfer..!!! Multiple rate

19. Rizwan Mumtaz RWTH Aachen University 2 nd COST0804 Training School Balearic Island University CTP Control Overhead LPL = 250ms, IPI = multiple Analysis of CTP Normal/Bulky No. of messages Normal/Bulky) No. of messages Total no. of messages generatedNo of control messages Control Overhead increases with increase in bulk sources Multiple rate

20. Rizwan Mumtaz RWTH Aachen University 2 nd COST0804 Training School Balearic Island University Duty Cycle per node Total No. of messages per node Analysis of CTP Power Consumption (Duty Cycle) Node ID No. of messages Duty cycle (%) Node ID Normal/Bulky Duty cycle (%) Min. duty cycle is constant Min. Duty Cycle Avg. Duty Cycle Avg. duty cycle grows with increasing bulk sources Multiple rate

21. Rizwan Mumtaz RWTH Aachen University 2 nd COST0804 Training School Balearic Island University Discussion: What CTP fails at? Provides very good data yield but does not scale well for burst data transfers. Tends to lose application packets at regular intervals – Jeopardizing the burst transfers Power consumption is inefficient. – Radio duty cycling on a network-wide basis according to high rate demand. – Power wastage on nodes sending only a single message during long intervals of time.

22. Rizwan Mumtaz RWTH Aachen University 2 nd COST0804 Training School Balearic Island University PLEX Developed by D3S group at University of Trento, Italy and Fondazione Bruno Kessler (www.fbk.eu) Implemented in TinyOS 2.0.1 Real world deployments: TRITon Project. Key Functionalities: – Aims to provides reliable routing solution for multiple traffic patterns on top of single routing tree – Broadcast tree building messages (beacons) at startup and after a configurable fixed amount of time. – Uses LQI as a cost metric for routing paths – Repair broken links after fixed amount of time.

23. Rizwan Mumtaz RWTH Aachen University 2 nd COST0804 Training School Balearic Island University Salient features supporting burst transfers Avoid parent change on a path forwarding burst traffic Hop-by-hop Packet Recovery Congestion Control Different sleep intervals for nodes part of burst traffic Parent change for burst nodes Hop-by-hop Packet Recovery

24. Rizwan Mumtaz RWTH Aachen University 2 nd COST0804 Training School Balearic Island University Analysis of PLEX Average Throughput PLEX Table: PLEX Avg. Throughput different experiments PLEX Avg. Delivery Ratio over time Time (sec) Avg. Delivery Ratio Avg. duty cycle fluctuctuates

25. Rizwan Mumtaz RWTH Aachen University 2 nd COST0804 Training School Balearic Island University PLEX Burst Delivery Ratio Burst Delivery Ratio PLEX Time (sec) Avg. Delivery Ratio Burst Delivery Ratio 0% packet loss 2% packet loss 4% packet loss 6% packet loss 8% packet loss Poor Burst delivery

26. Rizwan Mumtaz RWTH Aachen University 2 nd COST0804 Training School Balearic Island University PLEX Control Overhead Tree building messages PLEX Tree building msgs only at startup and at fixed intervals Normal/Bulky No. of messages Normal/Bulky) No. of messages Normal/Bulky No. of messages Recoveries Congestions Total messages Huge number of recovery messages

27. Rizwan Mumtaz RWTH Aachen University 2 nd COST0804 Training School Balearic Island University Did PLEX fail?? What is good? – PLEX is the presentation of new concepts to deal burst traffic. – The ideas are promissing What is bad? – The current implementation fails. How to proceed? – Thorough code debugging needed. – Investigate each novel feature separately – Check PLEX core design – Test PLEX ideas by integrating it into a stable protocol

28. Rizwan Mumtaz RWTH Aachen University 2 nd COST0804 Training School Balearic Island University Integrate PLEX Features into CTP Stick to same parent for an extra fraction of time Implement hop-by-hop recovery mechanism Integrate Congestion Control method Need-based approach for nodes’ duty cycling

29. Rizwan Mumtaz RWTH Aachen University 2 nd COST0804 Training School Balearic Island University Conclusions CTP – provides a very good PDR but fails for burst transfers. – is inefficient in terms of resources utilization in presence of multiple rate traffic. PLEX – uses a different approach to treat burst in a special manner. – provides an optimal approach for resource utilization. – verification of concepts required. Integration of PLEX features into CTP – integrate individual concepts of PLEX into CTP.

30. Rizwan Mumtaz RWTH Aachen University 2 nd COST0804 Training School Balearic Island University Questions! Thanks for your attention!