Adaptive Protocols for Information Dissemination in Wireless Sensor Networks

1. Adaptive Protocols for Information Dissemination in Wireless Sensor Networks W.R.Heinzelman, J.kulik, H.Balakrishnan CS 599 Intelligent Embedded Systems

2. Outline • Introduction • SPIN • Other Data Dissemination Algorithms • Sensor Network Simulations • Conclusions • Strengths and Weaknesses CS 599 Intelligent Embedded Systems

3. Introduction • Wide deployment of Wireless sensor networks • Wireless sensor networks • Can aggregate sensor data to provide multi-dimensional view • Improve sensing accuracy • Focus on critical events (e.g. intruder entering) • Fault tolerant network • Can improve remote access to sensor data – sink nodes CS 599 Intelligent Embedded Systems

4. Introduction contd. • Limitations of Wireless sensor networks • Energy • Computation • Communication CS 599 Intelligent Embedded Systems

5. Sensor Protocols for Information via Negotiation (SPIN) • Classic flooding limitations • Implosion • Overlap • Resource blindness CS 599 Intelligent Embedded Systems

6. Implosion Problem CS 599 Intelligent Embedded Systems

7. Overlap problem CS 599 Intelligent Embedded Systems

8. SPIN contd.. • SPIN overcomes these deficiencies • Negotiation • Resource-adaptation • Each sensor node has resource manager • Keeps track of resource consumption • Applications probe the manager before any activity • Cut down activity to save energy • Motivated by principle of ALF • Common data naming (meta-data) CS 599 Intelligent Embedded Systems

9. SPIN Meta-Data • Sensors use meta-data to describe the sensor data briefly • If x is the meta-data descriptor for data X sizeof (x) < sizeof (X) • If x==y sensor-data-of (x) = sensor-data-of (y) • If X==Y meta-data-of (X) = meta-data-of (Y) • Meta-data format is application specific CS 599 Intelligent Embedded Systems

10. SPIN Messages • ADV – new data advertisement • REQ – request for data • DATA – data message ADV and REQ messages contain only meta-data so they are smaller in size. CS 599 Intelligent Embedded Systems

11. SPIN-1 and SPIN-2 • SPIN-1 • Simple 3-stage handshake protocol • Data aggregation is possible • Can adapt to work in lossy or mobile network • Can run in a completely unconfigured network CS 599 Intelligent Embedded Systems

12. Node B sends a REQ listing all of the data it would like to acquire. CS 599 Intelligent Embedded Systems

13. If node B had its own data, it could aggregate this with the data of node A and advertise. CS 599 Intelligent Embedded Systems

14. Nodes need not respond to every message CS 599 Intelligent Embedded Systems

15. SPIN-2 • SPIN-1 with a Low-Energy Threshold • When energy below energy threshold – stop participating in the protocol • Can just receive data avoiding ADV-REQ phase CS 599 Intelligent Embedded Systems

16. Other data dissemination algos. • Classic Flooding • Converges in O(d), d-diameter of the network • Gossiping • Forward data to a random neighbor • Avoids implosion • Disseminates at a slow rate • Fastest rate = 1 node/round CS 599 Intelligent Embedded Systems

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18. Ideal dissemination • Every node sends sensor data along shortest path • Receives each piece of distinct data only once • Implementation • Network level multicast (source specific) • To handle losses, reliable multicast has to be deployed • SPIN is a form of application-level multicast CS 599 Intelligent Embedded Systems

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20. Sensor Network Simulations • Simulated using ns simulator • Extended ns to create a Resource-Adaptive Node CS 599 Intelligent Embedded Systems

21. Simulation Testbed CS 599 Intelligent Embedded Systems

22. SPIN-1 Results • Higher throughput than gossiping • Same throughput as flooding • Uses substantially less energy than other protocols • SPIN-2 delivers more data per unit energy than SPIN-1 • SPIN-2 performs closer to Ideal dissemination • Nodes with higher degree tend to dissipate more energy than nodes with lower degree CS 599 Intelligent Embedded Systems

23. Data Acquired Over Time CS 599 Intelligent Embedded Systems

24. Energy Dissipated Over Time CS 599 Intelligent Embedded Systems

25. Energy Dissipated Over Time CS 599 Intelligent Embedded Systems

26. Unlimited Energy Simulations CS 599 Intelligent Embedded Systems

27. Limited Energy Simulations CS 599 Intelligent Embedded Systems

28. Limited Energy Simulations contd.. CS 599 Intelligent Embedded Systems

29. Best-Case Convergence Times • For overlapping sensor data • Convergence times for ideal and flooding are the same • For non-overlapping sensor data • Flooding converges faster than SPIN-1 • To understand these results, we develop equations that predict convergence times of each of these protocols. CS 599 Intelligent Embedded Systems

30. Transmission time per data packet = 8s/dSince SPIN-1 has to process ADV, REQ, DATA so processing time = 3(d+r) Convergence Time – no overlap CS 599 Intelligent Embedded Systems

31. Convergence Time – overlapping data CS 599 Intelligent Embedded Systems

32. For the testbed network parameters • Simulation results • Flooding converges in 135ms • Ideal converges in 125ms • SPIN-1 converges in 215ms • Convergence times of flooding and ideal are closer to their upper bound unlike SPIN-1 CS 599 Intelligent Embedded Systems

33. Conclusions • SPIN solves the implosion and overlap problems. • SPIN-1 and SPIN-2 are simple protocols for wireless sensor networks. • SPIN outperforms gossiping. • SPIN-1 consumes only 25% energy w.r.t flooding • SPIN-2 distributes 60% more data per unit energy w.r.t flooding. CS 599 Intelligent Embedded Systems

34. Strengths and Weaknesses • Implosion problem still exists in the REQ stage • The paper doesn’t consider the collisions in the REQ stage • No justification for the network parameters chosen i CS 599 Intelligent Embedded Systems

35. Questions ? CS 599 Intelligent Embedded Systems