1. 1 Segal’s Law A man with a watch knows what time it is. A man with two watches is never sure.

2. Fasika Assegei 2 Decentralized Frame Synchronization of a TDMA-based Wireless Sensor Network Fasika Assegei Advisors: Frits van der Wateren – Chess B.V. dr.ir. Peter Smulders – TU/e

3. 3 This research is …. DevLab project, a project to build a WSN for research on protocols, power management, programming models, and security. What is MyriaNed ? Conducted at Chess B.V. in Haarlem, the Netherlands. Part of MyriaNed project.

4. 4 Outline of presentation Synchronization in Wireless Sensor Networks What is the flaw with the Median algorithm ? Proposed algorithms Simulation Results Energy consumption Conclusion and future work

5. 5 Why synchronization? TDMA Slots Data Integration NTP Having the same notion of time

6. 6 Isn’t this a solved problem by now ??? NTP, time broadcasts (GPS, WWVB), high-stability oscillators (Rubidium, Cesium) New problems arise in Wireless Sensor Networks Important assumptions no longer hold (fewer resources -- such as energy, good connectivity, infrastructure, size, and cost -- are available) Sensor apps have stronger requirements (…but we have to do better than the Internet anyway) What now ?

7. 7 Previous works on synchronization of adhoc networks … Average / Median of the phase errors with the neighbors…..unstable in dynamic networks Decentralized synchronization using topology as a metric……….higher cost Interference elimination…..less time and costly Correlation of a sequence ……high cost

8. 8 What is done in this research … Decentralized synchronization Using estimation Tolerant to dynamic situations Energy efficient Unnecessary synchronization wastes energy, and insufficient synchronization leads to poor performance.

9. 9 Terms used in … Phase error Time difference between the clocks Frequency error The difference in the rates of the clocks Clock cycle (clk) The time between adjacent pulses of the oscillator Wakeup time The time that the node starts to listen Sleep

10. 10 Where does the error come from ? Oscillator characteristics: Accuracy: Difference between ideal frequency and actual frequency of the oscillator. Stability: Tendency of the oscillator to stay at the same frequency over time. Caused by different factors like temperature, aging, noise, … Network and System Parameters Receive and Transmit Delay: Time duration between message generation and network injection. Propagation Delay: Time to travel from sender to receiver. Access Delay: Time to access the channel.

11. 11 Nodes communicate …… Synchronization period: The period in which the network can stay synchronized without the application of the synchronization algorithm.

12. 12 Representation …… What is f ???

13. 13 Median as a method for synchronization Simple method. Calculates the Median of the phase errors Adjusts the offset in the next wakeup time of the node. With the simplicity, … Not stable in a highly dynamic networks. for all j neighbors..

14. 14 What is the flaw with Median ? Got message from Node 3 Calculating offset Got message from Node 10

15. 15 Node 9 drifted from its neighbors A WSN scenario for Median contd. Algorithms are proposed ….. Less time to synchronize …

16. 16 Building blocks of a sync protocol… Synchronization Parameter Space: (max error, lifetime, scope, convergence, stability,…)

17. 17 Weighted Measurements The larger the phase error is, the lower the pre-weight factor it is assigned. if Uses the weighted average of the phase errors

18. 18 Weighted Measurements Contd. Two scenarios ….. Case ICase II Weight factor determination: where Offset calculation:

19. 19 Least Squares approach... Set of n phase errors from n neighbors : Minimizing the squares of error : where: Iteration of parameters: Model Curve:

20. 20 Least Squares contd. Upper bound fits in the guard time ….

21. 21 Discrete time kalman filter Kalman filter estimates a process by using a form of feed forward control the filter estimates the process state at some time then obtains feedback in the form of noisy measurements. Time update equations Measurement Update equations Dynamic and recursive

22. 22 Kalman Filter Contd. A - relates the state at the previous time step to the current state H - relates the current state to the measurement R - process noise covariance Q - measurement noise covariance P - estimate error covariance

23. 23 Simulation setup Synchronization error : the maximum difference between the clock times in the neighborhood. clk : Clock cycle precision : metric to express the performance of the synchronization error KF – Kalman Filter WM – Weighted Measurements LS – Least Squares.

24. 24 Simulation results

25. 25 Simulation results contd.

26. 26 Putting in perspective …. Computing energy cost… Communicating energy gain…

27. 27 Putting in perspective … Tradeoff ? Comparison of the energy consumption and gain per RX slot

28. 28 ActiveIdle CPU3.5mA0.01mA Radio11.3mA(TX)900nA Radio12.3mA(RX)900nA Tradeoff ? Directly comparing computation/communication energy cost not possible but: put them into perspective! Energy ratio of “listening for 1 clk ” vs. “computing instruction for 1 clk ”: greater than 4 times Communication is more expensive than computing. The downside in implementation ……

29. 29 Conclusion Decentralized synchronization algorithms for a TDMA- based WSN are proposed using KF, WM and LS. WM and LS have a very good tolerance in a dynamic Wireless Sensor Network. KF performs very good in all synchronization space, both in static as well as dynamic environments. Reducing the communication cost and increasing cost of computing is worthy bait.

30. 30 To be explored … Software power minimization techniques to reduce the power consumption of the algorithms. Implementation of the algorithms on the MyriaNode and further investigation... Additional tools for frequency error minimization, using the available resources like temperature sensor.

31. 31 Thank you!

32. 32 Vraag?

33. 33 Not a perfect clock … The nodes clock time is thus bounded as : where ρ is the maximum clock drift. Factors affecting.. Temperature Aging Noise …

34. 34 Energy Consumption….. For 5 clk, an increase in battery life of up to half a year can be obtained. Battery power : 2400 mAhNo of slots: 10

35. 35 Reducing the duty cycle …….. A decrease in the duty cycle: For a performance improvement:

36. 36 Wireless Sensor Networks: Why different ? Energy limitation Limited battery life Dynamic nature of the network, as well as inaccessibility Mobility … Diverse applications Relative and absolute reference Cost factor... Large scale deployment …

37. 37 Lower bound of synchronization where n is the number of nodes in the network. This means that synchronization is not only a local property, in the sense that the clock skew between two nodes depends not only on the distance between the nodes but also on the size of the network.

38. 38 What causes the clock to drift ? The frequency of the clock is given as : a is the aging factor fe is the environmental factor (temperature..) f r is the noise instability f o is the nominal frequency where :

39. 39 What is synchronization ? Having the same time of reference and count the same time [e ither global (UTC) or local (relative)] Operate a system in unison Same notion of time We are synchronized!!!!

40. 40 Wireless Sensor Networks Wireless network of low cost sensors. Nodes communicate by broadcasting. Multihop communication needed in order to reach far-away destinations.

41. 41 Simulation setup MiximOctave Input Output

42. 42 Having no comment after the presentation is unacceptable.

43. 43 Synchronization Methods- Previously Centralized synchronization Central reference time Global or Relative Receiver-Receiver RBS ( Receiver Broadcast Synchronization)

44. 44 Synchronization Methods- Previously Decentralized synchronization Estimation of the other’s clock time

45. 45 Abstraction

46. 46 Simulation results contd.

47. 47 Simulation results contd.

48. 48 Simulation results contd.

49. 49 Simulation results contd.

50. 50 Simulation results contd.

51. 51 Simulation results contd.