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Fine-Grained Network Time Synchronization using Reference Broadcasts

Fine-Grained Network Time Synchronization using Reference Broadcasts. Jeremy Elson, Lewis Girod, and Deborah Estrin U.C.L.A Presenter: Todd Fielder. Time Synchronization. Applications to Sensor Networks Security Cryptography Coordinate Future Action Domain Specific:

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Fine-Grained Network Time Synchronization using Reference Broadcasts

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  1. Fine-Grained Network Time Synchronization using Reference Broadcasts Jeremy Elson, Lewis Girod, and Deborah Estrin U.C.L.A Presenter: Todd Fielder

  2. Time Synchronization • Applications to Sensor Networks • Security • Cryptography • Coordinate Future Action • Domain Specific: • Integrate proximity detections into a velocity estimate • Suppress redundant messages by recognizing duplicated sensed events.

  3. Sources of Time Synchronization Errors • Send Time • Message construction time varies among senders • Non-determinant: Dependant on instantaneous load on CPU. • Access Time • Channel access time is indeterminate • Non-determinant: Dependant on instantaneous load on Network. • Propagation Time • Distance to receivers varies • Effectively zero: • RF close to speed of light • RBS only takes into account differences in distance of receivers • However: Increases if receivers are at different sides of sender. • Receive Time • Time to deliver to application varies • messages in queue can cause delay. • Mitigated by reading timestamp at interrupt time.

  4. Reference Broadcast Synchronization • Synchronizes a set of receivers with one another • Traditional method synchronizes senders with receivers. • Receivers use the arrival time of a ‘reference broadcasts’ as a point of reference for comparing their clocks. • Avoids errors due to Send Time and Access Time.

  5. Synchronization Algorithm • Phase Offset Estimation • Transmitter broadcasts a reference packet to two receivers. • Each receiver records the time according to its local clock. • Receivers Exchange their observations and synchronize with the average. • Synchronizes relative timescales. • Global time is not important in Sensor Networks. • Or is it?

  6. Synchronization Algorithm (cont.) • Estimation of Clock Skew • Accuracy • The agreement between an oscillator’s expected and actual frequencies. • Stability • An oscillator’s tendency to stay at the same frequency over time. • least-squares linear regression • Finds the best fit line through the phase error observations over time.

  7. Additional Comments • Requires additional overhead between all communicating nodes. • If two nodes cannot communicate directly, multi-hop communication is required or substantial message passing. • No energy usage graphs presented. • How does a node know if reference broadcasts is meant for it? • May cause nodes to unnecessarily expend energy to synchronize. • However, more efficient than traditional protocols because receivers do not need to maintain synchronization. • Can synchronize after hours or days of sleep. • Do receivers need to maintain synchronization in NTP?

  8. Experiment • Traffic scenarios: • Heavy traffic • Light traffic • Three synchronization techniques tested: • RBS-synchronizes receivers. • NTP-uses GPS and a NTP server to synchronize to an external timescale. • NTP offset-NTP limits rate at which to correct phase error this variation does not, in order to allow for more fair testing of synchronization precision.

  9. Experimental Results (application Level) • Light Traffic • RBS performed 8 times better than NTP • RBS: 6.29 +/- 6.45 usec. • Causes of jitter: • Code path through network stack • Time required to schedule daemon • System calls to get current time • NTP: 51.18 +/- 53.30 usec. • Heavy Traffic • RBS performance remained almost consistent while NTP performance degraded 30 fold • RBS: 8.44 usec • NTP: 1,542 usec *For reasons unknown, performance of NTP-offset was much worse than NTP.

  10. Experimental Results (Kernal Level) • Timestamps acquired at the network interrupt handler. • RBS performance improved considerably • 1.85 +/- 1.26usec. • Result limited by 1usec clock resolution

  11. Multi-Hop Synchronization • Nodes 1,2,3,4 synchronize to each other based on A’s broadcast. • Nodes 4,5,6,7 synchronize to each other based on B’s broadcast. • Node 4 is now common among all nodes and can synchronize A and B based on a best fit line. • At next reference broadcast, all nodes will be synchronized.

  12. Time Routing • Not necessary to have a common node actively synchronize two distinct regions. • Can dynamically determine the “time-route” for packets to be routed and converted on the fly. • Route packets through “gateway” node, which can determine conversion from one time base to another.

  13. Performance • Each conversion step can introduce error. • How is that error amplified as the hop-length increases? • Average per-hop error is e • For n hops, estimated error is e (n^1/2) • Experimental Results • For a 4 hop network, average error is 3.68 +/- 2.57usec.

  14. Additional Comments • Causes Gateway nodes to perform additional computation. • Is there a way to verify gateway node is not compromised? • Can C be a “watchdog” over 4,7,8,9 to ensure that all times reported are in a specified range? • Is there a way for C to Know that 8 and 9 should be reporting the same value, i.e. that they are both in the same region?

  15. External Timescales • Treat GPS as a Broadcasts Beacon. • To Work effectively, GPS must be attached to every Broadcast beacon in network. • Need to distribute additional computation load. • Time-routing causes some conversion between unsynchronized regions.

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