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Modeling Clock Synchronization in the Chess gMAC WSN Protocol Mathijs Schuts Feng Zhu Faranak Heidarian Julien S

Modeling Clock Synchronization in the Chess gMAC WSN Protocol Mathijs Schuts Feng Zhu Faranak Heidarian Julien Schmaltz Frits Vaandrager. QFM’09 FM’09. Plan. Intro to WSN and Chess case study A first model + analysis A second model + counterexamples Conclusions & Future Work.

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Modeling Clock Synchronization in the Chess gMAC WSN Protocol Mathijs Schuts Feng Zhu Faranak Heidarian Julien S

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  1. Modeling Clock Synchronization in the Chess gMAC WSN ProtocolMathijsSchutsFeng Zhu FaranakHeidarianJulien Schmaltz Frits Vaandrager QFM’09 FM’09

  2. Plan • Intro to WSN and Chess case study • A first model + analysis • A second model + counterexamples • Conclusions & Future Work

  3. WSN – butwith a twist! • Mainchallenges: • Energy efficiency (batteryoperatedorenergyharvesting → lifetime) • Robustness (RF spectrum is extremelynoisy, verybusy and unreliable) • Scalability (101 – 102 – 103 – 104 – 105nodeswith a single protocol) • Self-adaptable (constantlychangingnetworktopology, density, mobility) • Limited resources (CPU processing speed, availablememory, fysicalsize) • There are manyavailable WSN protocols, e.g.: • Wifi • Bluetooth • Zigbee • Z-wave • … • Neither of these technologiesaddresses all challenges!

  4. WSN – butwith a twist! • Communicationinspiredonbiology and humaninteraction • Epidemiccommunication • Analogy: spreading arumoror a virus • MYRIANED “GOSSIP” protocol • RF broadcast (2.4 Ghz ISM)

  5. WSN – butwith a twist! • Communicationinspiredonbiology and humaninteraction • Epidemiccommunication • Analogy: spreading arumoror a virus • MYRIANED “GOSSIP” protocol • RF broadcast (2.4 Ghz ISM)

  6. WSN – butwith a twist! • Communicationinspiredonbiology and humaninteraction • Epidemiccommunication • Analogy: spreading arumoror a virus • MYRIANED “GOSSIP” protocol • RF broadcast (2.4 Ghz ISM)

  7. WSN – butwith a twist! • Communicationinspiredonbiology and humaninteraction • Epidemiccommunication • Analogy: spreading arumoror a virus • MYRIANED “GOSSIP” protocol • RF broadcast (2.4 Ghz ISM)

  8. WSN – butwith a twist! • Communicationinspiredonbiology and humaninteraction • Epidemiccommunication • Analogy: spreading arumoror a virus • MYRIANED “GOSSIP” protocol • RF broadcast (2.4 Ghz ISM)

  9. WSN – butwith a twist! • Communicationinspiredonbiology and humaninteraction • Epidemiccommunication • Analogy: spreading arumoror a virus • MYRIANED “GOSSIP” protocol • RF broadcast (2.4 Ghz ISM)

  10. WSN – butwith a twist! • Communicationinspiredonbiology and humaninteraction • Epidemiccommunication • Analogy: spreading arumoror a virus • MYRIANED “GOSSIP” protocol • RF broadcast (2.4 Ghz ISM)

  11. WSN – butwith a twist! • Communicationinspiredonbiology and humaninteraction • Epidemiccommunication • Analogy: spreading arumoror a virus • MYRIANED “GOSSIP” protocol • RF broadcast (2.4 Ghz ISM)

  12. WSN – butwith a twist! • Communicationinspiredonbiology and humaninteraction • Epidemiccommunication • Analogy: spreading arumoror a virus • MYRIANED “GOSSIP” protocol • RF broadcast (2.4 Ghz ISM)

  13. WSN – butwith a twist! • Communicationinspiredonbiology and humaninteraction • Epidemiccommunication • Analogy: spreading arumoror a virus • MYRIANED “GOSSIP” protocol • RF broadcast (2.4 Ghz ISM)

  14. WSN – butwith a twist! • Communicationinspiredonbiology and humaninteraction • Epidemiccommunication • Analogy: spreading arumoror a virus • MYRIANED “GOSSIP” protocol • RF broadcast (2.4 Ghz ISM)

  15. Properties of GOSSIP In a nutshell: • Flooding provides robustness • Localcachingprevents overhead • Absense of routing provides scalability • Inherentlyself-configuring • Supports node mobility • Automaticadoption to networkdensity Butwhataboutenergy efficiency?

  16. RF TRANCEIVER (NORDIC SEMI) CPU (ATMEL XMEGA128) RF ANTENNA I/O INTERFACES

  17. Case Study for EU Quasimodo Project Model and analyze Chess WSN, based on • informal specification in deliverable • discussions with experts

  18. Our Focus: Clock Synchronization Time is considered as a sequence of Time Frames. A Time Frame A time frame is composed of a fixed number (C) of Time Slots. tsn RX TX RX idle idle idle idle In a time slot the hardware clock of the sensor node ticks a fixed number (k0) of times.

  19. Goal: Minimalize Energy Consumption TX Time Slot Guard Time Guard Time RX Time Slot

  20. Uppaal Model FM’09 A Wireless Sensor Node Clock Synchronizer

  21. Results FM’09 Paper • Full parametric analysis for clique networks • Parameter constraints found using Uppaal • Proof fully checked using Isabelle/Hol (> 5000 lines) • Correctness also studied for line topologies

  22. Results FM’09 Paper • Full parametric analysis for clique networks • Parameter constraints found using Uppaal • Proof fully checked using Isabelle/Hol (> 5000 lines) • Correctness also studied for line topologies • Model does not correspond to Chess implementation!

  23. HowCurrentImplementation Works • Clocksonlysynchronizedonce per frame • Implementationcomputesmedian of phaseerrors of all messagesreceived in frame • Offset = median * gain • Radio switching time is relevant

  24. Structure of Uppaal Model

  25. Clock

  26. Sender

  27. Receiver

  28. Controller

  29. Synchronizer

  30. compute_phase_correction() if (number of received messages == 0) offset = 0; else if (number of received messages <= 2) offset = the phase error of the first received message * gain; else offset = the median of all phase errors * gain

  31. Invariants for Correctness “Whenever I send all my neighbors listen” INV1 : A[] forall (i: Nodes) forall (j : Nodes) SENDER(i).Sending && neighbor(i,j)imply RECEIVER(j).Receiving “My neighbors never send simultaneously” INV2 : A[] forall (i:Nodes) forall (j:Nodes) forall (k:Nodes) SENDER(i).Sending && neighbor(i,k) && SENDER(j).Sending && neighbor(j,k) imply i == j “There’s no deadlock” INV3 : A[] not deadlock

  32. CounterexamplefoundbyUppaal

  33. Protocol fails for any network that contains 2 clans! Server Watershed Sensor field Gateway Internet Fastnodes Slow nodes

  34. Challenge: Fix the Problem • Assegei (2008) proposeduse of Kalman filter instead of medianalgorithm • Our FM2009 algorithm, possiblywithgain factor • Algorithm of Lenzen, Lochen & Wattenhofer (2008) • Adaptation of algorithmPussente & Barbosa (2009) Itshouldbe easy to adaptourUppaal model

  35. Challenge: Probabilities • Probabilistic model of message loss • Probabilisticalgorithmsfor (dynamic) slot allocation • Probabilisticleaving/joining of nodes/networks • Probabilisticalgorithmsforgossiping • … Key design issue: independence of layers?!?!!

  36. Conclusions • Our contribution: Uppaal model of clock synchronization in Chess WSN; bug found • Never trust your model! • Close interaction between designers and modellers essential • Model checking useful, even if one can only handle trivial instances • Models are imperfect approximations of reality!! (“Physicists approach to modeling”) • Simulation and testing also essential

  37. Questions?

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