Advertisement

Distributed scheduling with efficient collision detection for end-to-end delay optimization in 6TiSCH multi-hop wireless networks

  • Inès HosniEmail author
Article
  • 68 Downloads

Abstract

It is expected that the IEEE 802.15.4e-TSCH designed for wireless industrial sensor networks will be used in IoT systems. This standard relies on techniques such as channel hopping and bandwidth reservation to ensure both energy savings and reliable transmissions. Since many applications may require low end-to-end delay (e.g., alarms), we propose here a distributed algorithm to schedule the transmissions while upper bounding the end-to-end source-sink delay. Our strategy constructs stratums, regrouping all the nodes with the same depth in the DODAG Destination Oriented Directed Acyclic Graph constructed by RPL. Then, different time-frequency blocks(bands) are assigned deterministically to each stratum. By appropriately tuning the size of each block and chronologically organizing them, we are able to guarantee any packet is delivered along the path length to the border router before the end of the slotframe. We also provide self-healing mechanism to detect and alleviate local collisions. Experiments on a large-scale testbed prove the relevance of this approach to reduce the end-to-end delay while minimizing the number of collisions, prejudicial to the reliability in multihop networks.

Keywords

IEEE 802.15.4-TSCH End-to-end delay Self-healing Distributed scheduling Autonomous Large-scale experiments 

Notes

References

  1. 1.
    IEEE Std 802.15.4e-2012, IEEE Standard for local and metropolitan area networks–Part 15.4: Low-Rate Wireless Personal Area Networks (LR-WPANs) Amendment 1: MAC sublayer (2012)Google Scholar
  2. 2.
    Watteyne T, Mehta A, Pister K (2009) Reliability through frequency diversity: why channel hopping makes sense. In: ACM symposium on performance evaluation of wireless Ad Hoc, sensor, and ubiquitous networks (PE-WASUN), pp 116–123.  https://doi.org/10.1145/1641876.1641898
  3. 3.
    Palattella M, Accettura N, Vilajosana X, Watteyne T, Grieco L, Boggia G, Dohler M (2013) Standardized protocol stack for the internet of (important) things. IEEE Commun Surv Tutorials 15(3):1389–1406.  https://doi.org/10.1109/SURV.2012.111412.00158 CrossRefGoogle Scholar
  4. 4.
    Ieee, std. 802.15.4, Part 15.4: Low-rate wireless personal area networks (lr-wpans), standard for information technology (16 June 2011)Google Scholar
  5. 5.
    6tisch, Ipv6 over the tsch mode of ieee 802.15.4e wg charter-ietf-6tisch-01-00 (2013)Google Scholar
  6. 6.
    Winter T, Thubert P, Brandt A, Hui J, Kelsey R, Levis P, Pister K, Struik R, Vasseur JP, Alexander R (2012) Rpl: Ipv6 routing protocol for low-power and lossy networks, rfc 6550 IETFGoogle Scholar
  7. 7.
    Wang Q, Vilajosana X (2015) 6tisch operation sublayer (6top) interface, draft IETFGoogle Scholar
  8. 8.
    Pister K, Doherty L (2008) Tsmp: time synchronized mesh protocol. In: Parallel and distributed computing and systemsGoogle Scholar
  9. 9.
    Tsitsiklis JN, Xu K (2011) On the power of (even a little) centralization in distributed processing. In: ACM SIGMETRICS, pp 161–172.  https://doi.org/10.1145/1993744.1993759
  10. 10.
    Palattella MR et al (2013) On optimal scheduling in duty-cycled industrial IoT applications using IEEE802.15.4e TSCH. Sensors Journal, IEEE 13(10):3655–3666.  https://doi.org/10.1109/JSEN.2013.2266417 CrossRefGoogle Scholar
  11. 11.
    Tinka A, Watteyne T, Pister K (2010) A decentralized scheduling algorithm for time synchronized channel hopping. In: ICST Transactions on mobile communications and applicationsGoogle Scholar
  12. 12.
    Accettura N, Palattella M, Boggia G, Grieco L, Dohler M (2013) Decentralized traffic aware scheduling for multi-hop low power lossy networks in the internet of things. In: 2013 IEEE 14th international symposium and workshops on a world of wireless, mobile and multimedia networks (WoWMoM), pp 1–6.  https://doi.org/10.1109/WoWMoM.2013.6583485
  13. 13.
    Chang T, Watteyne T, Wang Q, Vilajosana X (2016) Low latency scheduling function for 6tisch networks. In: 2016 international conference on distributed computing in sensor systems (DCOSS), New York, USA, pp 93-95Google Scholar
  14. 14.
    Wan C-Y, Eisenman SB, Campbell AT, Crowcroft J (2005) Siphon: overload traffic management using multi-radio virtual sinks in sensor networks. In: ACM SenSys pp 116–129.  https://doi.org/10.1145/1098918.1098931
  15. 15.
    Dujovne D, Grieco LA, Palattella MR, Accettura N (2015) 6tisch on-the-fly scheduling, draft IETFGoogle Scholar
  16. 16.
    Ghosh A, Incel O, Kumar V, Krishnamachari B (2009) Multi-channel scheduling algorithms for fast aggregated convergecast in sensor networks. In: MASS, IEEE pp 363–372.  https://doi.org/10.1109/MOBHOC.2009.5336979
  17. 17.
    Yan M, Lam K-Y, Han S, Chan E, Chen Q, Fan P, Chen D, Nixon M (2014) Hypergraph-based data link layer scheduling for reliable packet delivery in wireless sensing and control networks with end-to-end delay constraints. Inf Sci 278:34–55.  https://doi.org/10.1016/j.ins.2014.02.006 MathSciNetCrossRefzbMATHGoogle Scholar
  18. 18.
    Yigit M, Incel OD, Gungor VC (2014) On the interdependency between multi-channel scheduling and tree-based routing for WSNs in smart grid environments. Comput Netw 65(0):1–20.  https://doi.org/10.1016/j.comnet.2014.02.025 CrossRefGoogle Scholar
  19. 19.
    Dobslaw F, Zhang T, Gidlund M End-to-end reliability-aware scheduling for wireless sensor networks, IEEE Transactions on Industrial Informatics.  https://doi.org/10.1109/TII.2014.2382335
  20. 20.
    Phung K-H, Lemmens B, Goossens M, Nowe A, Tran L, Steenhaut K (2015) Schedule-based multi-channel communication in wireless sensor networks: a complete design and performance evaluation. Ad Hoc Networks 26:88–102.  https://doi.org/10.1016/j.adhoc.2014.11.008 CrossRefGoogle Scholar
  21. 21.
    Rhee I, Warrier A, Aia M, Min J, Sichitiu M (2008) Z-mac: a hybrid mac for wireless sensor networks. IEEE/ACM Trans Networking 16(3):511–524.  https://doi.org/10.1109/TNET.2007.900704 CrossRefGoogle Scholar
  22. 22.
    Duquennoy S, Al Nahas B, Landsiedel O, Watteyne T (2015) Orchestra: robust mesh networks through autonomously scheduled tsch. In: Conference on embedded networked sensor systems (Sensys). ACM, pp 337–350.  https://doi.org/10.1145/2809695.2809714
  23. 23.
    Zand P, Chatterjea S, Ketema J (2012) A distributed scheduling algorithm for real-time (d-sar) industrial wireless sensor and actuator networks. In: Conference on emerging technologies and factory automation (ETFA).  https://doi.org/10.1109/ETFA.2012.6489719
  24. 24.
    Pottner W-B, Seidel H, Brown J, Roedig U, Wolf L (2014) Constructing schedules for time-critical data delivery in wireless sensor networks. Transactions on Sensor Networks (TOSN) 10 (0):1–20.  https://doi.org/10.1145/2494528 Google Scholar
  25. 25.
    Watteyne T, Palattella M, Grieco L (2014) Using ieee802.15.4e tsch in an iot context, draft 1 IETFGoogle Scholar
  26. 26.
    Soua R, Minet P, Livolant E (2012) MODESA: An optimized multichannel slot assignment for raw data convergecast in wireless sensor networks. In: International performance computing and communications conference (IPCCC). IEEE, pp 91–100.  https://doi.org/10.1109/PCCC.2012.6407742
  27. 27.
    De Couto DSJ, Aguayo D, Bicket J, Morris R (2005) A high-throughput path metric for multi-hop wireless routing. Wirel Netw 11(4):419–434.  https://doi.org/10.1007/s11276-005-1766-z CrossRefGoogle Scholar
  28. 28.
    Shi Y, Hou YT, Liu J, Kompella S (2009) How to correctly use the protocol interference model for multi-hop wireless networks. In: ACM mobihoc, New Orleans, LA, USA, pp 239-248Google Scholar
  29. 29.
    Muraoka K, Watteyne T, Accettura N (2016) Simple distributed scheduling with collision detection in tsch networks. IEEE sensors journal 16(1):5848–5849.  https://doi.org/10.1109/JSEN.2016.2572961 CrossRefGoogle Scholar
  30. 30.
    Dong Q, Dargie W, Schill A (December 2010) Effects of sampling rate on collision probability in hybrid mac protocols in wsn. In: IEEE GLOBECOM workshops (GC wkshps), Miami, USA, pp 213-218Google Scholar
  31. 31.
    Iala I, Ouadou M, Aboutajdine D (2017) Energy based collision avoidance at the mac layer for wireless sensor network. In: International conference on advanced technologies for signal and image processing (ATSIP), Fezi, Morocco, pp 1–5Google Scholar
  32. 32.
    Chan T, andTengfei Chan TW, Wang Q (2017) Ccr: Cost-aware cell relocation in 6tisch networks. Transactions on Emerging Telecommunications Technologies 29(1):5848–5849.  https://doi.org/10.1002/ett.3211 Google Scholar
  33. 33.
    Theoleyre F (2016) A distributed version of 6tisch for high reliability in self-configured low power lossy networks. Submitted, https://clarinet.u-strasbg.fr/theoleyre/tmp/net16-6tisch-distrib.pdf
  34. 34.
    Dujovne D, Grieco LA, Palattella MR, Accettura N (2016) 6tisch 6top scheduling function zero (sf0), draft 1 IETFGoogle Scholar

Copyright information

© Institut Mines-Télécom and Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.University of Tunis El Manar, National Engineering School of TunisCommunications Systems LaboratoryTunisTunisia
  2. 2.College of Computer and Information SciencesJouf UniversitySakakahSaudi Arabia

Personalised recommendations