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Group Communication in Machine-to-Machine Environments

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Wireless Networking for Moving Objects

Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 8611))

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Abstract

M2M systems bring new horizons to the current concept of smart environments, since M2M enables a new set of services and applications. One of the main M2M features is the large number of resource-constrained devices that usually perform collective communication. This characteristic requires the design of network solutions that support the Data Aggregation (DA) of groups of Low Duty Cycling (LDC) devices. If LDC and DA are not designed jointly, the intermittent periods caused by Low Duty Cycling make the execution of Data Aggregation impracticable or with low performance. To address this problem, this book chapter describes the Group Communication Architecture for M2M Environments (GoCAME). This architecture enables the joint execution of DA and LDC, taking into account two-way latency tolerance, and multiple data-types. GoCAME also assures the concurrent execution of data requests, managing groups of nodes to provide the best strategy to reply to each data request.

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References

  1. Booysen, M., Gilmore, J., Zeadally, S., Van Rooyen, G.: Machine-to-machine (m2m) communications in vehicular networks. Article, Korea Society of Internet Information (KSII) (2012)

    Google Scholar 

  2. Zhang, Y., Yu, R., Xie, S., Yao, W., Xiao, Y., Guizani, M.: Home m2m networks: architectures, standards, and qos improvement. IEEE Commun. Mag. 49(4), 44–52 (2011)

    Article  Google Scholar 

  3. Hassan, R., Radman, G.: Survey on smart grid. In: Proceedings of the IEEE SoutheastCon 2010 (SoutheastCon), pp. 210–213. IEEE (2010)

    Google Scholar 

  4. Lioumpas, A., Alexiou, A., Anton-Haro, C., Navaratnam, P.: Expanding lte for devices: requirements, deployment phases and target scenarios. In: 11th European Wireless Conference 2011 - Sustainable Wireless Technologies (European Wireless), pp. 1–6, April 2011

    Google Scholar 

  5. Hao, J., Zhang, B., Mouftah, H.T.: Routing protocols for duty cycled wireless sensor networks: a survey. IEEE Commun. Mag. 50(12), 116–123 (2012)

    Article  Google Scholar 

  6. Fasolo, E., Rossi, M., Widmer, J., Zorzi, M.: In-network aggregation techniques for wireless sensor networks: a survey. IEEE Wirel. Commun. 14(2), 70–87 (2007)

    Article  Google Scholar 

  7. Zhang, J., Shan, L., Hu, H., Yang, Y.: Mobile cellular networks and wireless sensor networks: toward convergence. IEEE Commun. Mag. 50(3), 164–169 (2012)

    Article  Google Scholar 

  8. Tekbiyik, N., Uysal-Biyikoglu, E.: Energy efficient wireless unicast routing alternatives for machine-to-machine networks. J. Netw. Comput. Appl. 34(5), 1587–1614 (2011)

    Article  Google Scholar 

  9. Bluetooth, S.: Bluetooth specification version 1.1 (2001). http://www.bluetooth.com

  10. Alliance, Z.: Zigbee specification. Document 053474r06, Version 1 (2006)

    Google Scholar 

  11. Alliance, W.: Wimedia logical link control protocol. WLP Specification Approved Draft 1 (2007)

    Google Scholar 

  12. Alliance, W.: Wi-fi standards (2007)

    Google Scholar 

  13. Matoba, K., Abiru, K., Ishihara, T.: Service oriented network architecture for scalable m2m and sensor network services. In: 2011 15th International Conference on Intelligence in Next Generation Networks (ICIN), pp. 35–40, October 2011

    Google Scholar 

  14. Jumira, O., Wolhuter, R.: Value chain scenarios for m2m ecosystem. In: 2011 IEEE GLOBECOM Workshops (GC Wkshps), pp. 410–415, December 2011

    Google Scholar 

  15. Madden, S., Franklin, M.J., Hellerstein, J.M., Hong, W.: Tag: a tiny aggregation service for ad-hoc sensor networks. ACM SIGOPS Oper. Syst. Rev. 36(SI), 131–146 (2002)

    Article  Google Scholar 

  16. Tsitsipis, D., Dima, S., Kritikakou, A., Panagiotou, C., Koubias, S.: Data merge: a data aggregation technique for wireless sensor networks. In: 2011 IEEE 16th Conference on Emerging Technologies & Factory Automation (ETFA), pp. 1–4. IEEE (2011)

    Google Scholar 

  17. AbdelSalam, H.S., Rizvi, S.R., Olariu, S.: Energy-aware task assignment and data aggregation protocols in wireless sensor networks. In: 6th IEEE Consumer Communications and Networking Conference, CCNC 2009, pp. 1–5. IEEE (2009)

    Google Scholar 

  18. Manjhi, A., Nath, S., Gibbons, P.B.: Tributaries and deltas: efficient and robust aggregation in sensor network streams. In: Proceedings of the 2005 ACM SIGMOD International Conference on Management of Data, pp. 287–298. ACM (2005)

    Google Scholar 

  19. Rajagopalan, R., Varshney, P.K.: Data aggregation techniques in sensor networks: a survey. IEEE Commun. Surv. & Tutor. 8, 48–63 (2006)

    Article  Google Scholar 

  20. Handy, M., Haase, M., Timmermann, D.: Low energy adaptive clustering hierarchy with deterministic cluster-head selection. In: 4th International Workshop on Mobile and Wireless Communications Network, pp. 368–372. IEEE (2002)

    Google Scholar 

  21. Younis, O., Fahmy, S.: Heed: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. IEEE Trans. Mob. Comput. 3(4), 366–379 (2004)

    Article  Google Scholar 

  22. Chatterjea, S., Havinga, P.: A dynamic data aggregation scheme for wireless sensor networks (2003)

    Google Scholar 

  23. Lindsey, S., Raghavendra, C., Sivalingam, K.M.: Data gathering algorithms in sensor networks using energy metrics. IEEE Trans. Parallel Distrib. Syst. 13(9), 924–935 (2002)

    Article  Google Scholar 

  24. Huang, S.H., Wan, P.J., Vu, C.T., Li, Y., Yao, F.: Nearly constant approximation for data aggregation scheduling in wireless sensor networks. In: 26th IEEE International Conference on Computer Communications, INFOCOM 2007, pp. 366–372. IEEE (2007)

    Google Scholar 

  25. Chen, X., Hu, X., Zhu, J.: Minimum data aggregation time problem in wireless sensor networks. In: Jia, X., Wu, J., He, Y. (eds.) MSN 2005. LNCS, vol. 3794, pp. 133–142. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  26. Yu, B., Li, J., Li, Y.: Distributed data aggregation scheduling in wireless sensor networks. In: IEEE, INFOCOM 2009, pp. 2159–2167. IEEE (2009)

    Google Scholar 

  27. Joo, C., Choi, J.G., Shroff, N.B.: Delay performance of scheduling with data aggregation in wireless sensor networks. In: 2010 Proceedings IEEE INFOCOM, pp. 1–9. IEEE (2010)

    Google Scholar 

  28. Xu, X., Li, X.Y., Mao, X., Tang, S., Wang, S.: A delay-efficient algorithm for data aggregation in multihop wireless sensor networks. IEEE Trans. Parallel Distrib. Syst. 22(1), 163 (2011)

    Article  Google Scholar 

  29. Ghosh, A., Incel, Ö.D., Kumar, V., Krishnamachari, B.: Multichannel scheduling and spanning trees: throughput-delay tradeoff for fast data collection in sensor networks. IEEE/ACM Trans. Netw. (TON) 19(6), 1731–1744 (2011)

    Article  Google Scholar 

  30. Keshavarzian, A., Lee, H., Venkatraman, L.: Wakeup scheduling in wireless sensor networks. In: Proceedings of the 7th ACM International Symposium on Mobile Ad Hoc Networking and Computing, pp. 322–333. ACM (2006)

    Google Scholar 

  31. Instruments, T.: Cc1100 data sheet (2003)

    Google Scholar 

  32. Anastasi, G., Conti, M., Di Francesco, M., Passarella, A.: Energy conservation in wireless sensor networks: a survey. Ad Hoc Netw. 7(3), 537–568 (2009)

    Article  Google Scholar 

  33. Xu, Y., Heidemann, J., Estrin, D.: Geography-informed energy conservation for ad hoc routing. In: Proceedings of the 7th Annual International Conference on Mobile Computing and Networking, pp. 70–84. ACM (2001)

    Google Scholar 

  34. Feng, W., Alshaer, H., Elmirghani, J.: Green information and communication technology: energy efficiency in a motorway model. IET Commun. 4(7), 850–860 (2010)

    Article  Google Scholar 

  35. Chen, B., Jamieson, K., Balakrishnan, H., Morris, R.: Span: an energy-efficient coordination algorithm for topology maintenance in ad hoc wireless networks. Wirel. Netw. 8(5), 481–494 (2002)

    Article  MATH  Google Scholar 

  36. Cerpa, A., Estrin, D.: Ascent: adaptive self-configuring sensor networks topologies. IEEE Trans. Mob. Comput. 3(3), 272–285 (2004)

    Article  Google Scholar 

  37. Armstrong, T.: Wake-up based power management in multi-hop wireless networks. Term Survey Paper, University of Toronto (2005)

    Google Scholar 

  38. Schurgers, C., Tsiatsis, V., Srivastava, M.B.: Stem: topology management for energy efficient sensor networks. In: IEEE Aerospace Conference Proceedings, vol. 3, p. 3-1099. IEEE (2002)

    Google Scholar 

  39. Gu, L., Stankovic, J.A.: Radio-triggered wake-up for wireless sensor networks. Real-Time Syst. 29(2–3), 157–182 (2005)

    Article  Google Scholar 

  40. Kijewski-Correa, T., Haenggi, M., Antsaklis, P.: Wireless sensor networks for structural health monitoring: a multi-scale approach. In: ASCE Structures 2006 Congress (2006)

    Google Scholar 

  41. Guha, S., Basu, P.B., Chau, C.K., Gibbens, R.: Green wave sleep scheduling: optimizing latency and throughput in duty cycling wireless networks. IEEE J. Sel. Areas Commun. 29(8), 1595–1604 (2011)

    Article  Google Scholar 

  42. Tseng, Y.C., Hsu, C.S., Hsieh, T.Y.: Power-saving protocols for IEEE 802.11-based multi-hop ad hoc networks. Comput. Netw. 43(3), 317–337 (2003)

    Article  MATH  Google Scholar 

  43. Stinson, D.R.: Combinatorial Designs: Construction and Analysis. Springer, New York (2004)

    Google Scholar 

  44. Kim, J., Lin, X., Shroff, N.B.: Optimal anycast technique for delay-sensitive energy-constrained asynchronous sensor networks. IEEE/ACM Trans. Netw. (TON) 19(2), 484–497 (2011)

    Article  Google Scholar 

  45. Rajendran, V., Obraczka, K., Garcia-Luna-Aceves, J.J.: Energy-efficient, collision-free medium access control for wireless sensor networks. Wirel. Netw. 12(1), 63–78 (2006)

    Article  Google Scholar 

  46. Demirkol, I., Ersoy, C., Alagoz, F.: Mac protocols for wireless sensor networks: a survey. IEEE Commun. Mag. 44(4), 115–121 (2006)

    Article  Google Scholar 

  47. Fu, H.L., Chen, H.C., Lin, P., Fang, Y.: Energy-efficient reporting mechanisms for multi-type real-time monitoring in machine-to-machine communications networks. In: 2012 Proceedings IEEE INFOCOM, pp. 136–144. IEEE (2012)

    Google Scholar 

  48. Ma, J., Lou, W., Wu, Y., Li, X.Y., Chen, G.: Energy efficient tdma sleep scheduling in wireless sensor networks. In: IEEE INFOCOM 2009, pp. 630–638. IEEE (2009)

    Google Scholar 

  49. Incel, O.D.: A survey on multi-channel communication in wireless sensor networks. Comput. Netw. 55(13), 3081–3099 (2011)

    Article  Google Scholar 

  50. Kim, Y., Shin, H., Cha, H.: Y-mac: An energy-efficient multi-channel mac protocol for dense wireless sensor networks. In: Proceedings of the 7th International Conference on Information Processing in Sensor Networks, pp. 53–63. IEEE Computer Society (2008)

    Google Scholar 

  51. Karl, H., Willig, A.: Protocols and Architectures for Wireless Sensor Networks. Wiley.com (2007)

    Google Scholar 

  52. Van Dam, T., Langendoen, K.: An adaptive energy-efficient mac protocol for wireless sensor networks. In: Proceedings of the 1st International Conference on Embedded Networked Sensor Systems, pp. 171–180. ACM (2003)

    Google Scholar 

  53. Polastre, J., Hill, J., Culler, D.: Versatile low power media access for wireless sensor networks. In: Proceedings of the 2nd International Conference on Embedded Networked Sensor Systems, pp. 95–107. ACM (2004)

    Google Scholar 

  54. Rhee, I., Warrier, A., Aia, M., Min, J., Sichitiu, M.L.: Z-mac: a hybrid mac for wireless sensor networks. IEEE/ACM Trans. Netw. (TON) 16(3), 511–524 (2008)

    Article  Google Scholar 

  55. ETSI, T.: Functional architecture. ETSI TS 102.169 Machine-to-Machine communications (2010)

    Google Scholar 

  56. Wu, Y., Li, X.Y., Liu, Y., Lou, W.: Energy-efficient wake-up scheduling for data collection and aggregation. IEEE Trans. Parallel Distrib. Syst. 21(2), 275–287 (2010)

    Article  Google Scholar 

  57. Incel, O.D., van Hoesel, L., Jansen, P., Havinga, P.: Mc-lmac: a multi-channel mac protocol for wireless sensor networks. Ad Hoc Netw. 9(1), 73–94 (2011)

    Article  Google Scholar 

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Acknowledgments

This work was partially funded by the iCIS project, under the grant CENTRO-07-ST24-FEDER-002003; and CAPES/CNPq (Brazil) through the Ciencia sem Fronteiras Program/2013.

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Authors and Affiliations

  1. Centre for Informatics and Systems of the University of Coimbra, Coimbra, Portugal

    André Riker, Marilia Curado & Edmundo Monteiro

Authors
  1. André Riker
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  2. Marilia Curado
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  3. Edmundo Monteiro
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Corresponding author

Correspondence to André Riker .

Editor information

Editors and Affiliations

  1. University of Limerick, Limerick, Ireland

    Ivan Ganchev

  2. University of Coimbra, Coimbra, Portugal

    MarĂ­lia Curado

  3. Karlstad University, Karlstad, Sweden

    Andreas Kassler

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Riker, A., Curado, M., Monteiro, E. (2014). Group Communication in Machine-to-Machine Environments. In: Ganchev, I., Curado, M., Kassler, A. (eds) Wireless Networking for Moving Objects. Lecture Notes in Computer Science(), vol 8611. Springer, Cham. https://doi.org/10.1007/978-3-319-10834-6_12

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  • DOI: https://doi.org/10.1007/978-3-319-10834-6_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-10833-9

  • Online ISBN: 978-3-319-10834-6

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