Hardware and Software Platforms for Distributed Computing on Resource Constrained Devices

  • Gloria Martorella
  • Daniele Peri
  • Elena Toscano
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 260)


The basic idea of distributed computing is that it is possible to solve a large problem by using the resources of various computing devices connected in a network. Each device interacts with each other in order to process a part of a problem, contributing to the achievement of a global solution. Wireless sensor networks (WSNs) are an example of distributed computing on low resources devices. WSNs encountered a considerable success in many application areas. Due to the constraints related to the small sensor nodes capabilities, distributed computing in WSNs allows to perform complex tasks in a collaborative way, reducing power consumption and increasing battery life. Many hardware platforms compose the ecosystem of WSNs and some lightweight operating systems have also been designed to ease application deployment, to ensure efficient resources management, and to decrease energy consumption. In this chapter we focus on distributed computing from several points of view emphasizing important aspects, ranging from hardware platforms to applications on resource constrained devices.



This work has been partially supported by the PON R&C grant MI01_00091 funding the SeNSori project.


  1. 1.
    Akkaya, K., Younis, M.: A survey on routing protocols for wireless sensor networks. Ad hoc Netw. 3(3), 325–349 (2005)CrossRefGoogle Scholar
  2. 2.
    Arduino uno (2013). Accessed 7 Sept 2013
  3. 3.
    Avancha, S., Patel, C., Joshi, A.: Ontology-driven adaptive sensor networks. In: MobiQuitous, Boston, pp. 194–202, 2004Google Scholar
  4. 4.
    Banzi, M.: Getting Started with Arduino. O’Reilly Media, Inc., Newton (2009)Google Scholar
  5. 5.
    Bhatti, S., Carlson, J., Dai, H., Deng, J., Rose, J., Sheth, A., Shucker, B., Gruenwald, C., Torgerson, A., Han, R.: Mantis os: An embedded multithreaded operating system for wireless micro sensor platforms. Mob. Netw. Appl. 10(4), 563–579 (2005)CrossRefGoogle Scholar
  6. 6.
    Bose, R., King, J., El-Zabadani, H., Pickles, S., Helal, A.: Building plug-and-play smart homes using the atlas platform. In: Proceedings of the 4th International Conference on Smart Homes and Health Telematic (ICOST), Belfast, June 2006, citeseer(2006)Google Scholar
  7. 7.
    Burns, A., Greene, B.R., McGrath, M.J., O’Shea, T.J., Kuris, B., Ayer, S.M., Stroiescu, F., Cionca, V.: Shimmer-a wireless sensor platform for noninvasive biomedical research. IEEE J. Sens. 10(9), 1527–1534 (2010)CrossRefGoogle Scholar
  8. 8.
    Cao, Q., Abdelzaher, T., Stankovic, J., He, T.: The liteos operating system: Towards unix-like abstractions for wireless sensor networks. In: Proceedings of 7th International Conference on Information Processing in Sensor Networks (IPSN ’08), pp. 233–244, April 2008Google Scholar
  9. 9.
    Chien, T.V., Chan, H.N., Huu, T.N.: A comparative study on operating system for wireless sensor networks. In: IEEE International Conference on Advanced Computer Science and Information System (ICACSIS’11), pp. 73–78, (2011)Google Scholar
  10. 10.
    Compton, M., Barnaghi, P., Bermudez, L., García-Castro, R., Corcho, O., Cox, S., Graybeal, J., Hauswirth, M., Henson, C., Herzog, A., et al.: The ssn ontology of the w3c semantic sensor network incubator group. Web Semant. Sci. Serv. Agents on the World Wide Web 17, 25–32 (2012)CrossRefGoogle Scholar
  11. 11.
    Compton, M., Neuhaus, H., Taylor, K., Tran, K.N.: Reasoning about sensors and compositions. In: Proceedings of Semantic Sensor Network, pp. 33–48, (2009)Google Scholar
  12. 12.
    De Paola, A., Gaglio, S., Lo Re, G., Ortolani, M.: Sensor9k: a testbed for designing and experimenting with WSN-based ambient intelligence applications. Pervasive and Mob. Comput. 8(3), 448–466 (2012)CrossRefGoogle Scholar
  13. 13.
    Demigha, O., Hidouci, W.K., Ahmed, T.: On energy efficiency in collaborative target tracking in wireless sensor network: a review. IEEE Commun. Surv. Tutorials 15(3), 1210–1222 (2013)CrossRefGoogle Scholar
  14. 14.
    Dunkels, A., Gronvall, B., Voigt, T.: Contiki - a lightweight and flexible operating system for tiny networked sensors. In: Proceedings of the 29th Annual IEEE International Conference on Local Computer Networks, pp. 455–462, (2004)Google Scholar
  15. 15.
    Elson, J., Römer, K.: Wireless sensor networks: a new regime for time synchronization. ACM SIGCOMM Comput. Commun. Rev. 33(1), 149–154 (2003)CrossRefGoogle Scholar
  16. 16.
    Farooq, M.O., Kunz, T.: Operating systems for wireless sensor networks: a survey. Sensors 11(6), 5900–5930 (2011)CrossRefGoogle Scholar
  17. 17.
    Ganeriwal, S., Kumar, R., Srivastava, M.B.: Timing-sync protocol for sensor networks. In: Proceedings of the 1st international conference on Embedded networked sensor systems (SenSys’03), pp. 138–149. ACM, New York (2003)Google Scholar
  18. 18.
    Gatani, L., Lo Re, G., Gaglio, S.: An efficient distributed algorithm for generating multicast distribution trees. In: International Conference on Parallel Processing Workshops (ICPP 2005 Workshops), pp. 477–484, (2005)Google Scholar
  19. 19.
    Girao, J., Westhoff, D., Mykletun, E., Araki, T.: TinyPEDS: tiny persistent encrypted data storage in asynchronous wireless sensor networks. Ad Hoc Netw. 5(7), 1073–1089 (2007)CrossRefGoogle Scholar
  20. 20.
    Hedetniemi, S.M., Hedetniemi, S.T., Liestman, A.L.: A survey of gossiping and broadcasting in communication networks. Networks 18(4), 319–349 (1988)CrossRefMATHMathSciNetGoogle Scholar
  21. 21.
    Jardak, C., Osipov, E., Mahonen, P.: Distributed information storage and collection for wsns. In: IEEE Internatonal Conference on Mobile Adhoc and Sensor Systems (MASS’07), pp. 1–10, (2007)Google Scholar
  22. 22.
    King, J., Bose, R., Yang, H.I., Pickles, S., Helal, A.: Atlas: A service-oriented sensor platform: Hardware and middleware to enable programmable pervasive spaces. In: Proceedings of 31st IEEE Conference on Local Computer Networks, pp. 630–638, (2006)Google Scholar
  23. 23.
    Klues, K., Liang, C.J.M., Paek, J., Musaloiu-Elefteri, R., Levis, P., Terzis, A., Govindan, R.: Tosthreads: thread-safe and non-invasive preemption in tinyos. In: SenSys, vol. 9, pp. 127–140, (2009)Google Scholar
  24. 24.
    Krontiris, I., Benenson, Z., Giannetsos, T., Freiling, F.C., Dimitriou, T.: Cooperative intrusion detection in wireless sensor networks. In: Wireless Sensor Networks, pp. 263–278. Springer, Berlin (2009)Google Scholar
  25. 25.
    Kulik, J., Heinzelman, W., Balakrishnan, H.: Negotiation-based protocols for disseminating information in wireless sensor networks. Wireless Netw. 8(2/3), 169–185 (2002)CrossRefMATHGoogle Scholar
  26. 26.
    Larios, D., Mora-Merchan, J., Personal, E., Barbancho, J., León, C.: Implementing a distributed wsn based on ipv6 for ambient monitoring. Int. J. Distrib. Sens. Netw. (2013)Google Scholar
  27. 27.
    Levis, P., Madden, S., Polastre, J., Szewczyk, R., Whitehouse, K., Woo, A., Gay, D., Hill, J., Welsh, M., Brewer, E., et al.: Tinyos: an operating system for sensor networks. In: Ambient intelligence, pp. 115–148. Springer, Heidelberg (2005)Google Scholar
  28. 28.
    Li, W., Bao, J., Shen, W.: Collaborative wireless sensor networks: a survey. In: IEEE International Conference on Systems, Man, and Cybernetics (SMC’11), pp. 2614–2619, (2011)Google Scholar
  29. 29.
    Lo Re, G., Milazzo, F., Ortolani, M.: Secure random number generation in wireless sensor networks. In: Proceedings of the 4th international conference on Security of Information and Networks, pp. 175–182, (2011)Google Scholar
  30. 30.
    Lo Re, G., Milazzo, F., Ortolani, M.: A distributed bayesian approach to fault detection in sensor networks. In: Proceedings of the IEEE Global Communications Conference (GLOBECOM’12), pp. 634–639, (2012)Google Scholar
  31. 31.
    Nakamura, M., Nakamura, J., Lopez, G., Shuzo, M., Yamada, I.: Collaborative processing of wearable and ambient sensor system for blood pressure monitoring. Sensors 11(7), 6760–6770 (2011)CrossRefGoogle Scholar
  32. 32.
    Piotrowski, K., Langendoerfer, P., Peter, S.: tinydsm: a highly reliable cooperative data storage for wireless sensor networks. In: International Symposium on Collaborative Technologies and Systems (CTS’09), pp. 225–232, (2009)Google Scholar
  33. 33.
    Rajagopalan, R., Varshney, P.K.: Data aggregation techniques in sensor networks: a survey. IEEE Comm. Surv. Tutorials 8, 48–63 (2006)Google Scholar
  34. 34.
    Reusing, T.: Comparison of operating systems tinyos and contiki. Sens. Nodes-Operation, Netw. Appli. (SN) 7 (2012)Google Scholar
  35. 35.
    Ribeiro, A., Giannakis, G.B., Roumeliotis, S.I.: Soi-kf: distributed kalman filtering with low-cost communications using the sign of innovations. IEEE Trans. Sig. Process. 54(12), 4782–4795 (2006)CrossRefGoogle Scholar
  36. 36.
    Singh, S.K., Singh, M., Singh, D.: A survey of energy-efficient hierarchical cluster-based routing in wireless sensor networks. Int. J. Adv. Networking and Appl. (IJANA) 2(02), 570–580 (2010)Google Scholar
  37. 37.
    Strazdins, G., Elsts, A., Selavo, L.: Mansos: easy to use, portable and resource efficient operating system for networked embedded devices. In: Proceedings of the 8th ACM Conference on Embedded Networked Sensor Systems (SenSys ’10), pp. 427–428, ACM (2010)Google Scholar
  38. 38.
    Sundararaman, B., Buy, U., Kshemkalyani, A.D.: Clock synchronization for wireless sensor networks: a survey. Ad Hoc Netw. 3(3), 281–323 (2005)CrossRefGoogle Scholar
  39. 39.
    Tang, L., Sun, Y., Gurewitz, O., Johnson, D.B.: Pw-mac: an energy-efficient predictive-wakeup mac protocol for wireless sensor networks. In: INFOCOM, 2011 Proceedings IEEE, pp. 1305–1313 (2011)Google Scholar
  40. 40.
    Wang, X., Wang, S., Bi, D.: Distributed visual-target-surveillance system in wireless sensor networks. IEEE Trans. Syst. Man Cybern. B Cybern. 39(5), 1134–1146 (2009)CrossRefGoogle Scholar
  41. 41.
    Waspmote datasheet: Available online at Accessed 7 Sept 2013
  42. 42.
    Whitehouse, K., Sharp, C., Brewer, E., Culler, D.: Hood: a neighborhood abstraction for sensor networks. In: Proceedings of the 2nd international conference on Mobile systems, applications, and services, pp. 99–110. ACM (2004)Google Scholar
  43. 43.
    Yu, B., Li, J., Li, Y.: Distributed data aggregation scheduling in wireless sensor networks. In: IEEE INFOCOM 2009, pp. 2159–2167 (2009)Google Scholar
  44. 44.
    Zennaro, M., Bagula, A., Gascon, D., Noveleta, A.B.: Long distance wireless sensor networks: simulation vs reality. In: Proceedings of the 4th ACM Workshop on Networked Systems for Developing Regions, pp. 12:1–12:2. ACM (2010)Google Scholar
  45. 45.
    Zolertia z1 datasheet: Available online at (2013). Accessed 7 Sept 2013

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Gloria Martorella
    • 1
  • Daniele Peri
    • 1
  • Elena Toscano
    • 2
  1. 1.Dipartimento di Ingegneria Chimica Gestionale Informatica MeccanicaUniversità degli Studi di PalermoPalermoItaly
  2. 2.Dipartimento di Matematica e InformaticaUniversità degli Studi di PalermoPalermoItaly

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