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A Smart City Fighting Pollution, by Efficiently Managing and Processing Big Data from Sensor Networks

  • Voichita Iancu
  • Silvia Cristina Stegaru
  • Dan Stefan TudoseEmail author
Chapter
Part of the Computer Communications and Networks book series (CCN)

Abstract

In this chapter, we will detail our view of a Smart City which benefits from the combined help of the sensors and of Big Data techniques, in order to fight pollution. We focus mostly on: (1) the management of a reliable and trustworthy mobile and static sensor network, which will gather the data; and (2) the spatial and temporal Big Data storage organization. We also point out hints about the way in which we envisage that the Smart City actions will be derived from the Big Data and the way in which they will actually be materialized by the Smart City’s actuators. We have a special section about what smart measures a Smart City should take, when it needs to fight against pollution. Among the future developments for our Smart City model, we see: (1) means to make the sensor network more resilient to insiders or outsiders’ attacks; (2) optimized high performance computing techniques, to determine a more accurate model for the Smart City’s intrinsic mechanisms; and also (3) designing models of interaction between weather forecast and the Smart City’s mechanisms in order to obtain accurate pollution forecast models.

Keywords

Data gathering Fault tolerance Scalability Load balancing Sensor networks Pollution 

References

  1. 1.
    Almăşan, V.: Using peer-to-peer scalable techniques to increase service availability in SIP networks. PhD thesis, Universitatea Tehnică din Cluj-Napoca, Romania (2011)Google Scholar
  2. 2.
    Chang, F., Dean, J., Ghemawat, S., Hsieh, W.C., Wallach, D.A., Burrows, M., Chandra, T., Fikes, A., Gruber, R.E.: Bigtable: A Distributed Storage System for Structured Data. In OSDI, Seattle, WA, USA (2006)Google Scholar
  3. 3.
    Nicolae, B., Antoniu, G., Bougé, L., Moise, D., Carpen-Amarie, A.: BlobSeer: next generation data management for large scale infrastructures. J. Parallel Distrib. Comput. 71(2), 168–184 (2011)CrossRefGoogle Scholar
  4. 4.
    Chowdhury, M., Zaharia, M., Ma, J., Jordan, M.I., Stoica, I.: Managing data transfers in computer clusters with orchestra. In: SIGCOMM (2011)Google Scholar
  5. 5.
    Zaharia, M., Chowdhury, M., Das, T., Dave, A., Ma, J., McCauley, M., Franklin, M.J., Shenker, S., Stoica, I.: A Fault-tolerant Abstraction for In-memory Cluster Computing. In NSDI, San Jose, CA, USA (2012)Google Scholar
  6. 6.
    Corbett, J.C., Dean, J., Epstein, M., Fikes, A., Frost, C., Furman, J., Ghemawat, S., Gubarev, A., Heiser, C., Hochschild, P., Hsieh, W., Kanthak, S., Kogan, E., Li, H., Lloyd, A., Melnik, S., Mwaura, D., Nagle, D., Quinlan, S., Rao, R., Rolig, L., Saito, Y., Szymaniak, M., Taylor, C., Wang, R., Woodford, D.: Spanner: Google’s Globally-Distributed Database. In OSDI, Hollywood, CA, USA (2012)Google Scholar
  7. 7.
    Schwan, P.: Lustre—building a filesystem for 1000-node cluster. In: Proceedings of Linux Symposium (2003)Google Scholar
  8. 8.
    Weiser, M.: Some Computer Science Problems in Ubiquitous Computing. Communications of the ACM (1993)Google Scholar
  9. 9.
    Tudose, D., Patrascu, T.A., Voinescu, A., Tataroiu, R., Tapus, N.: Mobile sensors in air pollution measurement. In: Proceedings of the 18th Workshop on Positioning, Navigation and Communication (WNPC’11), Dresden, Germany, April 2011Google Scholar
  10. 10.
    Tataroiu, R., Tudose, D.: Remote monitoring and control of wireless sensor networks. In: Proceedings of the 17th International Conference of Control Systems and Computer Science (CSCS17), vol. 1, pp. 187–192. Bucharest, Romania (May 2009)Google Scholar
  11. 11.
    The MySQL database. http://dev.mysql.com/
  12. 12.
    Davies, A., Fisk, H.: MySQL Clustering. MySQL Press (2006)Google Scholar
  13. 13.
    Sun Microsystems, I.: NFS: Network File System Protocol Specification. RFC 1094 (Standard) (1989)Google Scholar
  14. 14.
    Wilde, E.: Wilde’s WWW. Springer (1998)Google Scholar
  15. 15.
    Stoica, I., Morris, R., Karger, D., Kaashoek, F., Balakrishnan, H.: Chord: A Scalable Peer-To-Peer Lookup Service for Internet Applications. In: Proceedings of the 2001 ACM SIGCOMM Conference, pp. 149–160 (2001)Google Scholar
  16. 16.
    Ratnasamy, S., Francis, P., Handley, M., Karp, R., Schenker, S.: A scalable content-addressable network. In: SIGCOMM ’01: Proceedings of the 2001 conference on Applications, Technologies, Architectures, and Protocols for Computer Communications, vol. 31, pp. 161–172. ACM Press, October 2001Google Scholar
  17. 17.
    Rowstron, A., Druschel, P.: Pastry: Scalable, decentralized object location and routing for large-scale peer-to-peer systems. In: IFIP/ACM International Conference on Distributed Systems Platforms (Middleware), pp. 329–350, Nov 2001Google Scholar
  18. 18.
    Zhao, B.Y., Huang, L., Stribling, J., Rhea, S.C., Joseph, A.D., Kubiatowicz, J.D.: Tapestry: A resilient global-scale overlay for service deployment. IEEE J. Sel. Areas Commun. 22(1), 41–53 (2004)CrossRefGoogle Scholar
  19. 19.
    SHA-1—Secure Hash Standard. http://www.itl.nist.gov/fipspubs/fip180-1.htm
  20. 20.
    Dabek, F., Brunskill, E., Kaashoek, M.F., Karger, D., Morris, R., Stoica, I., Balakrishnan, H.: Building peer-to-peer systems with chord, a distributed lookup service. In: Proceedings of the 8th Workshop on Hot Topics in Operating Systems (HotOS-VIII), Schloss Elmau, Germany, IEEE Computer Society, May 2001Google Scholar
  21. 21.
    Borthakur, D., Gray, J., Sarma, J.S., Muthukkaruppan, K., Spiegelberg, N., Kuang, H., Ranganathan, K., Molkov, D., Menon, A., Rash, S., Schmidt, R., Aiyer, A.: Apache hadoop goes realtime at facebook. In: Proceedings of the 2011 ACM SIGMOD International Conference on Management of data, SIGMOD ’11, pp. 1071–1080. ACM, New York, NY, USA, (2011)Google Scholar
  22. 22.
    Shvachko, K., Kuang, H., Radia, S., Chansler, R.: The hadoop distributed file system. In: Proceedings of the 2010 IEEE 26th Symposium on Mass Storage Systems and Technologies (MSST), MSST ’10, IEEE Computer Society, pp. 1–10. Washington, DC, USA (2010)Google Scholar
  23. 23.
    Ananthanarayanan, G., Ghodsi, A., Wang, A., Borthakur, D., Kandula, S., Shenker, S., Stoica, I.: PACMan: Coordinated Memory Caching for Parallel Jobs. In NSDI, San Jose, CA, USA (2012)Google Scholar
  24. 24.
    Johnson Space Center: Fault-Detection, Fault-Isolation and Recovery (FDIR) Techniques. NASA Engineering Network, Technique DFE-7 (1994)Google Scholar
  25. 25.
    Nithya, R., Kevin, C., Rahul, K., Lewis, G., Eddie, K., Deborah, E.: Sympathy for the Sensor Network Debugger. In: 3rd Embedded Networked Sensor Systems, pp. 255–267 (2005)Google Scholar
  26. 26.
    Linnyer Beatrys, R., Isabela, G.S, Leonardo, B.O., Hao, C.W., José Marcos S.N., Antonio A.F.L.: Fault Management in Event-Driven Wireless Sensor Networks. In: Proceedings of the 7th ACM international Symposium on Modeling, Analysis and Simulation of Wireless and Mobile Systems (2004). doi: 10.1145/1023663.1023691
  27. 27.
    Jinran, C., Shubha, K., Arun, S.: Distributed fault detection of wireless sensor networks. In: Proceedings of the 2006 Workshop on Dependability Issues in Wireless ad Hoc Networks and Sensor Networks (2006). doi: 10.1145/1160972.1160985
  28. 28.
    Benhamida, F.Z., Challal, Y., Koudil, M.: Efficient adaptive failure detection for query/response based wireless sensor networks. In: Wireless Days, IFIP (2011). doi: 10.1109/WD.2011.6098190
  29. 29.
    Kebin, L., Qiang, M., Xibin, Z., Yunhao, L.: Self-diagnosis for large scale wireless sensor networks. In: IEEE INFOCOM (2011)Google Scholar
  30. 30.
    Qiang, M., Kebin, L., Xin, M., Yunhao, L.: Sherlock is around: detecting network failures with local evidence fusion. In: IEEE INFOCOM (2012)Google Scholar
  31. 31.
    Alan, M., David, C., Joseph, P., Robert, S., John, A.: Wireless sensor networks for habitat monitoring. In: Proceedings of the 1st ACM international Workshop on Wireless Sensor Networks and Applications, WSNA (2002). doi: 10.1145/570738.570751
  32. 32.
    Jeongyeup, P., Chintalapudi, K., Govindan, R., Caffrey, J., Masri, D.: A wireless sensor network for structural health monitoring: performance and experience. In: Proceedings of the 2nd IEEE Workshop on Embedded Networked Sensors, pp. 1–9. EmNets (2005)Google Scholar
  33. 33.
    Clemens, L., Nagendra, B.B., Daniel, R., Gerhard T.: On-body activity recognition in a dynamic sensor network. In: Proceedings of the ICST 2nd international conference on Body area networks, BodyNets (2007)Google Scholar
  34. 34.
    Phillip, B.G., Brad, K., Yan, K., Suman, N., Srinivasan, S.: IrisNet: An architecture for a worldwide sensor web. IEEE Pervasive Comput. 2(4), 22–33 (2003). doi: 10.1109/MPRV.2003.1251166
  35. 35.
    Adam, D., Richard, G., Sergio, A.M., Arnold, P., Mats, U.: Janus: an architecture for flexible access to sensor networks. In: Proceedings of the 1st ACM workshop on Dynamic interconnection of networks, DIN, pp. 48-52 (2005). doi: 10.1145/1080776.1080792
  36. 36.
    Mani, S., Mark, H., Jeff, B., Andrew, P., Sasank, R.: Wireless Urban Sensing Systems (2006)Google Scholar
  37. 37.
    Jung, Y.J., Lee, Y.K., Lee, D.G., Ryu, K.H., Nittel, S.: Air pollution monitoring system based on geosensor network. In: Geoscience and Remote Sensing Symposium, IGARSS (2008); IEEE International, vol. 3 (2009)Google Scholar
  38. 38.
    Kularatna, N., Sudantha, B.: An environmental air pollution monitoring system based on the IEEE 1451 standard for low cost requirements. IEEE Sens. J. 8(4) (2008)Google Scholar
  39. 39.
    Tsow, F., Forzani, E., Rai, A., Wang, R., Tsui, R., Mastroianni, S., Knobbe, C., Gandolfi, A.J., Tao, N.: A wearable and wireless sensor system for real-time monitoring of toxic environmental volatile organic compounds. IEEE Sens. J. 9(12) (2009)Google Scholar
  40. 40.
    Jeff, S., Peter, P., Jonathan, L., Mema, R., Margo, S., Matt, W.: Hourglass: An Infrastructure for Connecting Sensor Networks and Applications (2004)Google Scholar
  41. 41.
    Botts, M., Percivall, G., Reed, C., Davidson, J.: OGC Sensor Web Enablement: Overview and High Level Architecture, ed. pp. 175–190. Springer (2006)Google Scholar
  42. 42.
    Aman, K., Suman, N., Jie, L., Zhao, Feng: SenseWeb: an infrastructure for shared sensing. IEEE Multimedia 14(4), 8–13 (2007). doi: 10.1109/MMUL.2007.82 CrossRefGoogle Scholar
  43. 43.
    Shuo, G., Ziguo, Z., Tian, H.: FIND: faulty node detection for wireless sensor networks. In: Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems, pp. 253-266. Berkeley, California (2009). doi: 10.1145/1644038.1644064
  44. 44.
    Spark – lightning-fast cluster computing. http://spark-project.org/
  45. 45.
    Silvia Stegaru: Failure and Abnormal Behaviour Detection in Wireless Sensor Networks. Master thesis (2013)Google Scholar
  46. 46.
    United States Environmental Protection Agency: Carbon Monoxide (CO). http://www.epa.gov/iaq/co.html
  47. 47.
    Agency for Toxic Substances and Disease Registry: Medical Management Guidelines for Ammonia. http://www.atsdr.cdc.gov/mmg/mmg.asp?id=7&tid=2
  48. 48.
    Healthy child, healthy world: Keep amonia out of your home. http://healthychild.org/easy-steps/keep-ammonia-out-of-your-home/
  49. 49.
    New York Department of Health: Hydrogen Sulfide Chemical Information Sheet. http://www.health.state.ny.us/nysdoh/environ/btsa/sulfide.htm
  50. 50.
    American Lung Association Energy Policy Development: Transportation Background Document. Prepared by M.J. Bradley & Associates LLC (2011)Google Scholar
  51. 51.
    WebMD Asthma Health Center: High Carbon Dioxide Levels May Up Asthma Rate. http://www.webmd.com/asthma/news/20040429/high-carbon-dioxide-levels-may-up-asthma-rate?lastselectedguid=%7b5FE
  52. 52.
    Pollution Track. http://pollutiontrack.com/

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Voichita Iancu
    • 1
  • Silvia Cristina Stegaru
    • 1
  • Dan Stefan Tudose
    • 1
    Email author
  1. 1.Computer Science and Engineering DepartmentUniversity Politehnica of BucharestBucharestRomania

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