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Application Specific Sensor-Cloud: Architectural Model

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Computational Intelligence in Sensor Networks

Part of the book series: Studies in Computational Intelligence ((SCI,volume 776))

Abstract

In recent years, the sensor cloud infrastructure dawns a huge advancement in many real time applications. The major drawback of Wireless Sensor Network (WSN) is its limited processing capability, bandwidth scarcity, insufficient memory, etc. In reality, the sensors (EEG, ECG, and so on) continuously sense the highly sensitive data, and send to the medical server leading to numerous challenges. The integration of cloud computing and WSNs with internet enables to cover and provide a service to the entire world, and also to overcome the deficiency of the WSNs. This chapter gives a prelude on the integration of cloud computing with WSNs and discusses the functional architectures, design issues, benefits and the applications of the sensor cloud infrastructure. In addition, we also developed a general architectural model for precision agriculture application and farmers awareness using sensor cloud.

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References

  1. Rashid, B., Rehmani, M.H.: Applications of wireless sensor networks for urban areas: a survey. J. Netw. Comput. Appl. 60, 192219 (2016)

    Article  Google Scholar 

  2. Rawat, P., Singh, K.D., Chaouchi, H., Bonnin, J.M.: Wireless sensor networks: a survey on recent developments and potential synergies. J. Supercomput. 68, 148 (2014)

    Article  Google Scholar 

  3. Yetgin, H., Cheung, K.T.K., El-Hajjar, M., Hanzo, L.: Network-lifetime maximization of wireless sensor networks. IEEE Access 31, 2191–2226 (2015)

    Article  Google Scholar 

  4. Abo-Zahhad, M., Ahmed, S.M., Sabor, N., Shigenobu Sasaki, S.: Mobile sink based adaptive immune energy-efficient clustering protocol for improving the lifetime and stability period of wireless sensor networks. IEEE Sens. J. 13, 4576–4586 (2015)

    Article  Google Scholar 

  5. Huang, P., Xiao, L., Soltani, S., Mutka, M.W., Xi, N.: The evolution of MAC protocols in wireless sensor networks: a survey. IEEE Commun. Surv. Tutorials 13, 101–120 (2013)

    Article  Google Scholar 

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

    Article  Google Scholar 

  7. Lim, H., Kim, C.: Flooding in wireless Ad Hoc networks. Comput. Commun. 24, 353–363 (2001)

    Article  Google Scholar 

  8. Modi, Z., Jardosh, S., Ranjan, P.: Optimized rumor routing algorithm for wireless sensor networks. In: 2009 Fifth IEEE Conference on Wireless Communication and Sensor Networks (WCSN), pp. 1–6 (2009)

    Google Scholar 

  9. Yildiz, M.E., Scaglione, A., Aysal, T.C.: Computing along the routes via gossiping. In: Information Theory Workshop, ITW 2009, IEEE, pp. 450–454 (2009)

    Google Scholar 

  10. Heinzelman, W.P., Chandrakasan, A.P., Balakrishnan, H.: An application-specific protocol architecture for wireless microsensor networks. IEEE Trans. Wireless Commun. 1, 660–670 (2002)

    Article  Google Scholar 

  11. Deng, S., Li, J., Shen, L.: Mobility-based clustering protocol for wireless sensor networks with mobile nodes. IET Wireless Sens. Syst. 1, 39–47 (2011)

    Article  Google Scholar 

  12. Younis, O., Fahmy, S.: HEED: a hybrid, energy-efficient, distributed clustering approach for Ad Hoc sensor networks. IEEE Trans. Mob. Comput. 3, 1471–1472 (2004)

    Article  Google Scholar 

  13. Velmani, R., Kaarthick, B.: An efficient cluster-tree based data collection scheme for large mobile wireless sensor networks. IEEE Sens. J. 15, 2377–2390 (2015)

    Article  Google Scholar 

  14. Zhang, H., Shen, H.: Energy-efficient beaconless geographic routing in wireless sensor networks. IEEE Trans. Parallel Distrib. Syst. 21, 881–896 (2010)

    Article  Google Scholar 

  15. Zabin, F., Misra, S., Woungang, I., Rashvand, H.F., Ma, N.W., Ali, M.A.: REEP: data-centric, energy-efficient and reliable routing protocol for wireless sensor networks. IET Commun. 2, 995–1008 (2008)

    Article  Google Scholar 

  16. Mell, P., Grance, T.: The NIST Definition of Cloud Computing. National Institute of Standards and Technology Special Publication 800–145, 1–7 (2011)

    Google Scholar 

  17. Definition of Sensor Cloud http://www.sensorcloud.com/documentation

  18. Sheng, Z., Mahapatra, C., Zhu, C., Leung, V.C.M.: Recent advances in industrial wireless sensor networks toward efficient management in IoT. IEEE Access 3, 622–637 (2015)

    Article  Google Scholar 

  19. Fortino, G., Gravinal, R., Russo, W.: Activity-aaService: Cloud-assisted, BSN-based system for physical activity monitoring. In: Proceedings of the 2015 IEEE 19th International Conference on Computer Supported Cooperative Work in Design (CSCWD), pp. 588–593 (2015)

    Google Scholar 

  20. Poy, H.M., Duffy, B.: A cloud-enabled building and fire emergency evacuation application. IEEE Cloud Comput. 1, 40–49 (2014)

    Article  Google Scholar 

  21. Wan, L., Han, G., Shu, L., Feng, N., Zhu, C., Lloret, J.: Distributed parameter estimation for mobile wireless sensor network based on cloud computing in battlefield surveillance system. IEEE Access 3, 1729–1739 (2015)

    Article  Google Scholar 

  22. Sareen, S., Sood, S.K., Gupta, S.K.: A cloud-based seizure alert system for epileptic patients that uses higher-order statistics. Comput. Sci. Eng. 18, 56–67 (2016)

    Article  Google Scholar 

  23. Sareen, S., Sood, S.K., Gupta, S.K.: An automatic prediction of epileptic seizures using cloud computing and wireless sensor networks. J. Med. Syst. 40, 226 (2016)

    Article  Google Scholar 

  24. Ojha, T., Misra, S., Raghuwanshi, N.S.: Sensing-cloud: leveraging the benefits for agricultural applications. Comput. Electron. Agric. 135, 96–107 (2017)

    Article  Google Scholar 

  25. Ferdoush, S., Li, X.: Wireless sensor network system design using Raspberry Pi and Arduino for environmental monitoring applications. In: 9th International Conference on Future Networks and Communications (FNC-2014), Procedia Computer Science, Vol. 34, pp. 103–110 (2014)

    Article  Google Scholar 

  26. http://meteorology.uonbi.ac.ke/sites/default/files/cbps/sps/meteorology/WEATHER.pdf

  27. Gorelik, E.: Cloud Computing Models. Massachusetts Institute of Technology, pp. 1–81 (2013)

    Google Scholar 

  28. Alamri, A., Ansari, W.S., Hassan, M.M., Hossain, M.S., Alelaiwi, A., Hossain, M.A.: A survey on sensor-cloud: architecture, applications, and approaches. Int. J. Distrib. Sens. Netw. (2013)

    Google Scholar 

  29. Yuriyama, M., Kushida, T., Itakura, M.: A new model of accelerating service innovation with sensor-cloud infrastructure. In: SRII Global Conference (SRII), IEEE, pp. 308–314 (2011)

    Google Scholar 

  30. Yuriyama, M., Kushida, T.: Sensor-cloud infrastructure - physical sensor management with virtualized sensors on cloud computing. In: 13th International Conference on Network-Based Information Systems. IEEE (2010)

    Google Scholar 

  31. Madria, S., Kumar, V., Dalvi, R.: Sensor cloud: a cloud of virtual sensors. IEEE Softw. 31, 70–77 (2014)

    Article  Google Scholar 

  32. Maria, A.R., Sever, P., Carlos, V.: Cloud computing for big data from biomedical sensors monitoring, storage and analyze. In: 2015 Conference Grid, Cloud and High Performance Computing in Science (ROLCG), IEEE, pp. 1–4 (2015)

    Google Scholar 

  33. Mustafa, S., Nazir, B., Hayat, A., Khan, A.R., Madani, S.A.: Resource management in cloud computing: taxonomy, prospects, and challenges. Comput. Electr. Eng. 47, 186–203 (2015)

    Article  Google Scholar 

  34. Aslam, S., Islam, S., Khan, A., Ahmed, M., Akhundzada, A., Khan, M.K.: Information collection centric techniques for cloud resource management: taxonomy, analysis and challenges. J. Netw. Comput. Appl. 100, 80–94 (2017)

    Article  Google Scholar 

  35. Schroeter, J., Mucha, P., Muth, M., Jugel, K., Lochau, M.: Dynamic configuration management of cloud-based applications. In: SPLC12 Proceedings of the 16th International Software Product Line Conference, ACM, Vol. 2, pp. 171–178 (2012)

    Google Scholar 

  36. Prahlada Rao, B.B., Saluja, P., Sharma, N., Mittal, A., Sharma, S.V.: Cloud computing for internet of things and sensing based applications. In: Sixth International Conference on Sensing Technology (ICST), pp. 374–380 (2012)

    Google Scholar 

  37. Singh, A., Chatterjee, K.: Cloud security issues and challenges: a survey. J. Netw. Comput. Appl. 79, 88–115 (2017)

    Article  Google Scholar 

  38. Touati, F., Al-Hitmi, M., Benhmed, K., Tabish, R.: A fuzzy logic based irrigation system enhanced with wireless data logging applied to the state of Qatar. Comput. Electron. Agric. 98, 233–241 (2013)

    Article  Google Scholar 

  39. Xiao, D., Feng, J., Wang, N., Luo, X., Hu, Y.: Integrated soil moisture and water depth sensor for paddy fields. Comput. Electron. Agric. 98, 214–221 (2013)

    Article  Google Scholar 

  40. Goumopoulos, C., O’Flynn, B., Kameas, A.: Automated zone-specific irrigation with wireless sensor/actuator network and daptable decision support. Comput. Electron. Agric. 105, 20–33 (2014)

    Article  Google Scholar 

  41. Kim, Y., Jabro, J.D., Evans, R.G.: Wireless lysimeters for real-time online soil water monitoring. Irrig. Sci. 29, 423–430 (2011)

    Article  Google Scholar 

  42. Park, D.H., Kang, B.J., Cho, K.R., Shin, C.S., Cho, S.E., Park, J.W., Yang, W.M.: A study on greenhouse automatic control system based on wireless sensor network. Wireless Pers. Commun. 56, 117–130 (2011)

    Article  Google Scholar 

  43. Lloret, J., Bosch, I., Sendra, S., Serrano, A.: A wireless sensor network for vineyard monitoring that uses image processing. Sensors 11, 6165–6196 (2011)

    Article  Google Scholar 

  44. Srbinovska, M., Gavrovski, C., Dimcev, V., Krkoleva, A., Borozan, V.: Environmental parameters monitoring in precision agriculture using wireless sensor networks. J. Clean. Prod. 88, 297–307 (2015)

    Article  Google Scholar 

  45. Garcia-Sanchez, A.J., Garcia-Sanchez, F., Garcia-Haro, J.: Wireless sensor network deployment for integrating video-surveillance and data-monitoring in precision agriculture over distributed crops. Comput. Electron. Agric. 75, 288–303 (2011)

    Article  Google Scholar 

  46. Lopez Riquelme, J.A., Soto, F., Suardiaz, J., Sanchez, P., Iborra, A., Vera, J.A.: Wireless sensor networks for precision horticulture in Southern Spain. Comput. Electron. Agric. 68, 25–35 (2009)

    Article  Google Scholar 

  47. Gutierrez, J., Villa-Medina, J.F., Nieto-Garibay, A., Porta-Gandara, A.: Automated irrigation system using a wireless sensor network and GPRS module. IEEE Trans. Instrum. Meas. 63, 166–176 (2014)

    Article  Google Scholar 

  48. Ramane, D.V., Patil, S.S., Shaligram, A.D.: Detection of NPK nutrients of soil using fiber optic sensor. In: International Journal of Research in Advent Technology, Special Issue National Conference ACGT 2015 (2015)

    Google Scholar 

  49. Carvajal-Arango, R., Zuluaga-Holguin, D., Mejia-Gutierrez, R.: A systems-engineering approach for virtual/real analysis and validation of an automated greenhouse irrigation system. Int. J. Interact. Des. Manuf. 10, 355–367 (2014)

    Article  Google Scholar 

  50. Katyara, S., Shah, M.A., Zardari, S., Chowdhry, B.S., Kumar, W.: WSN based smart control and remote field monitoring of Pakistan irrigation system using SCADA applications. Wireless Pers. Commun. 95, 491–504 (2017)

    Article  Google Scholar 

  51. Santos, I.M., da Costa, F.G., Cugnasca, C.E., Ueyama, J.: Computational simulation of wireless sensor networks for pesticide drift control. Precision Agric. 15, 90–303 (2014)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Electronics and Communication Engineering, Anna University Regional Campus, Coimbatore, 641046, Tamil Nadu, India

    V. Bhanumathi & K. Kalaivanan

Authors
  1. V. Bhanumathi
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  2. K. Kalaivanan
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Corresponding author

Correspondence to V. Bhanumathi .

Editor information

Editors and Affiliations

  1. Department of Information Technology, Silicon Institute of Technology, Bhubaneswar, India

    Bijan Bihari Mishra

  2. Department of Information and Communication, Fakir Mohan University, Balasore, Odisha, India

    Satchidanand Dehuri

  3. Department of Electrical Engineering, Indian Institute of Technology, New Delhi, India

    Bijaya Ketan Panigrahi

  4. Department of Computer Science and Engineering, Silicon Institute of Technology, Bhubaneswar, India

    Ajit Kumar Nayak

  5. School of Computer Engineering, KIIT University, Bhubaneswar, Odisha, India

    Bhabani Shankar Prasad Mishra

  6. School of Computer Engineering, KIIT University, Bhubaneswar, Odisha, India

    Himansu Das

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Bhanumathi, V., Kalaivanan, K. (2019). Application Specific Sensor-Cloud: Architectural Model. In: Mishra, B., Dehuri, S., Panigrahi, B., Nayak, A., Mishra, B., Das, H. (eds) Computational Intelligence in Sensor Networks. Studies in Computational Intelligence, vol 776. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-57277-1_12

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