Efficient and Compressive Hybrid Data Dissemination Model with Data Aggregation in Healthcare Applications Using WSN

  • Authors

    • SyeD Abdul Raheem
    • Dr. M. Prabhakar
    • Dr. C. Venugopal
    • Kumar Gillela
    https://doi.org/10.14419/ijet.v7i3.20.22948
  • Wireless Sensor network, Healthcare application, Data aggregation, Energy consumption, Compressive data sensing
  • Wireless sensor Networks (WSN) have great attention within the past years to provide the choices of flexibilities and save the value of patients and health care activities. Constant time, during disaster events, there is a developing health care area which is able to produce actual care to the patient. For the reason, equipment’s are modified to observe the patient that has great attention to enhance the efficiency and Quality value of health care. Huge amount of real-time information on the hospitals Sensors used to monitor the patient information that turns out a progressively. The medical data of a private is extremely sensitive; it is an important problem in a hospital during the transmission of this information through wireless networks. For communication the information size get reduces in data aggregation. This paper aims to reduce the traffic within the cluster so as to enhance the energy efficiency and for that purpose a hybrid data dissemination model is proposed which uses the enhanced comb needle model and compressive data sensing. Comb Needle Model is the simplest network that can be compared with proposed hybrid data dissemination model by exploitation the parameters like the ratio of packet delivery, average delay, throughput, and cost of communication and intake of energy.

     

     

     
  • References

    1. [1] S. Hill, et al., “System Architecture Directions for Networked Sensors,†ASPLOS, 2001.

      [2] J.W. Kaiser, et al., “Wireless Integrated Network Sensors,†Communications of the ACM, vol. 42, no. 5, pp. 552-8, May 2009.

      [3] X. Liu, W. He et al, "PDA: privacy-preserving data aggregation in wireless sensor networks,†Proceedings of the 26th IEEE International Conference on Computer Communications (INFOCOM’07), pp. 2046-2054, Anchorage, USA, June 2007.

      [4] E. J. Coyle, et al., “An energy efficient hierarchical clustering algorithm for wireless sensor networks†.In INFOCOM 2003. Twenty-Second Annual Joint Conference of the IEEE Computer and Communications. IEEE Societies Vol. 7, pp. 1719- 1732.

      [5] Candies. J and M. S. Wakin, et al.,â€An Introduction To Compressive Sampling†IEEE Signal Processing Magazine, Volume: 9, Issue: 3, Pages: 31 – 40, 2008.

      [6] P. K. Chen. Et al., “Compressive data gathering for large-scale wireless sensor networksâ€, In Proceedings of MobiCom. 2009.

      [7] Stephen Lmdsey, et al., “PEGASIS: Power-Efficient Gathering in Sensor Information Systems†in IEEE – 2005.

      [8] Estrin Deborah, et al., “Impact of network density on data aggregation in wireless sensor networks†in IEEE 2006.

      [9] Wei Hong, et al., “A Tiny Aggregation Service for Ad-Hoc Sensor Networks “, in ACM 2009.

      [10] S. ChangjinSuh, et al., “CREEC: Chain Routing with Even Energy Consumption,†in IEEE Communications and Networks, pp. 18-25, 2011.

      [11] M. Rabbat, et al, “Compressed sensing for networked data, IEEE Signal Process†Mag. 24 92–101, 2010.

      [12] S.K. Ghosh., et al.,†Enhancement of lifetime using duty cycle and network coding in wireless sensor networksâ€, IEEE Trans. Wirel. Commun. 654–667, 2013.

      [13] S.-Y. Li, et al., Linear network coding, IEEE Transaction Information Theory 49 (3)373–383, 2005.

      [14] R. Chakrabarti, et al., “Co-operative routing for WSN using network codingâ€, IET Wireless Sensor System 2, 75–85, 2012.

      [15] M.S. Wong, et al.,†Fast and simultaneous data aggregation over multiple regions in WSNâ€, IEEE Transaction System Man Cybern. – Part B: Application Rev. 41 (2) 343–353, 2012.

      [16] K. Das, et al., “A survey for Routing correlated data in WSNâ€, in: IEEE Network, pp. 41–48, 2007.

      [17] E.Kamal, et al., “Network coding-based on protection of many-to-one wireless flowsâ€, IEEE Journal of Sel. Areas Communication 25 (5) 796–811, 2008.

      [18] A. Rossi, et al., “IRIS: integrated data gathering and interest dissemination system for wireless sensor networksâ€, Ad Hoc Netw. 13 (3) 657–675, 2014.

      [19] M. Wakin, et al. “An introduction to compressive samplingâ€, IEEE Signal Process. Mag. 23 (2) 27–34, 2006.

      [20] A. F. Duarte, et al., “Introduction to compressed sensingâ€, chapter2- 2011.

      [21] D.L. Donohol et al. “Compressed sensingâ€, IEEE Trans. Inform. Theory 52 (4) 1289–1306, 2006.

      [22] Pradeep Kumar, et al., “Efficient-Strong Authentication Protocol for Healthcare Applications Using Wireless Medical Sensor Networks, 12, 1635 – 1657, 2015.

      [23] Surya devara, N. S., “A Realistic Approach Wireless Sensor Network Based Safe Home to Care Elderly Peopleâ€, Recent Advances in Intelligent Computational Systems (RAICS), IEEE 2011.

      [24] Townsendy, K., et all, “Recent Advances and Future Trends on Low Power Wireless Systems for Medical Applications, Proceedings, 5th International Workshop on System-on-Chip for Real-Time Applications, pages 473 -475, 2008.

      [25] Kumar S, Hareesh, “Health Care disparities in Rural Areas†National Healthcare Disparities Report, 2004.

      [26] MuhammedShafi. P,Selvakumar.S*, Mohamed Shakeel.P, “An Efficient Optimal Fuzzy C Means (OFCM) Algorithm with Particle Swarm Optimization (PSO) To Analyze and Predict Crime Dataâ€, Journal of Advanced Research in Dynamic and Control Systems, Issue: 06,2018, Pages: 699-707

      [27] Selvakumar, S & Inbarani, Hannah & Mohamed Shakeel, P. (2016). A hybrid personalized tag recommendations for social E-Learning system. 9. 1187-1199.

      [28] Dishongh, Terrance, et al, “Wireless Sensor Networks for Healthcare Applicationsâ€, Artech House Publishing, 2010.

      [29] Hongwei, Huo, et all, “An Elderly Health Care System Using Wireless Sensor Networks at Homeâ€, 3rd International Conference on Sensor Technologies and Applications, Vol 2,pp 453-462, 2009.

      [30] Anuroop, Chandra, et al, “Elder Care Based on Cognitive Sensor Networkâ€, IEEE Journal of Sensors Network, Vol. 1, No. 9, March 2012.

  • Downloads

  • How to Cite

    Abdul Raheem, S., M. Prabhakar, D., C. Venugopal, D., & Gillela, K. (2018). Efficient and Compressive Hybrid Data Dissemination Model with Data Aggregation in Healthcare Applications Using WSN. International Journal of Engineering & Technology, 7(3.20), 593-598. https://doi.org/10.14419/ijet.v7i3.20.22948