Performance metrics in wireless sensor networks :a survey and outlook

  • Authors

    • E Ramya
    • R Gobinath
    2018-05-07
    https://doi.org/10.14419/ijet.v7i2.26.12527
  • Wireless Sensor Networks, Quality of Service, Performance Parameters, Wireless Body Area Sensor Networks

  • Abstract

    Data mining plays an important role in analysis of data in modern sensor networks. A sensor network is greatly constrained by the various challenges facing a modern Wireless Sensor Network. This survey paper focuses on basic idea about the algorithms and measurements taken by the Researchers in the area of Wireless Sensor Network with Health Care. This survey also catego-ries various constraints in Wireless Body Area Sensor Networks data and finds the best suitable techniques for analysing the Sensor Data. Due to resource constraints and dynamic topology, the quality of service is facing a challenging issue in Wireless Sensor Networks. In this paper, we review the quality of service parameters with respect to protocols, algorithms and Simulations.

     

  • References

    1. [1] Bansal, Nikhil, and Zhen Liu. "Capacity, delay and mobility in wireless ad-hoc networks." INFOCOM 2003. Twenty-Second Annual Joint Conference of the IEEE Computer and Communications. IEEE Societies. Vol. 2. IEEE, 2003.

      [2] Neely, Michael J., and Eytan Modiano. "Capacity and delay tradeoffs for ad hoc mobile networks." IEEE Transactions on Information Theory 51.6 (2005): 1917-1937.

      [3] Groenevelt, Robin, Philippe Nain, and Ger Koole. "The message delay in mobile ad hoc networks." Performance Evaluation 62.1 (2005): 210-228.

      [4] Layuan, Li, Li Chunlin, and Yaun Peiyan. "Performance evaluation and simulations of routing protocols in ad hoc networks." Computer Communications 30.8 (2007): 1890-1898.

      [5] Bobade, Nilesh P., and Nitiket N. Mhala. "Performance evaluation of ad hoc on demand distance vector in manets with varying network size using ns-2 simulation." International Journal on Computer Science and Engineering (IJCSE) 2.08 (2010): 2731-2735.

      [6] Nikam, Samiksha, and B. T. Jadhav. "DELAY ANALYSIS OF ADHOC NETWORK USING NS 2.34." International Journal of Current Research and Review 8.9 (2016): 7.

      [7] Jabeen Q, Khan F, Khan S, Jan MA. Performance improvement in multihop wireless mobile adhoc networks. the Journal Applied, Environmental, and Biological Sciences (JAEBS). 2016;6:82-92.

      [8] Chiasserini, C-F., and Michele Garetto. "Modeling the performance of wireless sensor networks." In INFOCOM 2004. Twenty-third AnnualJoint Conference of the IEEE Computer and Communications Societies, vol. 1. IEEE, 2004.

      [9] Akkaya, Kemal, Mohamed Younis, and Meenakshi Bangad. "Sink repositioning for enhanced performance in wireless sensor networks." Computer Networks 49.4 (2005): 512-534.

      [10] Small, Tara, and Zygmunt J. Haas. "Resource and performance tradeoffs in delay-tolerant wireless networks." Proceedings of the 2005 ACM SIGCOMM workshop on Delay-tolerant networking. ACM, 2005.

      [11] Kim, Joohwan, et al. "Minimizing delay and maximizing lifetime for wireless sensor networks with anycast." IEEE/ACM Transactions on Networking (TON) 18.2 (2010): 515-528.

      [12] Lu, Gang, et al. "Delay efficient sleep scheduling in wireless sensor networks." INFOCOM 2005. 24th Annual Joint Conference of the IEEE Computer and Communications Societies. Proceedings IEEE. Vol. 4. IEEE, 2005.

      [13] Liang, Zhongliang, et al. "Delay performance analysis for supporting real-time traffic in a cognitive radio sensor network." IEEE Transactions on Wireless Communications 10.1 (2011): 325-335.

      [14] Pasalkar, Jayashree C., Vivek S. Deshpande, and Dattatary Waghole. "Performance analysis of delay in wireless sensor networks." Trends in innovative computing (2012): 192-195.

      [15] Khan, Shahzad, Fazlullah Khan, and Sher Afzal Khan. "Delay and throughput performance improvement in wireless sensor and actor networks." Information Technology: Towards New Smart World (NSITNSW), 2015 5th National Symposium on. IEEE, 2015.

      [16] Yaqoob, M. M., et al. "Transmission delay of multi-hop heterogeneous networks for medical applications." Broadband, Wireless Computing, Communication and Applications (BWCCA), 2012 Seventh International Conference on. IEEE, 2012.

      [17] Liang, Xuedong, and Ilangko Balasingham. "Performance analysis of the IEEE 802.15. 4 based ECG monitoring network." Proceedings of the 7th IASTED International Conferences on Wireless and Optical Communications. 2007.

      [18] Javaid, Nadeem, et al. "Analyzing delay in wireless multi-hop heterogeneous body area networks." arXiv preprint arXiv:1304.1059 (2013).

      [19] Khan, Jamil Y., Mehmet R. Yuce, and Farbood Karami. "Performance evaluation of a wireless body area sensor network for remote patient monitoring." Engineering in Medicine and Biology Society, 2008. EMBS 2008. 30th Annual International Conference of the IEEE. IEEE, 2008.

      [20] Akbar, Muhammad Sajjad, Hongnian Yu, and Shuang Cang. "Delay, reliability, and throughput based QoS profile: A MAC layer performance optimization mechanism for biomedical applications in wireless body area sensor networks." Journal of Sensors 2016 (2016).

      [21] Cao, Huasong, Sergio González-Valenzuela, and Victor CM Leung. "Employing IEEE 802.15. 4 for quality of service provisioning in wireless body area sensor networks." Advanced Information Networking and Applications (AINA), 2010 24th IEEE International Conference on. IEEE, 2010.

      [22] Al Masud, Shah Murtaza Rashid. "Qos taxonomy towards wireless body area network solutions." International Journal of Application or Innovation in Engineering & Management (IJAIEM) 2 (2013): 221-234.

      [23] Hema.C.R, Paulraj.M.P & Ramkumar.S, “Classification of Eye Movements Using Electrooculography and Neural Networksâ€, International Journal of Human Computer Interaction, Vol.5(4), pp.51-63, 2014.

      [24] Hema, C. R., Ramkumar, S., & Paulraj, M. P. , “Idendifying Eye Movements using Neural Networks for Human Computer Interactionâ€, International Journal of Computer Applications, 105(8), pp 18-26, 2014.

      [25] S.Ramkumar, K.SatheshKumar, G.Emayavaramban, â€EOG Signal Classification Using Neural Network for Human Computer Interactionâ€, International Journal of Computer Theory and Applications, Vol.9(24) , pp.223-231, 2016

      [26] Ramkumar, Dr.K.Satheshkumar and G.Emayavaramban†Nine States HCI using Electrooculogram and Neural Networksâ€, IJET, Vol. 8(6), pp. 3056-3064 , Jan 2017.

      [27] S.Ramkumar, K.Sathesh Kumar G.Emayavaramban,†A Feasibility Study On Eye Movements Using Electrooculogram Based HCI†IEEE- International Conference on Intelligent Sustainable Systems, pp.384-388, Dec-2017.

      [28] G.Emayavaramban, S.Ramkumar, A.Amudha and K.Sathesh Kumar “Classification Of Hand Gestures Using FFNN And TDNN Networksâ€, International Journal of Pure And Applied Mathematics, Vol.118(8) Pp. 27-32, Jan 2018.

      [29] S.Ramkumar , K.Sathesh Kumar, T.Dhiliphan Rajkumar, M.Ilayaraja, K.Shankar, “A review-classification of electrooculogram based human computer interfacesâ€, Biomedical Research, 29(6), Pp. 1078-1084, April 2018.

  • Downloads

  • How to Cite

    Ramya, E., & Gobinath, R. (2018). Performance metrics in wireless sensor networks :a survey and outlook. International Journal of Engineering & Technology, 7(2.26), 25-30. https://doi.org/10.14419/ijet.v7i2.26.12527

    Received date: 2018-05-06

    Accepted date: 2018-05-06

    Published date: 2018-05-07