An Adaptive Qos Aware Routing with Energy Efficient Approach for Biomedical Wireless Sensor Networks

  • Authors

    • D. Jayasutha
    • C. Kalaiarasan
    https://doi.org/10.14419/ijet.v7i3.20.22943
  • BWSN, QoS, energy efficiency, AQSREE, window size adjustment, packet prioritization

  • Abstract

    Biomedical Wireless Sensor Networks (BWSNs) supports the advancement of new health careservices regarding patient monitoring for continuous assessment of patient health and medical diagnosis within affordable cost. On the other hand, dealing with medical data, BWSN should develop mechanisms to provide a high quality of service (QoS) level. As well, BWSN composed with the typical battery powered sensor nodes and these additional QoS mechanisms make extra energy consumption that significantly reduces the lifetime of the network. The network lifetimeis consequently significant feature to assure the needs of QoS.Since, to enhance the network lifetime and its capacity to provide the required QoS new schemes are essential for BWSN.Thus, in this paper, an adaptive QoS aware routing with energy efficient (AQSREE) approach has been proposed for BWMS to assure the QoS of various packets at the same time it minimize the energy consumption of the nodes thus prolonging the lifetime of the network. The proposed AQSREE differentiates the ordinary packets and emergency packet before transmitting in each queue of the node and also selects the optimal route to reach the sink node by considering the packet transmission time, energy level and the link load fulfill the QoS requirements. Additionally, the AQSREE adjusts the contention window size adeptly for energy efficiency with respect to the data rate and energy level. The simulation results show that the proposed AQSREE approach can effectively reduce the energy consumption by ensuring the QoS requirements of BWSN.

     

     

  • References

    1. [1] Xuedong Liang, IlangkoBalasingham, Sang-SeonByun, “A reinforcement learning based routing protocol with QoS support for biomedical sensor networksâ€, IEEE International Symposium on Applied Sciences on Biomedical and Communication Technologies, Aalborg, pp. 1-5, 2008

      [2] Md. AbdurRazzaque, ChoongSeonHong andSungwon Lee, “Data-Centric MultiobjectiveQoS-Aware Routing Protocol for Body Sensor Networksâ€, Sensors, vol. 11, pp. 917-937, 2011

      [3] Carlos Abreua, Manuel Ricardob, P.M. Mendes, “Energy-aware routing for biomedical wireless sensor networksâ€, Journal of Network and Computer Applications, vol. 40, pp. 270-278, 2014

      [4] Carlos Abreu and P. M. Mendes, “Extending Lifetime of Biomedical Wireless Sensor Networks using Energy-Aware Routing and Relay Nodesâ€, International Journal of E-Health and Medical Communications (IJEHMC), vol. 5, no. 4, 2014

      [5] Zahoor Ali Khan,ShyamalaSivakumar, William Phillips, and Bill Robertson, “ZEQoS: A New Energy and QoS-Aware Routing Protocol for Communication of Sensor Devices in Healthcare Systemâ€, International Journal of Distributed Sensor Networks, vol. 2014, Article ID. 627689, pp. 1-18, 2014

      [6] [6] Zahoor A. Khan, ShyamalaSivakumar, William Phillips, Bill Robertson, and NadeemJavaid, “QPRD: QoS-Aware Peering Routing Protocol for Delay-Sensitive Data in Hospital Body Area Networkâ€, Mobile Information Systems, vol. 2015, article id. 153232, pp. 1-16, 2015

      [7] VahidAyatollahitafti,MdAsriNgadi, Johan bin Mohamad Sharif, and Mohammed Abdullahi, “An Efficient Next Hop Selection Algorithm for Multi-Hop Body Area Networksâ€, PLoS One, vol. 11, no. 1, 2016

      [8] Carlos Abreu, Francisco Miranda, Manuel Ricardo, and Paulo Mateus Mendes, “QoS-based management of biomedical wireless sensor networks for patient monitoringâ€, Springerplus, vol.3, 239, 2014

      [9] Muhammad Sajjad Akbar, Hongnian Yu, and ShuangCang, “Delay, Reliability, and Throughput Based QoS Profile: A MAC Layer Performance Optimization Mechanism for Biomedical Applications in Wireless Body Area Sensor Networksâ€, Journal of Sensors, vol.2016, article id. 7170943, pp.1-17, 2016

      [10] Guowei Wu, JiankangRen, Feng Xia, Lin Yao, ZichuanXu, and Pengfei Shang, “A Game Theoretic Approach for Interuser Interference Reduction in Body Sensor Networksâ€, International Journal of Distributed Sensor Networks, vol. 2011, article id. 329524, pp. 1-12, 2011

      [11] Cui Chunsheng, Yang Yongjian, and Huang Liping, “A Cross-Layer Cooperation Mechanism of Wireless Networks Based on Game Theoryâ€, IEEE International Conference on Distributed Computing in Sensor Systems, Cambridge, MA, pp. 223 – 230, 2013

      [12] Young-Duk Kim, Won-Seok Kang, Dong-Ha Lee, and Jae-Hwang Yu,“Distance Adaptive Contention Window Mechanism for Wireless Sensor Networksâ€, IEICE International Technical Conference on Circuits/Systems, Computers and Communications, pp. 1693-1696, 2008.

      [13] 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

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

      [15] MajidGholipour, AbolfazlToroghiHaghighatand Mohammad Reza Meybodi, “Hop-by-hop traffic-aware routing to congestion control in wireless sensor networksâ€, EURASIP Journal on Wireless Communications and Networking, vol. 15, pp. 1-13, 2015

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  • How to Cite

    Jayasutha, D., & Kalaiarasan, C. (2018). An Adaptive Qos Aware Routing with Energy Efficient Approach for Biomedical Wireless Sensor Networks. International Journal of Engineering & Technology, 7(3.20), 567-572. https://doi.org/10.14419/ijet.v7i3.20.22943

    Received date: 2018-12-02

    Accepted date: 2018-12-02