Optimizing Network QoS Using Multichannel Lifetime Aware Aggregation-Based Routing Protocol

  • Uma K. ThakurEmail author
  • C. G. Dethe
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 898)


Improvement in quality of service (QoS) of wireless networks has always been a study subject for wireless network designers worldwide. Optimization of end-to-end communication delay, reduction in energy consumption, improvement in network throughput and reduction in end-to-end communication delay jitter are some of the parameter optimizations which are used to improve the QoS of the wireless networks. In this paper, we propose a QoS aware routing protocol which uses a combination of delay and energy aware routing with data aggregation and multichannel communication in order to reduce the energy consumption, reduce the end-to-end delay and improve the network throughput. The simulation results show that there is a more than 20% improvement in network communication speed, and at least 15% improvement in the network lifetime after using the proposed QoS aware routing protocol.


QoS Delay Throughput Aggregation Multichannel Energy aware 


  1. 1.
    Bizagwira, H., Toussaint, J., Misson, M.: Multi-channel routing protocol for dynamic WSN. In: Wireless Days (WD). IEEE (2016)Google Scholar
  2. 2.
    Zhao, M., Ho, I.W.-H., Chong, P.H.J.: An energy-efficient region-based AODV routing protocol for low-power and lossy networks. IEEE Int. Things J. (2012)Google Scholar
  3. 3.
    Barcelo, M., Correa, A., Vicario, J.L., Morell, A., Vilajosana, X.: Addressing mobility in AODV with position assisted metrics. IEEE Sens. J. 16(7) (2016)Google Scholar
  4. 4.
    Ko, J., Chang, M.: MoMoRo: providing mobility support for low-power wireless applications. IEEE Syst. J. 9(2) (2015)CrossRefGoogle Scholar
  5. 5.
    Kulkarni, R.V., Förster, A., Venayagamoorthy, G.K.: Computational intelligence in wireless sensor networks: a survey. IEEE Commun. Surv. Tutor. 13(1) (2011)CrossRefGoogle Scholar
  6. 6.
    Forster, A., Murphy, A.L.: FROMS: feedback routing for optimizing multiple sinks in WSN with reinforcement learning. National Competence Center in Research on Mobile Information and Communication Systems (NCCR-MICS) (2010)Google Scholar
  7. 7.
    Kaur, R., Rai, M.K.: A novel review on routing protocols in MANETs. Undergrad. Acad. Res. J. (UARJ) 1(1) (2012). ISSN 2278-1129Google Scholar
  8. 8.
    Usha, M., Jayabharathi, S., Banu R.W.: REAODV: an enhanced routing algorithm for QoS support in wireless ad-hoc sensor networks. In: IEEE International Conference on Recent Trends in Information Technology (2011)Google Scholar
  9. 9.
    Gupta, P., Kumar, P.R.: The capacity of wireless networks. IEEE Trans. Inf. Theory 46(2), 388–404 (2007)MathSciNetCrossRefGoogle Scholar
  10. 10.
    Khabbazian, M., Bhargava V.K.: Localized broadcasting with guaranteed delivery and bounded transmission redundancy. IEEE Trans. Comput. 57(8), 1072–1086 (2008)MathSciNetCrossRefGoogle Scholar
  11. 11.
    Shen, Z., Thomas, J.P.: Security and QoS self-optimization in mobile ad hoc networks. IEEE Trans. Mob. Comput. 7, 1138–1151 (2008)CrossRefGoogle Scholar
  12. 12.
    Asutkar, G.M., Rangaree, P.: Design of self-powered wireless sensors network using hybrid PV-wind system. In: IEEE 10th International Conference on Intelligent System and Control (ISCO) (2016)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Sant Gadge Baba Amravati UniversityAmravatiIndia

Personalised recommendations