Skip to main content
Log in

Impact of Residual Life Estimator Battery Model on QoS Issues in MANET

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

The objective of the research is to analyze, simulate and do a performance comparison of three MANET routing protocols namely AODV, DSR and DYMO under Residual Life Estimator Battery Model in QualNet 5.0. The significant metrics used for comparative study are- throughput, average end-to-end delay, jitter and total power consumption. The nodes of designed scenario communicate all the way through constant bit rate (CBR) application traffic. Multiple runs are performed with different time durations of 10–60 min for each protocol and the collected data are averaged over those runs. By analyzing how a protocol performs, helps in choosing a protocol best suited to particular set of conditions. We found that AODV is best performer under CBR traffic for MANET nodes operated through residual life estimator battery model.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. Zhao, W., & Ammar, M. E. Z. (2005). The energy-limited capacity of wireless networks, In IEEE communications society conference on sensor and ad hoc communications and networks, pp. 279–288.

  2. Kumar, D., & Kumar, V. (2009). EAAC: Energy-aware admission control scheme for ad hoc network. World Academy of Science, Engineering and Technology, 51, 934–942.

    Google Scholar 

  3. Stojmenovic, I., & Lin, X. (2001). Power-aware localized routing in wireless networks. IEEE Transactions on Parallel and Distributed Systems, 12(11), 1122–1133.

    Article  Google Scholar 

  4. Rango, F. D., Fotino, M., & Marano, S. (2008). EE-OLSR: Energy efficient OLSR routing protocol for mobile ad hoc networks. In Proceedings of the military communications conference (MILCOM) (pp. 1–7). IEEE.

  5. Kanjanarot, J., Sitthi, K., & Saivichit, C. (2006). Energy-based route discovery mechanism in mobile ad hoc networks, ICA0T2006 (pp. 1967–1972).

  6. Singh, S., Woo, M., & Raghavendra, C. S. (1998). Power aware routing in mobile ad hoc networks, In Proceedings of the 4th annual ACM/IEEE international conference on mobile computing and networking (pp. 181–190). ACM Press.

  7. Gopinath, S., Rajaram, A., & Suresh Kumar, N. (2012). Improving minimum energy consumption in ad hoc networks under different scenarios. International Journal of Advanced and Innovative Research (IJAIR), 1(4), 40–46.

    Google Scholar 

  8. Kumar, A., Rafiq, M. Q., & Bansal, K. (2012). Performance evaluation of energy consumption in MANET (0975–8887). International Journal of Computer Applications, 42(2), 7–12.

    Article  Google Scholar 

  9. Suganya S., & Palaniammal, S. (2012). A dynamic approach to optimize energy consumption in mobile ad hoc network, European Journal of Scientific Research ISSN 1450-216X, 85(2), 225–232.

  10. Banerjee, N., Rahmati, A., Corner, M. D., Rollins, S., & Zhong, L. (2007). Users and batteries: Interactions and adaptive energy management in mobile systems, In Proceedings of the 9th international conference on Ubiquitous computing, ser. UbiComp’07 (pp. 217–234). Berlin, Heidelberg: Springer.

  11. Maurya, S. K., Rahul, S., & Rajvanshi, Y. (2012). Evaluation of LANMAR and DSR ad hoc routing protocol for various battery models in MANET using QualNet. International Journal of Computer Networks and Wireless Communications(2250-3501), 2(6), 709–716.

    Google Scholar 

  12. Sangwan, R., Duhan, M., & Dahiya, S. (2013). Energy Consumption analysis of ad hoc routing protocols for different energy models in MANET. IOSR Journal of Electronics and Communication Engineering (2278–8735), 6(4), 48–55.

    Article  Google Scholar 

  13. Shrotriya, A., & Nitnawwre, D. (2012). Energy efficient modeling of wireless sensor networks based on different modulation schemes using QualNet. International Journal of Scientific Engineering and Technology (2277–1581), 1(3), 171–174.

    Google Scholar 

  14. Vir, D., Agarwal, S. K., & Imam, S. A. (2013). Analysis on open-source networks of MAC, energy model for IEEE 802.11 standards using QualNet simulator. International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering (2278–8875), 2(5), 1781–1792.

    Google Scholar 

  15. Namith, T., & Shankpal, P. (2012). Design and development of efficient battery charging and cell balancing for battery management system. SASTECH Journal, 11(2), 15–22.

    Google Scholar 

  16. Kaur, R., & Singh, G. (2014). Models provided in QualNet for wireless ad hoc networks—A review. International Journal of Advanced Research in Computer Science and Software Engineering (2277–128X), 4(3), 826–834.

    Google Scholar 

  17. Ray, N. K., & Turuk, A. K. (2014). A technique to improve network lifetime in mobile ad hoc networks. International Journal of Communication Systems,. doi:10.1002/dac.2784.

    Google Scholar 

  18. Li, P., Guo, S., Hu, J., & Sarker, R. (2014). Lifetime optimization for reliable broadcast and multicast in wireless ad hoc networks. Wireless Communications and Mobile Computing, 14, 221–231. doi:10.1002/wcm.1247.

    Article  Google Scholar 

  19. Varaprasad, G. (2014). Stable routing algorithm for mobile ad hoc networks using mobile agent. International Journal of Communication Systems, 27, 163–170. doi:10.1002/dac.2354.

    Article  Google Scholar 

  20. Hassan, M. M., Kamruzzaman, S. M., Alamri, A., Almogren, A., Alelaiwi, A., Alnuem, M., Islam M. M., & Razzaque, M. A. (2014). Design of an energy-efficient and reliable data delivery mechanism for mobile ad hoc networks: A cross-layer approach. Concurrency and Computation: Practice and Experience, 27, 2637–2655. doi:10.1002/cpe.3309.

    Article  Google Scholar 

  21. Shah, S. C. (2014). Energy efficient and robust allocation of interdependent tasks on mobile ad hoc computational grid. Concurrency and Computation: Practice and Experience,. doi:10.1002/cpe.3297.

    Google Scholar 

  22. Kostin, A., Oz, G., & Haci, H. (2014). Performance study of a wireless mobile ad hoc network with orientation-dependent internodes communication scheme. International Journal of Communication Systems, 27, 322–340. doi:10.1002/dac.2363.

    Article  Google Scholar 

  23. Jayakumar, G., & Ganapathy, G. (2007). Performance comparison of mobile ad-hoc network routing protocol, International Journal of computer science and network Security, 7(11).

  24. Perkins, C., Belding-Royer, E., & Das, S. (2003). RFC 3561, ad hoc on-demand distance vector (AODV) routing. https://www.ietf.org/rfc/rfc3561.txt.

  25. Johnson, D. B., Maltz, D. A., Hu, Y.-C., & Jetcheva, J. G. (2002). Draft-ietf-manet-dsr-07, “the dynamic source routing protocol for mobile ad hoc networks (DSR)”. https://tools.ietf.org/html/draft-ietf-manet-dsr-07.

  26. Perkins, C., & Chakeres, I. (2007). IETF draft < draft-ietf-manet-dymo-09>, “Dynamic MANET on-demand (DYMO) routing”.

  27. http://www.duracell.com.

  28. QualNet documentation, QualNet Model Library, QualNet. http://www.scalablenetworks.com.

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sonika Kandari.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kandari, S., Pandey, M.K. Impact of Residual Life Estimator Battery Model on QoS Issues in MANET. Wireless Pers Commun 86, 601–614 (2016). https://doi.org/10.1007/s11277-015-2947-4

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-015-2947-4

Keywords

Navigation