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Intelligent energy-aware efficient routing for MANET

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Abstract

Designing an energy efficient routing protocol is one of the main issue of Mobile Ad-hoc Networks (MANETs). It is challenging task to provide energy efficient routes because MANET is dynamic and mobile nodes are fitted with limited capacity of batteries. The high mobility of nodes results in quick changes in the routes, thus requiring some mechanism for determining efficient routes. In this paper, an Intelligent Energy-aware Efficient Routing protocol for MANET (IE2R) is proposed. In IE2R, Multi Criteria Decision Making (MCDM) technique is used based on entropy and Preference Ranking Organization METHod for Enrichment of Evaluations-II (PROMETHEE-II) method to determine efficient route. MCDM technique combines with an intelligent method, namely, Intuitionistic Fuzzy Soft Set (IFSS) which reduces uncertainty related to the mobile node and offers energy efficient route. The proposed protocol is simulated using the NS-2 simulator. The performance of the proposed protocol is compared with the existing routing protocols, and the results obtained outperforms existing protocols in terms of several network metrics.

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References

  1. Ali, H., Shahzad, W., & Khan, F. A. (2012). Energy-efficient clustering in mobile ad-hoc networks using multi-objective particle swarm optimization. Applied Soft Computing, 12(7), 1913–1928.

    Article  Google Scholar 

  2. Cho, J.-H., Chen, R., & Chan, K. S. (2016). Trust threshold based public key management in mobile ad hoc networks. Ad Hoc Networks, 44, 58–75.

    Article  Google Scholar 

  3. Priya, K. S., Revathi, T., Muneeswaran, K., & Vijayalakshmi, K. (2015). Heuristic routing with bandwidth and energy constraints in sensor networks. Applied Soft Computing, 29, 12–25.

    Article  Google Scholar 

  4. Yadav, A. K., & Tripathi, S. (2016). Qmrprns: Design of qos multicast routing protocol using reliable node selection scheme for manets. Peer-to-Peer Networking and Applications. doi:10.1007/s12083-016-0441-8.

  5. Verdone, R., Dardari, D., Mazzini, G., & Conti, A. (2010). Wireless sensor and actuator networks: Technologies, analysis and design. London: Academic Press.

    Google Scholar 

  6. Das, S. K., Kumar, A., Das, B., & Burnwal, A. P. (2013). Ethics of e-commerce in information and communications technologies. International Journal of Advanced Computer Research, 3(1), 122–124.

    Google Scholar 

  7. Dardari, D., Conti, A., Buratti, C., & Verdone, R. (2007). Mathematical evaluation of environmental monitoring estimation error through energy-efficient wireless sensor networks. IEEE Transactions on Mobile Computing, 6(7), 790–802.

    Article  Google Scholar 

  8. Das, S. K., Kumar, A., Das, B., & Burnwal, A. P. (2013). Ethics of reducing power consumption in wireless sensor networks using soft computing techniques. International Journal of Advanced Computer Research, 3, 301–304.

    Google Scholar 

  9. Yadav, A. K., & Tripathi, S. (2015). Dlbmrp: Design of load balanced multicast routing protocol for wireless mobile ad-hoc network. Wireless Personal Communications, 85(4), 1815–1829.

    Article  Google Scholar 

  10. Ilgin, M. A., Gupta, S. M., & Battaïa, O. (2015). Use of MCDM techniques in environmentally conscious manufacturing and product recovery. Journal of Manufacturing Systems, 37, 746–758.

    Article  Google Scholar 

  11. Lu, A., & Ng, W. (2005). Vague sets or intuitionistic fuzzy sets for handling vague data: Which one is better? In International conference on conceptual modeling, pp. 401–416. Berlin: Springer.

  12. Das, S. K., Tripathi, S., & Burnwal, A. P. (2015). Fuzzy based energy efficient multicast routing for ad-hoc network. In 2015 third international conference on computer, communication, control and information technology (C3IT), pp. 1–5. New York: IEEE.

  13. Das, S. K., Tripathi, S., & Burnwal, A. P. (2015). Design of fuzzy based intelligent energy efficient routing protocol for wanet. In 2015 Third international conference on computer, communication, control and information technology (C3IT), pp. 1–4. New York: IEEE.

  14. Das, S K., Tripathi, S., & Burnwal, A. P. (2015). Intelligent energy competency multipath routing in wanet. In Information systems design and intelligent applications, pp. 535–543. Berlin: Springer.

  15. Zeshui, X., & Zhao, N. (2016). Information fusion for intuitionistic fuzzy decision making: An overview. Information Fusion, 28, 10–23.

    Article  Google Scholar 

  16. Sridhar, S., Baskaran, R., & Chandrasekar, P. (2013). Energy supported AODV (EN-AODV) for QoS routing in MANET. Procedia-Social and Behavioral Sciences, 73, 294–301.

    Article  Google Scholar 

  17. Chao, G., & Zhu, Q. (2014). An energy-aware routing protocol for mobile ad hoc networks based on route energy comprehensive index. Wireless Personal Communications, 79(2), 1557–1570.

    Article  Google Scholar 

  18. Lou, C., & Zhuang, W. (2015). Energy-efficient routing over coordinated sleep scheduling in wireless ad hoc networks. Peer-to-peer networking and applications, pp. 1–13.

  19. Ravi, G., & Kashwan, K. R. (2015). A new routing protocol for energy efficient mobile applications for ad hoc networks. Computers & Electrical Engineering, 48, 77–85.

    Article  Google Scholar 

  20. Abirami, S., Bhanumathi, V., & Dhanasekaran, R. (2012). A balanced approach for power aware routing in MANET using fuzzy logic. In IJCA proceedings on international conference in recent trends in computational methods, communication and controls (ICON3C 2012), no. 5. Foundation of Computer Science (FCS).

  21. Hiremath, P. S., & Joshi, S. M. (2012). Energy efficient routing protocol with adaptive fuzzy threshold energy for manets. In International Journal of Computer Networks and Wireless Communications (IJCNWC), Vol. 2. ISSN: 2250-3501.

  22. Chettibi, S., & Chikhi, S. (2013). FEA-OLSR: An adaptive energy aware routing protocol for manets using zero-order sugeno fuzzy system. International Journal of Computer Science Issues (IJCSI), 10(2), 136–141.

    Google Scholar 

  23. Chettibi, S., & Chikhi, S. (2016). Dynamic fuzzy logic and reinforcement learning for adaptive energy efficient routing in mobile ad-hoc networks. Applied Soft Computing, 38, 321–328.

    Article  Google Scholar 

  24. Carvalho, T., Júnior, J. J., & Francês, R. (2016). A new cross-layer routing with energy awareness in hybrid mobile ad hoc networks: A fuzzy-based mechanism. Simulation Modelling Practice and Theory, 63, 1–22.

    Article  Google Scholar 

  25. Sarkar, S., & Datta, R. (2016). A secure and energy-efficient stochastic multipath routing for self-organized mobile ad hoc networks. Ad Hoc Networks, 37, 209–227.

    Article  Google Scholar 

  26. Das, S. K., Tripathi, S. (2016) Energy efficient routing protocol for MANET using vague set. In Proceedings of fifth international conference on soft computing for problem solving, pp. 235–245. Berlin: Springer.

  27. Zimmermann, H. J. (1991) Fuzzy set theory and its applications. Boston: Kluwer Academic Publishers.

  28. Das, S. K., & Tripathi, S. (2015). Energy efficient routing protocol for MANET based on vague set measurement technique. Procedia Computer Science, 58, 348–355.

  29. Das, S. K., Kumar, A., Das, B., & Burnwal, A. P. (2013). On soft computing techniques in various areas. Intenational Journal of Informational Technology and Computer Science, 3, 59–68.

    Google Scholar 

  30. Das, S. K., Tripathi, S., & Burnwal, A. P. (2014). Some relevance fields of soft computing methodology. International Journal of Research in Computer Applications and Robotics, 2, 1–6.

    Google Scholar 

  31. Bhawsar, Y., & Thakur, G. S. (2016). Performance evaluation of link prediction techniques based on fuzzy soft set and markov model. Fuzzy Information and Engineering, 8(1), 113–126.

    Article  MathSciNet  Google Scholar 

  32. Alcantud, J. C. R. (2016). A novel algorithm for fuzzy soft set based decision making from multiobserver input parameter data set. Information Fusion, 29, 142–148.

    Article  Google Scholar 

  33. Muthukumar, P., & Krishnan, G. S. S. (2016). A similarity measure of intuitionistic fuzzy soft sets and its application in medical diagnosis. Applied Soft Computing, 41, 148–156.

    Article  Google Scholar 

  34. Bartoletti, S., Dai, W., Conti, A., & Win, M. Z. (2015). A mathematical model for wideband ranging. IEEE Journal of Selected Topics in Signal Processing, 9(2), 216–228.

    Article  Google Scholar 

  35. Win, M. Z., Conti, A., Mazuelas, S., Shen, Y., Gifford, W. M., Dardari, D., et al. (2011). Network localization and navigation via cooperation. IEEE Communications Magazine, 49(5), 56–62.

    Article  Google Scholar 

  36. Tseng, Y.-C., Ni, S.-Y., Chen, Y.-S., & Sheu, J.-P. (2002). The broadcast storm problem in a mobile ad hoc network. Wireless Networks, 8(2–3), 153–167.

    Article  MATH  Google Scholar 

  37. Conti, A., Panchenko, D., Sidenko, S., & Tralli, V. (2009). Log-concavity property of the error probability with application to local bounds for wireless communications. IEEE Transactions on Information Theory, 55(6), 2766–2775.

    Article  MathSciNet  MATH  Google Scholar 

  38. WANG, Y., Mei, S. O. N. G., WEI, Y., WANG, Y., & WANG, X. (2014). Improved ant colony-based multi-constrained qos energy-saving routing and throughput optimization in wireless ad-hoc networks. The Journal of China Universities of Posts and Telecommunications, 21(1), 43–59.

    Article  Google Scholar 

Download references

Acknowledgments

The authors would like to thank the associate editor and the anonymous reviewers for their insightful comments and suggestions that helped us to improve the content of this paper.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Indian Institute of Technology (ISM), Dhanbad, Jharkhand, 826004, India

    Santosh Kumar Das & Sachin Tripathi

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  1. Santosh Kumar Das
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  2. Sachin Tripathi
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Correspondence to Santosh Kumar Das.

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Das, S.K., Tripathi, S. Intelligent energy-aware efficient routing for MANET. Wireless Netw 24, 1139–1159 (2018). https://doi.org/10.1007/s11276-016-1388-7

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