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MCLMR: A Multicriteria Based Multipath Routing in the Mobile Ad Hoc Networks

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Abstract

In Mobile Ad hoc Networks (MANETs), nodes’ mobility, traffic congestion, and link quality estimation of the intermediate nodes are very crucial factors for establishing a reliable forwarding path between a source and destination node pairs. The unpredictable movement of nodes and random data traffic flow at a single node can cause congestion and network topology instability, which significantly lowers the performance of the ad hoc network. Indeed, the above-highlighted issues can be mitigated by implementing a more reliable mobility-centric, contention, and link quality-aware routing protocol for efficient data transmissions in a mobile network. This paper proposes a routing strategy called Mobility, Contention window, and Link quality sensitive multipath Routing (MCLMR) in MANETs, which considers the nodes mobility, contention window size, and link quality estimated value of the intermediate nodes in the optimal route selection. Also, Technique for Order of Preference by Similarity to Ideal Solution; a multicriteria decision-making technique, which provides weights according to node mobility, contention window size, and link quality estimated values, is also employed for the selection of intermediate nodes, whereas the Expected Number of Transmissions metric is used to minimize the effect of control message storm. The extensive simulations results prove that the proposed MCLMR routing scheme outperforms the conventional Multipath Optimized Link State Routing (MP-OLSR) and MP-OLSRv2 routing schemes in terms of network throughput, end-to-end delay, energy consumption, and packets loss ratio.

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References

  1. Shikh-Bahaei, V., Choi, Y. S., & Hong, D. (2018). Full-duplex and cognitive radio networking for the emerging 5G systems. Wireless Communications and Mobile Computing,2018, 1–2.

    Article  Google Scholar 

  2. Elijah, O., Rahman, T. A., Orikumhi, I., Leow, C. Y., & Hindia, M. N. (2018). An overview of internet of things (IoT) and data analytics in agriculture: Benefits and challenges. IEEE Internet of Things Journal,5(5), 3758–3773.

    Article  Google Scholar 

  3. Conti, M., & Giordano, S. (2014). Mobile ad hoc networking: Milestones, challenges, and new research directions. IEEE Communications Magazine,52, 85–96.

    Article  Google Scholar 

  4. Tilwari, V., Dimyati, K., Hindia, M., Fattouh, A., & Amiri, I. S. (2019). Mobility, residual energy, and link quality aware multipath routing in MANETs with Q-learning algorithm. Applied Sciences,9, 1582.

    Article  Google Scholar 

  5. Zhang, J., Dai, L., Li, X., Liu, Y., & Hanzo, L. (2018). On low-resolution ADCs in practical 5G millimeter-wave massive MIMO systems. IEEE Communications Magazine,56(7), 205–211.

    Article  Google Scholar 

  6. Qamar, F., Dimyati, K. B., Hindia, M. N., Noordin, K. A. B., & Al-Samman, A. M. (2017). A comprehensive review on coordinated multi-point operation for LTE-A. Computer Networks,123, 19–37.

    Article  Google Scholar 

  7. Tehrani, M. N., Uysal, M., & Yanikomeroglu, H. (2014). Device-to-device communication in 5G cellular networks: Challenges, solutions, and future directions. IEEE Communications Magazine,52, 86–92.

    Article  Google Scholar 

  8. Peng, M., Yan, S., Zhang, K., & Wang, C. (2016). Fog-computing-based radio access networks: Issues and challenges. IEEE Network,30, 46–53.

    Article  Google Scholar 

  9. Lu, Z., Qu, G., & Liu, Z. (2019). A survey on recent advances in vehicular network security, trust, and privacy. IEEE Transactions on Intelligent Transportation Systems,20, 760–776.

    Article  Google Scholar 

  10. Qamar, F., Hindia, M. H. D., Dimyati, K., Noordin, K. A., Majed, M. B., Abd Rahman, T., et al. (2019). Investigation of future 5G-IoT millimeter-wave network performance at 38 GHz for urban microcell outdoor environment. Electronics,8(5), 495.

    Article  Google Scholar 

  11. Qamar, F., Hindia, M. N., Abbas, T., Dimyati, K. B., & Amiri, I. S. (2019). Investigation of QoS performance evaluation over 5G network for indoor environment at millimeter wave bands. International Journal of Electronics and Telecommunications,65, 95–101.

    Google Scholar 

  12. Qamar, F., Dimyati, K., Hindia, M. N., Noordin, K. A., & Amiri, I. S. (2019). A stochastically geometrical poisson point process approach for the future 5G D2D enabled cooperative cellular network. IEEE Access,7, 60465–60485.

    Article  Google Scholar 

  13. Qamar, F., Hindia, M. N., Dimyati, K., Noordin, K. A., & Amiri, I. S. (2019). Interference management issues for the future 5G network: A review. Telecommunication Systems,71, 1–17.

    Article  Google Scholar 

  14. Rosati, S., Krużelecki, K., Heitz, G., Floreano, D., & Rimoldi, B. (2016). dynamic routing for flying ad hoc networks. IEEE Transactions on Vehicular Technology,65, 1690–1700.

    Article  Google Scholar 

  15. Maheswar, R., Jayarajan, P., Vigneswaran, D., Udaiyakumar, R., Theepak, C. G., & Amiri, I. S. (2018). VSMART—A simulation tool for performance analysis of wireless sensor node using queue threshold. In 2018 international conference on communication and signal processing (ICCSP) (pp. 0234–0237).

  16. Udaiyakumar, R., Joseph, S., Sundararajan, T. V. P., Vigneswaran, D., Maheswar, R., & Amiri, I. S. (2018). Self clock-gating scheme for low power basic logic element architecture. Wireless Personal Communications,102(4), 3477–3488.

    Article  Google Scholar 

  17. Udaiyakumar, R., Joseph, S., Sundararajan, T. V. P., Vigneswaran, D., Maheswar, R., & Amiri, I. S. (2018). Performance analysis in digital circuits for process corner variations, slew-rate and load capacitance. Wireless Personal Communications,103(1), 99–115.

    Article  Google Scholar 

  18. Hindia, M. N., Fadoul, M. M., Abdul Rahman, T., & Amiri, I. S. (2018). A stochastic geometry approach to full-duplex MIMO relay network. Wireless Communications and Mobile Computing,2018, 1–11.

    Article  Google Scholar 

  19. Gupta, L., Jain, R., & Vaszkun, G. (2016). Survey of important issues in UAV communication networks. IEEE Communications Surveys and Tutorials,18, 1123–1152.

    Article  Google Scholar 

  20. Sadiq, U., Kumar, M., Passarella, A., & Conti, M. (2015). Service composition in opportunistic networks: A load and mobility aware solution. IEEE Transactions on Computers,64, 2308–2322.

    Article  MathSciNet  Google Scholar 

  21. Ogundile, O. O., Balogun, M. B., Ijiga, O. E., & Falayi, E. O. (2019). Energy-balanced and energy-efficient clustering routing protocol for wireless sensor networks. IET Communications,13(10), 1449–1457.

    Article  Google Scholar 

  22. Toutouh, J., Garcia-Nieto, J., & Alba, E. (2012). Intelligent OLSR routing protocol optimization for VANETs. IEEE Transactions on Vehicular Technology,61, 1884–1894.

    Article  Google Scholar 

  23. Tran, D. A., & Raghavendra, H. (2006). Congestion adaptive routing in mobile ad hoc networks. IEEE Transactions on Parallel and Distributed Systems,17, 1294–1305.

    Article  Google Scholar 

  24. Rendong, B., & Singhal, M. (2006). DOA: DSR over AODV routing for mobile ad hoc networks. IEEE Transactions on Mobile Computing,5, 1403–1416.

    Article  Google Scholar 

  25. Bai, F., Sadagopan, N., Krishnamachari, B., & Helmy, A. (2004). Modeling path duration distributions in MANETs and their impact on reactive routing protocols. IEEE Journal on Selected Areas in Communications,22, 1357–1373.

    Article  Google Scholar 

  26. Saleet, H., Langar, R., Naik, K., Boutaba, R., Nayak, A., & Goel, N. (2011). Intersection-based geographical routing protocol for VANETs: A proposal and analysis. IEEE Transactions on Vehicular Technology,60, 4560–4574.

    Article  Google Scholar 

  27. Li, M., Zhang, L., Li, V. O., Shan, X., & Ren, Y. (2005). An energy-aware multipath routing protocol for mobile ad hoc networks. ACM Sigcomm Asia,5, 10–12.

    Google Scholar 

  28. Rajeswari, K., & Neduncheliyan, S. (2017). Genetic algorithm based fault tolerant clustering in wireless sensor network. IET Communications,11, 1927–1932.

    Article  Google Scholar 

  29. Villasenor-Gonzalez, L., Ge, Y., & Lament, L. (2005). HOLSR: A hierarchical proactive routing mechanism for mobile ad hoc networks. IEEE Communications Magazine,43, 118–125.

    Article  Google Scholar 

  30. Wu, Z.-Y., & Song, H.-T. (2008). Ant-based energy-aware disjoint multipath routing algorithm for MANETs. The Computer Journal,53, 166–176.

    Article  Google Scholar 

  31. Mnaouer, A. B., Chen, L., Foh, C. H., & Tantra, J. W. (2007). OPHMR: an optimized polymorphic hybrid multicast routing protocol for MANET. IEEE Transactions on Mobile Computing,6, 551–562.

    Article  Google Scholar 

  32. Kacem, I., Sait, B., Mekhilef, S., & Sabeur, N. (2018). A new routing approach for mobile ad hoc systems based on fuzzy petri nets and ant system. IEEE Access,6, 65705–65720.

    Article  Google Scholar 

  33. Taha, A., Alsaqour, R., Uddin, M., Abdelhaq, M., & Saba, T. (2017). Energy efficient multipath routing protocol for mobile ad-hoc network using the fitness function. IEEE access,5, 10369–10381.

    Article  Google Scholar 

  34. Le, P. H., & Pujolle, G. (2011, June). A link-disjoint interference-aware multi-path routing protocol for mobile ad hoc network. In International conference on digital information and communication technology and its applications (pp. 649–661). Springer, Berlin.

  35. Wang, Z., Chen, Y., & Li, C. (2014). PSR: A lightweight proactive source routing protocol for mobile ad hoc networks. IEEE Transactions on Vehicular Technology,63, 859–868.

    Article  Google Scholar 

  36. Joshi, R. D., & Rege, P. P. (2012). Implementation and analytical modelling of modified optimised link state routing protocol for network lifetime improvement. IET Communications,6, 1270–1277.

    Article  Google Scholar 

  37. Yi, J., Adnane, A., David, S., & Parrein, B. (2011). Multipath optimized link state routing for mobile ad hoc networks. Ad Hoc Networks,9, 28–47.

    Article  Google Scholar 

  38. Yi, J. & Parrein, B. (2017). Multipath extension for the optimized link state routing protocol version 2 (OLSRv2), hal-01705335 2070–1721, 2017.

  39. Zhang, Y., Cao, Y., Wen, Y., Liang, L., & Zou, F. (2018). Optimization of information interaction protocols in cooperative vehicle-infrastructure systems. Chinese Journal of Electronics,27, 439–444.

    Article  Google Scholar 

  40. De Couto, D. S. J., Aguayo, D., Bicket, J., & Morris, R. (2005). A high-throughput path metric for multi-hop wireless routing. Wireless Networks,11, 419–434.

    Article  Google Scholar 

  41. Tran, A. T., Mai, D. D., & Kim, M. K. (2015). Link quality estimation in static wireless networks with high traffic load. Journal of Communications and Networks,17, 370–383.

    Article  Google Scholar 

  42. Wang, T.-C., & Lee, H.-D. (2009). Developing a fuzzy TOPSIS approach based on subjective weights and objective weights. Expert Systems with Applications,36, 8980–8985.

    Article  Google Scholar 

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Correspondence to Iraj Sadegh Amiri.

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Tilwari, V., Maheswar, R., Jayarajan, P. et al. MCLMR: A Multicriteria Based Multipath Routing in the Mobile Ad Hoc Networks. Wireless Pers Commun 112, 2461–2483 (2020). https://doi.org/10.1007/s11277-020-07159-8

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