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Adaptive mobility-aware and reliable routing protocols for healthcare vehicular network

  • Received: 28 December 2021 Revised: 01 April 2022 Accepted: 06 April 2022 Published: 16 May 2022
  • Healthcare vehicles such as ambulances are the key drivers for digital and pervasive remote care for elderly patients. Thus, Healthcare Vehicular Ad Hoc Network (H-VANET) plays a vital role to empower the digital and Intelligent Transportation System (ITS) for the smart medical world. Quality of Service (QoS) performance of vehicular communication can be improved through the development of a robust routing protocol having enhanced reliability and scalability. One of the most important issues in vehicular technology is allowing drivers to make trustworthy decisions, therefore building an efficient routing protocol that maintains an appropriate level of Quality of Service is a difficult task. Restricted mobility, high vehicle speeds, and continually changing topologies characterize the vehicular network environment. This paper contributes in four ways. First, it introduces adaptive, mobility-aware, and reliable routing protocols. The optimization of two routing protocols which are based on changing nature topologies of the network used for vehicular networks has been performed, amongst them, Optimized Link State Routing (Proactive) and Ad-hoc on Demand Distance Vector (Reactive) are considered for Packet Delivery Ratio (PDR) and throughput. Furthermore, Packet Loss Ratio (PLR), and end-to-end (E2E) delay parameters have also been calculated. Second, a healthcare vehicle system architecture for elderly patients is proposed. Third, a Platoon-based System model for routing protocols in VANET is proposed. Fourth, a dynamic channel model has been proposed for the vehicle to vehicle communication using IEEE8011.p. To optimize the QoS, the experimental setup is conducted in a discrete Network Simulator (NS-3) environment. The results reveal that the AODV routing protocol gives better performance for PDR as well as for PLR and the communication link established is also reliable for throughput. Where OLSR produces a large average delay. The adoptive mobility-aware routing protocols are potential candidates for providing Intelligent Transportation Systems with acceptable mobility, high reliability, high PDR, low PLR, and low E2E delay.

    Citation: Nawaz Ali Zardari, Razali Ngah, Omar Hayat, Ali Hassan Sodhro. Adaptive mobility-aware and reliable routing protocols for healthcare vehicular network[J]. Mathematical Biosciences and Engineering, 2022, 19(7): 7156-7177. doi: 10.3934/mbe.2022338

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  • Healthcare vehicles such as ambulances are the key drivers for digital and pervasive remote care for elderly patients. Thus, Healthcare Vehicular Ad Hoc Network (H-VANET) plays a vital role to empower the digital and Intelligent Transportation System (ITS) for the smart medical world. Quality of Service (QoS) performance of vehicular communication can be improved through the development of a robust routing protocol having enhanced reliability and scalability. One of the most important issues in vehicular technology is allowing drivers to make trustworthy decisions, therefore building an efficient routing protocol that maintains an appropriate level of Quality of Service is a difficult task. Restricted mobility, high vehicle speeds, and continually changing topologies characterize the vehicular network environment. This paper contributes in four ways. First, it introduces adaptive, mobility-aware, and reliable routing protocols. The optimization of two routing protocols which are based on changing nature topologies of the network used for vehicular networks has been performed, amongst them, Optimized Link State Routing (Proactive) and Ad-hoc on Demand Distance Vector (Reactive) are considered for Packet Delivery Ratio (PDR) and throughput. Furthermore, Packet Loss Ratio (PLR), and end-to-end (E2E) delay parameters have also been calculated. Second, a healthcare vehicle system architecture for elderly patients is proposed. Third, a Platoon-based System model for routing protocols in VANET is proposed. Fourth, a dynamic channel model has been proposed for the vehicle to vehicle communication using IEEE8011.p. To optimize the QoS, the experimental setup is conducted in a discrete Network Simulator (NS-3) environment. The results reveal that the AODV routing protocol gives better performance for PDR as well as for PLR and the communication link established is also reliable for throughput. Where OLSR produces a large average delay. The adoptive mobility-aware routing protocols are potential candidates for providing Intelligent Transportation Systems with acceptable mobility, high reliability, high PDR, low PLR, and low E2E delay.



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    [1] A. H. Sodhro, M. S. Obaidat, Q. H. Abbasi, P. Pace, S. Pirbhulal, A. Yasar, et al., Quality of service optimization in an IoT-driven intelligent transportation system, IEEE Wireless Commun., 26 (2019), 10-17. https://doi.org/10.1109/mwc.001.1900085 doi: 10.1109/mwc.001.1900085
    [2] A. H. Sodhro, G. H. Sodhro, M. Guizani, S. Pirbhulal, A. Boukerche, AI-enabled reliable channel modeling architecture for fog computing vehicular networks, IEEE Wireless Commun., 27 (2020), 14-21. https://doi.org/10.1109/mwc.001.1900311 doi: 10.1109/mwc.001.1900311
    [3] A. R. Kaci, Named data networking architecture for internet of vehicles in the era of 5G, Ann. Telecommun., 76 (2021), 717-729. https://doi.org/10.1007/s12243-021-00866-8 doi: 10.1007/s12243-021-00866-8
    [4] P. Fabian, A. Rachedi, C. Guéguen, Selection of relays based on the classification of mobility-type and localized network metrics in the Internet of Vehicles, Transact. Emerg. Telecommun. Technol., 32 (2021). https://doi.org/10.1002/ett.4246
    [5] T. Abar, A. Rachedi, A. Letaifa, P. Fabian, S. Asmi, FellowMe cache: Fog Computing approach to enhance (QoE) in internet of vehicles, Future Gener. Computer Syst., 113 (2020), 170-182. https://doi.org/10.1016/j.future.2020.06.026 doi: 10.1016/j.future.2020.06.026
    [6] R. V. Hoek, J. Ploeg, H. Nijmeijer, Cooperative driving of automated vehicles using B-splines for trajectory planning, IEEE Transact. Intelligent Vehicles, 6 (2021), 594-604. https://doi.org/10.1109/tiv.2021.3072679 doi: 10.1109/tiv.2021.3072679
    [7] Z. Zhang, X. T. Yang, Analysis of highway performance under mixed connected and regular vehicle environment, J. Intell. Connected Vehicles, (2021). https://doi.org/10.1108/jicv-10-2020-0011
    [8] D. Jia, K. Lu, J. Wang, X. Zhang, X. S. Hen, A survey on platoon-based vehicular cyber-physical systems, IEEE Commun. Surveys Tutor., 18 (2015), 263-284. https://doi.org/10.1109/comst.2015.2410831 doi: 10.1109/comst.2015.2410831
    [9] A. Lakhan, M. A. Dootio, T. M. Groenli, A. H. Sodhro, M. S. Khokhar, Multi-layer latency aware workload assignment of E-transport IoT applications in mobile sensors cloudlet cloud networks, Electronics, 10 (2021), 1719. https://doi.org/10.3390/electronics10141719 doi: 10.3390/electronics10141719
    [10] A. H Sodhro, Y. Li, M. A Shah, Energy-efficient adaptive transmission power control for wireless body area networks, IET Commun., 10 (2016), 81-90. https://doi.org/10.1049/iet-com.2015.0368 doi: 10.1049/iet-com.2015.0368
    [11] N. Haddadou, A. Rachedi, Y. G. Doudane, A job market signaling scheme for incentive and trust management in vehicular Ad Hoc networks, IEEE Transact. Vehicular Technol., 64 (2014), 3657-3674. https://doi.org/10.1109/tvt.2014.2360883 doi: 10.1109/tvt.2014.2360883
    [12] C. P. S. Cañar, J. J. T. Yépez, H. M. R. López, Performance of reactive routing protocols DSR and AODV in vehicular Ad-Hoc networks based on Quality of Service (QoS) metrics, Int. J. Eng. Adv. Technol., 9 (2020), 2033-2039. https://doi.org/10.35940/ijeat.c6608.049420 doi: 10.35940/ijeat.c6608.049420
    [13] Y. Lin, X. Jin, J. Chen, A. H. Sodhro, Z. Pan, An analytic computation-driven algorithm for Decentralized Multicore Systems, Future Gener. Computer Syst., 96 (2019), 101-110. https://doi.org/10.1016/j.future.2019.01.031 doi: 10.1016/j.future.2019.01.031
    [14] S. Mohapatra, P. Kanungo, Performance analysis of AODV, DSR, OLSR and DSDV routing protocols using NS2 simulator, Proced. Eng., 30 (2012), 69-76. https://doi.org/10.1016/j.proeng.2012.01.835 doi: 10.1016/j.proeng.2012.01.835
    [15] S. A. Saleh, M. F. Zuhairi, H. Dao, A comparative performance analysis of MANET routing protocols in various propagation loss models using NS3 simulator, J. Commun., 15 (2020), 537. https://doi.10.12720/jcm doi: 10.12720/jcm
    [16] T. Mekki, I. Jabri, A. Rachedi, M. B. Jemaa, Proactive and hybrid wireless network access strategy for vehicle cloud networks, an evolutionary game approach, 13th International Wireless Communications and Mobile Computing Conference (IWCMC), (2017). https://doi.org/10.1109/iwcmc.2017.7986440
    [17] K. L. Arega, G. Raga, R. Bareto, Survey on performance analysis of AODV, DSR and DSDV in MANET, Computer Eng. Intell. Syst., 11 (2020), 23-32. https://doi.org/10.7176/ceis/11-3-03 doi: 10.7176/ceis/11-3-03
    [18] A. Kurniawan, P. Kristalina, M. Z. S.Hadi, Performance analysis of routing protocols AODV, OLSR and DSDV on MANET using NS3, International Electronics Symposium (IES), (2020), 199-206. https://doi:10.1109/IES50839.2020.9231690
    [19] M. I. Talukdar, M. S. Hossen, Reactive and proactive routing strategies in mobile Ad Hoc network, In Opportunistic Networks, CRC Press, 2021, 37-54. https://doi.org/10.1201/9781003132585-3
    [20] T. Kaur, A. K. Verma, Simulation and analysis of AODV routing protocol in VANETs, Int. J. Soft Comput. Eng., 2 (2012), 2231-2307. https://doi.org/10.1.1.206.5788
    [21] H. F. Mahdi, M. S. Abood, M. M. Hamdi, Performance evaluation for vehicular ad-hoc networks based routing protocols, Bull. Electr. Eng. Inform., 10 (2021), 1080-1091. https://doi.org/10.11591/eei.v10i2.2943 doi: 10.11591/eei.v10i2.2943
    [22] P. K. Shrivastava, L. K. Vishwamitra, Comparative analysis of proactive and reactive routing protocols in VANET environment, Measurement Sensors, 16 (2021). https://doi.org/10.1016/j.measen.2021.100051
    [23] P. T. K. Bai, M. Sundararajan, Performance efficiency of OLSR and AODV protocols in MANETs, Indian J Sci. Technol., 8 (2015). https://doi.org/10.17485/ijst/2015/v8i14/73048
    [24] G. Z. Santoso, M. Kang, Performance analysis of AODV, DSDV and OLSR in a VANETs safety application scenario, 2012 14th International Conference on Advanced Communication Technology (ICACT), (2012).
    [25] N. Zahid, A. H. Sodhro, U. R. Kamboh, A. Alkhayyat, L. Wang, AI-driven adaptive reliable and sustainable approach for internet of things enabled healthcare system, Math. Biosci. Eng., 19 (2022), 3953-3971. https://doi.org/10.3934/mbe.2022182 doi: 10.3934/mbe.2022182
    [26] A. H. Sodhro, S. Pirbhulal, Z. Luo, K. Muhammad, Towards 6G architecture for energy efficient communication in IoT-enabled smart automation systems, IEEE Int. Things J., 8 (2021), 5141-5146. https://doi.org/10.1109/jiot.2020.3024715 doi: 10.1109/jiot.2020.3024715
    [27] Z. Zhang, K. Xu, C. Gan, The vehicle-to-vehicle link duration scheme using platoon-optimized clustering algorithm, IEEE Access, 7 (2019), 78584-78596. https://doi.org/10.1109/access.2019.2922981 doi: 10.1109/access.2019.2922981
    [28] S. Malik, P. K. Sahu, A comparative study on routing protocols for VANETs, Heliyon, 5 (2019), e02340. https://doi.org/10.1016/j.heliyon.2019.e02340 doi: 10.1016/j.heliyon.2019.e02340
    [29] H. Nurwarsito, A. R. Aziz, Implementation of the Friis free space propagation model in the Dynamic Source Routing (DSR) routing protocol in the Vehicular Ad-hoc Network (VANET) with variations of road models, J. Phys. Conference Series, 1962 (2021). https://doi.org/10.1088/1742-6596/1962/1/012063
    [30] L. Cheng, B. E. Henty, D. D. Stancil, F. Bai, P. Mudalige, Mobile vehicle-to-vehicle narrow-band channel measurement and characterization of the 5.9 GHz Dedicated Short Range Communication (DSRC) frequency band, IEEE J. Selected Areas Commun., 25 (2007), 1501-1516. https://doi.org/10.1109/jsac.2007.071002 doi: 10.1109/jsac.2007.071002
    [31] A. Ueda, T. Fujii, Packet delivery ratio prediction for V2V based on radio environment map considering hidden terminal problem, Int. J. Intell. Transport. Syst. Res., 19 (2021), 254-263. https://doi.org/10.1007/s13177-020-00239-w doi: 10.1007/s13177-020-00239-w
    [32] A. H. Sodhro, N. Zahid, AI-enabled framework for Fog computing driven E-healthcare applications, Sensors, 21 (2021), 8039. https://doi.org/10.3390/s21238039 doi: 10.3390/s21238039
    [33] S. Ullah, G. Abbas, Z. H. Abbas, M. Waqas, M. Ahmed, RBO-EM: Reduced broadcast overhead scheme for emergency message dissemination in VANETs, IEEE Access, 8 (2020), 175205-175219. https://doi.org/10.1109/access.2020.3025212 doi: 10.1109/access.2020.3025212
    [34] R. Mehra, R. S. Bali, P. Kaur, Efficient clustering based OLSR routing protocol for VANET, In symposium on colossal data analysis and networking (CDAN), IEEE, 2016. https://doi.org/10.1109/CDAN.2016.7570915
    [35] A. Lakhan, M. A. Dootio, A. H. Sodhro, S. Pirbhulal, T. M. Groenli, M. S. Khokhar, et al., Cost-efficient service selection and execution and blockchain-enabled serverless network for internet of medical things, Math. Biosci. Eng., 18 (2021), 7344-7362. https://doi.org/10.3934/mbe.2021363 doi: 10.3934/mbe.2021363
    [36] A. H. Sodhro, Z. Luo, G. H. Sodhro, M. Muzamal, J. J. P. C. Rodrigues, V. C. Albuquerque, Artificial Intelligence based QoS optimization for multimedia communication in IoV systems, Future Gener. Computer Syst., 95 (2019), 667-680. https://doi.org/10.1016/j.future.2018.12.008 doi: 10.1016/j.future.2018.12.008
    [37] L. Liu, M. Zhao, M. Yu, M. A. Jan, D. Lan, A. Taherkordi, Mobility-aware multi-hop task offloading for autonomous driving in vehicular edge computing and networks, IEEE Transact. Intell. Transport. Syst., (2022), 1-14. https://doi.org/10.1109/tits.2022.3142566
    [38] S. Ghosh, A. Mukherjee, S. K. Ghosh, R. Buyya, Mobi-IoST: Mobility-aware Cloud-Fog-Edge-IoT collaborative framework for time-critical applications, IEEE Transact. Network Sci. Eng., 7 (2019), 2271-2285. https://doi.org/10.1109/tnse.2019.2941754 doi: 10.1109/tnse.2019.2941754
    [39] T. S. Gomides, R. E. De Grande, A. M. de Souza, F. S. H. Souza, L. A. Villas, D. L. Guidonia, An adaptive and distributed traffic management system using vehicular Ad-hoc networks, Computer Commun., 159 (2020), 317-330. https://doi.org/10.1016/j.comcom.2020.05.027 doi: 10.1016/j.comcom.2020.05.027
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