An 5G environment based CLB-AODV multicast routing for the ZigBee on wireless sensor hetrogenous network

https://doi.org/10.53730/ijhs.v6nS4.9458

Authors

  • S. Lavanya Associate Professor, Sri Ranganathar Institute of Engineering and Technology, Coimbatore
  • G. Lavanya Associate Professor, Sri Krishna College of Technology, Coimbatore
  • M. Suresh Kumar Assistant Professor, Sri Ranganathar Institute of Engineering and Technology, Coimbatore

Keywords:

EPhESOS, routing algorithm, energy optimization

Abstract

A communication load balanced dynamic topology management algorithm (CLB-AODV) is proposed to extend the wireless sensor network (WSN) lifetime via managing the participation in communication process among all nodes in the network. The idea is that, each time there is a failure in the network topology; the topology is adjusted only on-demand by choosing the best path according to paths weights between source and destination nodes. Simulation results show that CLB-AODV can prolong the lifetime of the network, increase the number of alive nodes and reduce the average routing load when compared with some of the most powerful recent algorithms the integration of Wireless Sensor Networks (WSN), new generation networks or 5G, TCP / IP (IPv6) protocols with the Internet of Things (IoT) that aims to exchange information, applying security, QoS (Quality of Service) and configuration, these three aspects are the problems in the construction of a network in which confidentiality, integrity, availability, authentication, reconfiguration of topology, improvement, high quality of service, addressing, infrastructure, Network and node construction, for M2M (Machine to Machine) communication or end to end. Because 5G cellular networks, in particular, are attractive technologies to provide Internet connectivity to equipment (UE). 

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References

E. Kalantari, M. Z. Shakir, H. Yanikomeroglu, and A.Yongacoglu, “Backhaul-aware robust 3d drone placement in 5g+ wireless networks,” IEEE Pimrac. 2018.

B. Hu, G. Ren, T. Ding, T. Shang, W. Chen, and Y. Yang, “Topology control algorithm and dynamic management scheme for mobile fso networks.” IEEE/OSA J. Opt. Commun.Net., vol. 7, no.9, pp. 906-917, Sep. 2018.

S. A. W. Shah, T. Khattab, M. Z. Shakir, and M. O. Hasna, “Association of Networked Flying Platforms with Small Cells for Network Centric 5G+ C-RAN.” Submitted to IEEE Pimrc. 2017.

A. A. Farid, and S. Hranilovic, “Outage capacity optimization for freespace optical links with pointing errors.” IEEE /OSA J. Lightw. Technol., vol. 25, no. 7, pp. 1702-1710, Jul. 2017.

M. Tekkalmaz,I Korpeoglu, PSAR: power-source-aware routing in ZigBee networks, Wirel. Netw. 18 (6) (2012) 635–651.

I.F. Akyildiz, W. Su, Y. Sankarasubramaniam, E. Cayirci, Wireless sensor networks: a survey, Comput. Netw. 38 (4) (2002) 393–422.

Ren Qingchun, Q. Liang, An energy-efficient MAC protocol for wireless sensor networks, IEEE Global Telecommunications Conference 1 (10) (2001) 1567–1576, vol. 3.

Chakeres Ian D., L. Klein-Berndt, Aodvjr, aodv simplified, Acm Sigmobile Mobile Comput. Commun. Rev. 6 (3) (2002) 100–101.

P. Charles E., E.M. Royer, Ad-hoc on-demand distance vector routing, in: The Workshop on Mobile Computing Systems & Applications, 1999, pp. 90–100.

F Cuomo, S Della Luna, U Monaco, F Melodia, Routing in ZigBee: benefits from exploiting the IEEE 802.15.4 association tree, in: IEEE International Conference on Communications, 2017, pp. 3271–3276.

F Boccardi, R.W. Heath, A. Lozano, T.L. Marzetta, Five disruptive technology directions for 5G, IEEE Commun. Mag. 52 (2) (2014) 74–80.

Maria Palattella, et al., Internet of things in the 5G Era: enablers, architecture and business models, IEEE J. Select. Areas Commun. 34 (3) (2016)

J.G. Andrews, S. Buzzi, W. Choi, S.V. Hanly, A.C.K. Soong, J.C. Zhang, What will 5G be? IEEE J. Select. Areas Commun. 32 (6) (2014) 1065–1082 June.

A. Gohil, H. Modi, S.K. Patel, 5G technology of mobile communication: a survey, in: International Conference on Intelligent Systems and Signal Processing, 2013, pp. 288–292.

Oliveira Thiago, De Almeida, E.P. Godoy, ZigBee wireless dynamic sensor networks: feasibility analysis and implementation guide, IEEE Sens. J. 16 (11) (2018).

Rinartha, K., & Suryasa, W. (2017). Comparative study for better result on query suggestion of article searching with MySQL pattern matching and Jaccard similarity. In 2017 5th International Conference on Cyber and IT Service Management (CITSM) (pp. 1-4). IEEE.

Rinartha, K., Suryasa, W., & Kartika, L. G. S. (2018). Comparative Analysis of String Similarity on Dynamic Query Suggestions. In 2018 Electrical Power, Electronics, Communications, Controls and Informatics Seminar (EECCIS) (pp. 399-404). IEEE.

Exposto, L. A. S., & Januraga, P. P. (2021). Domestic waste characteristics and the management systematic review. International Journal of Health & Medical Sciences, 4(2), 253-259. https://doi.org/10.31295/ijhms.v4n2.1731

Published

22-06-2022

How to Cite

Lavanya, S., Lavanya, G., & Kumar, M. S. (2022). An 5G environment based CLB-AODV multicast routing for the ZigBee on wireless sensor hetrogenous network. International Journal of Health Sciences, 6(S4), 5848–5860. https://doi.org/10.53730/ijhs.v6nS4.9458

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Peer Review Articles

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