Investigation and performance optimization of mesh networking in Zigbee

Essa Ibrahim Essa, Mshari A. Asker, Fidan T. Sedeeq


The aim of this research paper is to perform a detailed investigation and performance optimization of mesh networking in Zigbee. ZigBee applications are open and global wireless technology that are based on IEEE 802.15.4 standard, it is used for sense and control in many fields like, military, commercial, industrial and medical applications. Extending ZigBee lifetime is a high demand in many ZigBee networks industry and applications, and since the lifetime of ZigBee nodes depends mainly on batteries for their power, the desire for developing a scheme or methodology that support power management and saving battery lifetime is of a great requirement. In this research work, a power sensitive routing Algorithm is proposed Power Sensitive Ad hoc On-Demand (PS-AODV) to develop protocol scheme and methodology of existing on-demand routing protocols, by introducing an algorithm that manages ZigBee operations and construct the route from trusted active nodes. Furthermore, many aspects of routing protocol in ZigBee mesh networks have been researched to concentrate on route discovery, route maintenance, neighbouring table, and shortest paths. PS-AODV routing algorithm is used in two different ZigBee mesh networks, with two different coordinator locations, one used at the centre and the other one at the corner of the networks. The extracted results conclude a better network operation for the coordinator located at the centre with an increase in the network lifetime around 20% percentage, and saved about 32.7% of delay time compare to AODV.



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E. Di Pascale, I. Macaluso, A. Nag, M. Kelly, and L. Doyle, “The Network As a Computer: A Framework for Distributed Computing over IoT Mesh Networks,” IEEE Internet Things J., vol. 5, no. 3, pp. 2107–2119, 2018, doi: 10.1109/JIOT.2018.2823978.

. S. Sharma, S. Kumar, and B. Singh, “Routing in Wireless Mesh Networks: Three New Nature Inspired Approaches,” Wirel. Pers. Commun., vol. 83, no. 4, pp. 3157–3179, 2015, doi: 10.1007/s11277-015-2588-7

. Y. Tsado, K. A. A. Gamage, B. Adebisi, D. Lund, K. M. Rabie, and A. Ikpehai, “Improving the reliability of optimised link state routing in a smart grid neighbour area network based wireless mesh network using multiple metrics,” Energies, vol. 10, no. 3, 2017, doi: 10.3390/en10030287.

. Y. Chai and X. J. Zeng, “Regional condition-aware hybrid routing protocol for hybrid wireless mesh network,” Comput. Networks, vol. 148, no. October 2019, pp. 120–128, 2019, doi: 10.1016/j.comnet.2018.11.008.

. Y. Chai, W. Shi, T. Shi, and X. Yang, “An efficient cooperative hybrid routing protocol for hybrid wireless mesh networks,” Wirel. Networks, vol. 23, no. 5, pp. 1387–1399, 2017, doi: 10.1007/s11276-016-1229-8.

. J. L. Chen, Y. W. Ma, C. P. Lai, C. C. Hu, and Y. M. Huang, “Multi-hop routing mechanism for reliable sensor computing,” Sensors, vol. 9, no. 12, pp. 10117–10135, 2009, doi: 10.3390/s91210117.

. I. Al Barazanchi, H. R. Abdulshaheed, S. A. Shawkat, and S. R. Binti, “Identification key scheme to enhance network performance in wireless body area network,” Period. Eng. Nat. Sci., vol. 7, no. 2, pp. 895–906, 2019.

. J. H. Park, “All-Terminal Reliability Analysis of Wireless Networks of Redundant Radio Modules,” IEEE Internet Things J., vol. 3, no. 2, pp. 219–230, 2016, doi: 10.1109/JIOT.2015.2496259.

. L. Rosyidi, H. P. Pradityo, D. Gunawan, R. Harwahyu, and R. F. Sari, “Dual hop multicast ping method for node failure detection in ZigBee loop network,” 2014 Int. Conf. Inf. Technol. Syst. Innov. ICITSI 2014 - Proc., no. July 2017, pp. 76–80, 2014, doi: 10.1109/ICITSI.2014.7048241.

. A. Yaqini and F. Popalyar, “An artificial neural network based fault detection and diagnosis for wireless mesh networks,” IFIP Wirel. Days, vol. 2018-April, pp. 107–109, 2018, doi: 10.1109/WD.2018.8361704.

. Z. Wang et al., “Failure prediction using machine learning and time series in optical network,” Opt. Express, vol. 25, no. 16, p. 18553, 2017, doi: 10.1364/oe.25.018553.

. T. Hayajna and M. Kadoch, “Hello-based link failure detection analysis in wireless mesh networks,” Proc. - 2016 IEEE 4th Int. Conf. Futur. Internet Things Cloud, FiCloud 2016, pp. 201–206, 2016, doi: 10.1109/FiCloud.2016.36.

.T. Lindhorst, G. Lukas, E. Nett, and M. Mock, “Data-mining-based link failure detection for wireless mesh networks,” Proc. IEEE Symp. Reliab. Distrib. Syst., pp. 353–357, 2010, doi: 10.1109/SRDS.2010.51.

N. Sota and H. Higaki, “Cooperative watchdog for malicious failure notification in wireless ad-hoc networks,” 2016 8th IFIP Int. Conf. New Technol. Mobil. Secur. NTMS 2016, pp. 3–6, 2016, doi: 10.1109/NTMS.2016.7792440.

. M. Tanha, D. Sajjadi, and J. Pan, “Demystifying Failure Recovery for Software-Defined Wireless Mesh Networks,” 2018 4th IEEE Conf. Netw. Softwarization Work. NetSoft 2018, pp. 476–481, 2018, doi: 10.1109/NETSOFT.2018.8460087.



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Copyright (c) 2020 Essa Ibrahim Essa, Mshari A. Asker, Fidan T. Sedeeq

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ISSN: 2303-4521

Digital Object Identifier DOI: 10.21533/pen

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License