CLUSTER ROUTER BASED ON ECCENTRICITY
DOI:
https://doi.org/10.31489/2022No3/84-90Keywords:
cluster router, eccentricity, complex networks, box covering algorithms, Tsallis and Renyi dimensionsAbstract
In this paper, a cluster router based on eccentricity was worked out, related to the field of
telecommunications, especially, to the field of message transmission. Messages in this router are transmitted as
packets along the route specified in it between devices connected to the network. Each node in this network is
assigned a unique address, thanks to which routing can be accelerated. Each router forms a routing map, thanks
to the calculated eccentricity of nodes, with which the physical route of the packet is selected at the logical
address of the cluster. In addition, the routing map is stored in the register and non-volatile memory of the device
to prevent information loss. To analyze this cluster device, a fractal analysis of the UV-flower model network was
carried out and the information dimensions of Tsallis and Renyi were calculated.
References
Mazloomi N., Gholipour M., Zaretalab A., Efficient configuration for multi-objective QoS optimization in wireless sensor network. Ad Hoc Networks. 2022, 125 p.
Mehbodniya A., Bhatia S., Mashat A., et al. Proportional fairness based energy efficient routing in wireless sensor network. Computer Systems Science and Engineering. 2022. Vol. 41(3), pp. 1071-1082.
Nasri M., et al. Energy-efficient fuzzy logic-based cross-layer hierarchical routing protocol for wireless internet-of-things sensor networks. International Journal of Communication Systems. 2021.Vol.34(9), pp. 4808.
Khan M.K., et. al., Hierarchical routing protocols for wireless sensor networks: functional and performance analysis. Journal of Sensors. 2021. pp. 1-18.
Al-Zubi R. T., et al. Solution for intra/inter-cluster event-reporting problem in cluster-based protocols for wireless sensor networks. International Journal of Electrical and Computer Engineering. 2022. Vol. 12(1), pp. 868-879.
Daanoune I., Abdennaceur B., Ballouk A. A comprehensive survey on LEACH-based clustering routing protocols in wireless sensor networks. Ad Hoc Networks, 2021, Vol.114, pp.102409.
Blazevic L., Le Boudec J.Y., Giordano S. A location based routing method for mobile ad hoc networks. IEEE Transactions on Mobile Computing. 2005. Vol.4, pp. 97–110.
Sarkar A., Murugan T.S., Cluster head selection for energy efficient and delay-less routing in wireless sensor network. Journal of Wireless Networks. 2019. Vol. 25, No. 1, pp. 303– 320.
Soni V., Mallick D.K. Location-based routing protocols in wireless sensor networks: A survey. International Journal of Internet Protocol Technology. 2014. Vol. 8(4), pp. 200 – 213.
Huang R., Cui X., Pu H. Wireless sensor network clustering routing protocol based on energy and distance. Lecture Notes in Electrical Engineering. 2020. Vol. 675, pp. 1735 – 1745.
Song C., et al. How to calculate the fractal dimension of a complex network: the box covering algorithm. Journal of Statistical Mechanics: Theory and Experiment. 2007. Vol. 2007, No.03, pp. P03006.
Schneider C.M., et al. Box-covering algorithm for fractal dimension of complex networks. Physical Review E. 2012. Vol. 86, No.1, pp. 016707.
Song C., Havlin S., Makse H.A. Origins of fractality in the growth of complex networks. Nature physics. 2006. Vol.2, No.4, pp. 275 – 281.
Gallos L.K., Song C., Makse H.A. A review of fractality and self-similarity in complex networks. Physica A: Statistical Mechanics and its Applications. 2007. Vol. 386, No.2, pp. 686 – 691.
Wen T., Cheong K. H. The fractal dimension of complex networks: A review. Information Fusion. 2021. Vol. 73, pp.87 – 102.
Akhtanov S. et al. Centre including eccentricity algorithm for complex networks. Electronics Letters. 2022. Vol. 58, No. 7, pp. 283 – 285.
Kim J.S., et al. Fractality in complex networks: Critical and supercritical skeletons. Physical Review E. 2007, Vol.75. No.1, pp. 016110.
Long G.U.O., Cai X.U. The fractal dimensions of complex networks. Chinese Physics Letters. 2009, Vol.26. No.8, pp. 088901.
Zhang Q., et al. Tsallis information dimension of complex networks. Physica A: Statistical Mechanics and its Applications. 2015. Vol. 419, pp. 707 – 717.
Ramirez-Arellano A., Hernandez-Simon L.M., Bory-Reyes J. A box-covering Tsallis information dimension and non-extensive property of complex networks. Chaos, Solitons & Fractals. 2020. Vol.132, pp. 109590.
Bromiley P. A., Thacker N. A., Bouhova-Thacker E. Shannon entropy, Renyi entropy, and information. Statistics and Inf. Series (2004-004). 2004. Vol. 9, pp. 2 – 8.
Zyczkowski K. Renyi extrapolation of Shannon entropy. Open Systems & Information Dynamics. 2003. Vol.10, No.03, pp. 297 – 310.
Wei D., et al. A new information dimension of complex networks. Physics Letters A. 2014. Vol.378, No.16-17, pp.1091 – 1094.
Farmer J.D. Information dimension and the probabilistic structure of chaos. Zeitschrift für Naturforschung A. 1982. Vol. 37, No.11, pp. 1304 – 1326.
Geiger B.C., Koch T. On the information dimension of stochastic processes. IEEE transactions on information theory. 2019. Vol.65, No. 10, pp. 6496 – 6518.
Barth A., Baumann G., Nonnenmacher T. F. Measuring Renyi dimensions by a modified box algorithm. Journal of Physics A: Mathematical and General. 1992. Vol. 25, No.2, pp. 381.
Zhang Q. et al. Tsallis information dimension of complex networks. Physica A: Statistical Mechanics and its Applications. 2015. Vol. 419, pp. 707 – 717.
Duan S., Wen T., Jiang W. A new information dimension of complex network based on Rényi entropy. Physica A: Statistical Mechanics and its Applications. 2019. Vol.516, pp. 529 – 542.