Abstract
The world of networks inherently being complex, is a primitive based on graphs. It uses adjacency matrix for abstracting the topology of underlying expanse. This structure of graphs, single-handedly decides the entries of the adjacency matrix, and thus, the overall topology of the system being described. In this research, we open new horizons at the cost of conventions of traditional adjacency formulation. We argue that fresh perspectives need to be plugged into as adjacency entries for modeling, which need not necessarily be binary in nature, rather a real number between one and zero. This adjacency entry between one and zero can be interpreted as a probability of successful transmission in a communication network for example. Also, we roll out the viable idea that number of connections together with probability of successful transmission for a link combined, rules the crux of ranking nodes as decided by the HITS algorithm. Broader perspectives have been discovered, deviating from traditional approaches of capturing networks and an innovative computational insight has been presented to illustrate the relationship between reliability of links, connectivity and leadership in the community. In particular, results presented here are in agreement with work done in the area of trust, reputation and leadership in the sense that leaders should be able to attain highest amount of activity.
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This work is dedicated to fond memories of late Dr. Vashishtha Narayan Singh whose life and work has always inspired us to take on difficult research challenges.
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Pandey, H., Ranjan, P., Singh, A., Tripathy, M.R. (2020). Reliability and Connectivity Improve the Ranking Principle. In: Thampi, S., et al. Advances in Signal Processing and Intelligent Recognition Systems. SIRS 2019. Communications in Computer and Information Science, vol 1209. Springer, Singapore. https://doi.org/10.1007/978-981-15-4828-4_21
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DOI: https://doi.org/10.1007/978-981-15-4828-4_21
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