Abstract
For analysing networks like social media networks, wireless sensor networks, etc. in many applications, generating random connected graph is very important. As it is time consuming to generate the random connected graph consisting of large nodes it is necessary to generate it in minimum time. Characteristics like dependent edges and non-binomial degree distribution that are absent in many classical random graph models such as the Erdos-Renyi graph model can be captured by random graphs with a given degree range. The problem of random connected graph generation having a prescribed degree range has been addressed here. Random graphs are used to model wireless sensor networks (WSNs) or IoT comprising of sensor nodes with limited power resources. A fast and light-weight algorithm has been proposed in this paper to produce a random connected graph for a real-time multi-hop wireless sensor networks (WSNs). Results show that our method has better performance than other existing methods.
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Talapatra, S., Das, A. (2023). Random Connected Graph Generation for Wireless Sensor Networks. In: Pati, B., Panigrahi, C.R., Mohapatra, P., Li, KC. (eds) Proceedings of the 6th International Conference on Advance Computing and Intelligent Engineering. Lecture Notes in Networks and Systems, vol 428. Springer, Singapore. https://doi.org/10.1007/978-981-19-2225-1_14
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DOI: https://doi.org/10.1007/978-981-19-2225-1_14
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