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Local Weak Convergence Based Analysis of a New Graph Model

Moharrami, M and Subramanian, V and Liu, M and Sundaresan, R (2019) Local Weak Convergence Based Analysis of a New Graph Model. In: 56th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2018, 2 - 5 October, 2018, Allerton Park and Retreat Center Monticello, United States, pp. 502-503.

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Official URL: http://dx.doi.org/10.1109/ALLERTON.2018.8635966

Abstract

Different random graph models have been proposed as an attempt to model individuals' behavior. Each of these models proposes a unique way to construct a random graph that covers some properties of the real-world networks. In a recent work4], the proposed model tries to capture the self-optimizing behavior of the individuals in which the links are made based on the cost/ benefit of the connection. In this paper, we analyze the asymptotics of this graph model. We prove the model locally weakly converges 1] to a rooted tree associated with a branching process which we named Erlang Weighted Tree( EWT) and analyze the main properties of the EWT.

Item Type: Conference Proceedings
Additional Information: Copyright belongs to Institute of Electrical and Electronics Engineers Inc.
Keywords: Convergence;Graph theory;Random processes,Trees(mathematics)
Department/Centre: Division of Electrical Sciences > Electrical Communication Engineering
Depositing User: Id for Latest eprints
Date Deposited: 21 Apr 2019 08:07
Last Modified: 21 Apr 2019 08:07
URI: http://eprints.iisc.ac.in/id/eprint/62520

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