Onur Ugurlu

Dr. Onur Ugurlu


Research Focus & Metrics

Academic Career Length

15Years (2012-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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14 June 2022 in Journal of Computational Science
Verified
Journal Article
Closed access
OUOnur Ugurlu
Onur Ugurlu

1 January 2013 in Journal of Psychiatric Research
Verified
Journal Article
Closed access
SISerhan Isıklı
Serhan Isıklı
OUOnur Ugurlu
Onur Ugurlu
EDEce Durmusoglu
Ece Durmusoglu
GKGozde Kizilates
Gozde Kizilates
OKOmer Kitis
Omer Kitis
AGAli Saffet Gonul
Ali Saffet Gonul

1 April 2018 in Comprehensive Psychiatry
Verified
Journal Article
Closed access
EDEce Durmusoglu
Ece Durmusoglu
OUOnur Ugurlu
Onur Ugurlu
SASebnem Akan
Sebnem Akan
FSFatma Simsek
Fatma Simsek
GKGozde Kizilates
Gozde Kizilates
AGAli Saffet Gonul
Ali Saffet Gonul

30 August 2023 in IEEE/ACM Transactions on Networking
Verified
Journal Article
Closed access
VAVahid Akram
Vahid Akram
OUOnur Ugurlu
Onur Ugurlu
An articulation point is a node whose removal partitions the network into disconnected segments. The articulation points may affect the reliability and efficiency of wireless multi-hop networks from different aspects. Although all articulation points destroy the connectivity of the network, their negative impact on the network is not equal. Removing some articulation points may disconnect a large subset of nodes or generate a large number of partitions, while removing some other articulation points may only disconnect a few nodes. In this paper, we present two novel problems for identifying the most vital articulation points that significantly impact the network. The first problem is finding the $p$ most important articulation points that minimize the largest connected component in the remaining network. The second problem is finding the $p$ most important articulation points whose removal maximizes the number of partitions in the network. We prove that both problems are NP-Hard and propose a distributed algorithm to identify the vital articulation points in both problems. The proposed algorithm establishes a distributed depth-first search tree to identify the articulation points, assigns a score to each articulation point, and selects the prominent articulation points based on their scores. We compare the proposed algorithm with a brute force-based exact algorithm. The simulation result shows that after removing the detected prominent articulation points by the proposed algorithm, the maximum difference between the largest partition size and the number of partitions with the optimal solutions are less than 27.6% and 28.2%, respectively, while the sent bytes of the proposed algorithm can be 89.9% lower.