A Comparative Study on Maximum Matching Concept to Identify Crucial Components within A Large Complex Network
S.V.S. Santhi1, P. Padmaja2, Sri Harshitha Palla3
1S.V.S. Santhi, Associate Professor, Department of Computer Science and Engineering, Vignan’s Lara Institute of Technology and Science VLITS, Vadlamudi, Guntur (Andhra Pradesh), India.
2P.Padmaja, Professor, Department of Information Technology, Anil Neerukonda Institute of Technology and Science ANITS, Visakhapatnam (Andhra Pradesh), India.
3Sri Harshitha Palla, Student, Department of Information Technology, VIT, Vellore (Tamil Nadu), India.
Manuscript received on 07 March 2019 | Revised Manuscript received on 20 March 2019 | Manuscript published on 30 March 2019 | PP: 967-975 | Volume-8 Issue-5, March 2019 | Retrieval Number: E3128038519/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Previous studies mostly concentrated on the structural properties of the networks rather than behavioural properties. In real world, the networks are large, complex and sparse. To study the behavioural properties, we need to identify the crucial components of large complex networks. So it is necessary to identify driver nodes which provide control over the networks. Hence, it is important to analyze the controllability of these large and complex networks of the real world. For a complete study, we analyzed the maximum matching concept and suggest a comparatively more efficient approach. This paper puts-forth a delineate analysis of maximum matching concept using an example network.
Keyword: Complex Networks, Controllability, Maximum Matching, Matched Nodes, Driver Nodes.
Scope of the Article: Network Performance, Protocols, Sensors