An Efficient Stack Based Graph Traversal Method for Network Configuration
Prajwala. N. B1, Vijayalakshmi. M. K2
1Prajwala. N. B, Department of Computer Science, Amrita School of Arts & Sciences, Amrita Vishwa Vidyapeetham, Mysuru, (Karnataka), India.
2Vijayalakshmi. M. K, Department of Computer Science, Amrita School of Arts & Sciences, Amrita Vishwa Vidyapeetham, Mysuru, (Karnataka), India.
Manuscript received on 02 June 2019 | Revised Manuscript received on 10 June 2019 | Manuscript published on 30 June 2019 | PP: 1447-1451 | Volume-8 Issue-8, June 2019 | Retrieval Number: H7514068819/19©BEIESP
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© 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: The research focuses on the efficient approach to find out the connectivity between nodes and provides the list of networks of the network if available. Networks can be logically represented as a graph; graph traversal is one of the common mechanisms in the network to find the connectivity and subnetworks. In this proposed approach stacks are used to find a number of connected components. The number of resultant stacks is a metric for measurement of components. The proposed algorithm is efficient compared to graph traversal techniques like BFS and DFS as its order of complexity is O(n2). Finding a number of components can be useful to find connectivity in networks to check reachability in the network, connectivity in any electronic circuits and island and so on. The graph can be represented by adjacency matrix or incidence matrix. If there is an edge between two vertices, then it is represented by 1 and 0 otherwise. Incidence matrix is an n*m matrix where n is a number of vertices and m is a number of edges, where rows represent vertices and column represents edges. If two vertices are connected by an edge, then it is represented by 1 and 0 otherwise.
Keyword: Adjacency Matrix, Graph; Networks of Network, Stack, VBS.
Scope of the Article: Advanced Computer Networking.