2014
DOI: 10.12988/ijcms.2014.410105
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Root square mean labeling of graphs

Abstract: A graph = ( , ) with vertices and edges is said to be a Root Square Mean graph if it is possible to label the vertices ∈ with distinct elements ( ) from 1,2, … , + 1 in such a way that when each edge = is labeled with⌋ , then the resulting edge labels are distinct. In this case is called a Root Square Mean labeling of .In this paper we prove that Path ,

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Cited by 17 publications
(7 citation statements)
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“…A very good application of graph labeling is given in [3,4] Jayasekaran and David Raj introduced the concept one modulo three harmonic mean labeling of graphs in [5]. Root square mean labeling was introduced by Sandhya, Somasundaram and Anusa in [6]. Jayasekaran and Jaslin Melbha introduced the concept one modulo three root square mean labeling of graphs in [7].…”
Section: Introductionmentioning
confidence: 99%
“…A very good application of graph labeling is given in [3,4] Jayasekaran and David Raj introduced the concept one modulo three harmonic mean labeling of graphs in [5]. Root square mean labeling was introduced by Sandhya, Somasundaram and Anusa in [6]. Jayasekaran and Jaslin Melbha introduced the concept one modulo three root square mean labeling of graphs in [7].…”
Section: Introductionmentioning
confidence: 99%
“…Mean labeling of graphs was discussed in [3,4,6], the concept of k-even mean and (k, d)-even mean are introduced and discussed in [2], the concept of root square mean labeling was introduced and discussed in [7] and the concept of super root square mean labeling was introduced and discussed in [8]. In this paper, we investigate super root square mean labeling of 2 n P , slanting ladder, …”
Section: Introductionmentioning
confidence: 99%
“…The mean labeling was introduced by Somasundram and Ponraj [2]. Root square mean labeling was introduced by Sandhya, Somasundram and Anusa in [3]. The square sum and square difference labelings were introduced by Ajitha, Arumugam and Germina [4].…”
Section: Introductionmentioning
confidence: 99%