SlideShare a Scribd company logo
1 of 6
Download to read offline
IOSR Journal of Mathematics (IOSR-JM)
e-ISSN: 2278-5728,p-ISSN: 2319-765X, Volume 6, Issue 2 (Mar. - Apr. 2013), PP 05-10
www.iosrjournals.org
www.iosrjournals.org 5 | Page
To find a non-split strong dominating set of an interval graph
using an algorithm
Dr. A. Sudhakaraiah*, A. Sreenivasulu1
,V. Rama Latha2
, E. Gnana Deepika3
,
Department of Mathematics, S. V . University, Tirupati-517502, Andhra Pradesh, India.
Abstract: In graph theory, a connected component of an undirected graph is a sub graph in which any two
vertices are connected to each other by paths. For a graph G, if the subgraph of G itself is a connected
component then the graph is called connected, else the graph G is called disconnected and each connected
component sub graph is called it’s components. A dominating set Dst of graph G=(V,E) is a non-split strong
dominating set if the induced sub graph < V-Dst > is connected. The non-split strong domination number of G is
the minimum cardinality of a non-split strong dominating set . In this paper constructed a verification method
algorithm for finding a non-split strong dominating set of an interval graph.
Keywords: Domination number, Interval graph, Strong dominating set, Strong domination number , split
dominating set.
I. Introduction
Let I = {I1,I2 ,….,I n} be the given interval family. Each interval i in I is represented by [ , ]i ia b , for
1,2,.....,i n . Here ia is called the left endpoint and ib the right endpoint of the interval I i .Without loss of
generality we may assume that all end points of the intervals in I which are distinct between 1and 2n. The intervals
are labelled in the increasing order of their right endpoints. Two intervals i and j are said to intersect each other, if
they have non-empty intersection. Interval graphs play important role in numerous applications, many of which are
scheduling problems. A graph ( , )G V E is called an interval graph if there is a one-to-one correspondence
between V and I such that two vertices of G are joined by an edge in E if and only if their corresponding intervals
in I intersect. That is, if
[ , ]i ii a b and [ , ]j jj a b , then i and j intersect means either j ia b or i ja b .
Let G be a graph, with vertex set V and edge set E .
The open neighbourhood set of a vertex v V is ( ) { / }nbd v u V uv E   .
The closed neighbourhood set of a vertex v V is [ ] ( ) { }nbd v nbd v v  .
A vertex in a graph G dominates itself and its neighbors. A set D V is called dominating set if every
vertex in V D   is adjacent to some vertex in D. The domination studied in [1-2]. The domination number 
of G is the minimum cardinality of a dominating set. The domination number is well-studied parameter. We can
see this from the bibliography [3] on domination. In [4] , Sampathkumar and Pushpa Latha have introduced the
concept of strong domination in graphs. Strong domination has been studied [5-7]. Kulli. V. R. et all [8]
introduced the concept of split and non-split domination[9] in graphs. Also Dr.A. Sudhakaraiah et all [10]
discussed an algorithm for finding a strong dominating set of an interval graph using an algorithm . A
dominating set D is called split dominating set if the induced subgraph V D   is disconnected. The split
domination number of s of G is the minimum cardinality of a split dominating set. Let ( , )G V E be a graph
and ,u v V .
Then u strongly dominates v if
(i) uv E
(ii) deg v deg u .
A set Dst  V is a strong dominating set of G if every vertex in stV D is strongly dominated by at
least one vertex in stD . The strong domination number ( )st G of G is the minimum cardinality of a strong
dominating set. A dominating set stD V of a graph G is a Non-split strong dominating set if the induced subgraph
V D   is connected.Define ( ) , if bi jNI i j a  and there do not exist an interval k such that i k jb a a  . If
there is no such j , then define ( )NI i null . Nsd (i) is the set of all neighbors whose degree is greater than degree
To find a non-split strong dominating set of an interval graph using an algorithm
www.iosrjournals.org 6 | Page
of i and also greater than i.If there is no such neighbor then defines ( ) .sdN i null M (S) is the largest highest
degree vertex in the set S.
II. Algorithms.
2.1.To find a Strong dominating set (SDS) of an interval graph using an algorithm[9].
Input : Interval family 1 2{ , ,....., }nI I I I .
Output : Strong dominating set of an interval graph of a given interval family.
11 : [1]Step S nbd .
1 12 : S = The set of vertices in S which are adjacent to all other vertices in S .Step
3 : D The largest highest degree interval in S.stStep 
4 : LI The largest interval in DstStep 
5 : If N ( ) existssdStep LI
5.1 : a = M(N ( ))sdStep LI .
 5.2 : b The largest highest degree interval in nbd a .Step 
5.3 : D { }st stStep D b  goto step 4.
end if
else
6 : Find NI(LI)Step
6.1: If NI(LI) null goto step 7Step .
26.2 : S [ ( )]Step nbd NI LI .
36.3 : S The set of all neighbors of ( ) which are greaterthan or equalto ( ).Step NI LI NI LI
4 3 36.4 : S The set of all vertices in S which are adjacent to all vertices in S .Step 
46.5 : c = The largest highest degree interval in S .Step
6.6 : D { }st stStep D c  goto step 4.
7 : End.Step
2.2.To find a Non-split Strong dominating set (NSSDS) of an interval graph using an algorithm.
Input : Interval family I= {I1,I2,I3,-------------In} .
Output : Whether a strong dominating set is a non split strong dominating set or not.
Step1 : S1=nbd[1]
Step2 : S=The set of vertices in S1 which are adjacent to all other vertices in S1.
Step3 : Dst=The largest highest degree interval in S .
Step4 : LI=The largest interval in Dst
Step5 : If Wsd (LI) exists
Step 5.1 : a = M(Nsd(LI))
Step 5.2 : b=The largest highest degree interval in nbd[a]
Step 5.3 : Dst = Dst{b} go to step 4
End if
Else
Step 6 : Find NI(LI).
Step 6.1 : If NI(LI)=null go to step 7.
Step 6.2 : S2=nbd[NI(LI)]
36.3 : S The set of all neighbors of ( ) which are greater than or
equalto ( ).
Step NI LI
NI LI

4 3
3
6.4 : S The set of all vertices in S which are adjacent to all
vertices in S .
Step 
46.5 : c = The largest highest degree interval in S .Step
6.6 : D { }st stStep D c  goto step 4.
Step 7 : V={1, 2,3,------------,n}
Step 8 : |Dst|=k
Step 9 : SN={V-Dst}={S1,S2,S3,-----------,Sk}, k1≤ n-k
To find a non-split strong dominating set of an interval graph using an algorithm
www.iosrjournals.org 7 | Page
Step 10 : for (i = 1 to k1-1)
{
For ( j = i+1 to k1 )
{
If (Si,Sj)E of G then plot Si to Sj
} }
The induced sub graph G1=V-Dst is obtained
Step11 : If W(G1)=1
Dst is non split strong dominating set
Else
Dst is split strong dominating set
End.
III. Main Theorems
Theroem 1 : Let G be an interval graph corresponding to an interval family I={I1,I2,I3,------.In}. If i and j are
any two intervals in I such that iDst is minimum strong dominating set of the given interval graph G, j≠1 and j
is contained in i and if there is at least one interval to the left of j that intersects j and at least one interval k≠ i to
the right of j that intersects j then Dst is a non split strong domination.
Proof : Let G be an interval graph corresponding to an interval family I = {I1,I2,I3,------In}. Let i and j be any
two intervals in I such that i Dst ,where Dst is a minimum strong dominating set of the given interval graph G,
j ≠1 and j is contained in i and suppose there is at least one interval to the left of j that intersects j and at least
one interval k ≠ i to the right of j that intersects j.Then it is obviously we know that j is adjacent to k in the
induced subgraph <V-Dst>.Then there will be a connection in <V-Dst> to its left.
Interval family I
As follows an algorithm with illustration for neighbours as given interval family I. We construct an interval
graph G from interval family I={1,2,3,--------10} as follows
nbd[1]={1,2,3}, nbd[2]={1,2,3,4}, nbd[3]={1,2,3,4,6},
nbd [4]={2,3,4,5,6}, nbd [5]={4,5,6,7}, nbd[6]={3,4,5,6,7,9},
nbd[7]={5,6,7,8,9}, nbd[8]={7,8,9,10}, nbd [9]={6,7,8,9,10},
nbd[10]={8,9,10}.
Nsd(1)={2,3}, Nsd(2)={3,4}, Nsd(3)={6}, Nsd(4)=6, Nsd(5)={6}, Nsd(6)=null, Nsd(7)=null, Nsd(8)={9},
Nsd(9)=null, Nsd(10)=null.
NI(1)=4, NI(2)=5, NI(3)=5, NI(4)=7, NI(5)=8, NI(6)=8, NI(7)=10, NI(8)=null, NI(9)=null,
NI(10)=null.
Procedure for finding a non-split strong dominating set of an interval graph using an algorithm.
Step 1: S1={1,2,3}.
Step 2: S={1,2,3}.
Step 3 : Dst={3}.
Step 4 : LI=3.
Step 5 : Nsd(3)={6}.
Step 5.1 : a=M(Nsd(3))=M({6})=6.
Step 5.2 : b=6.
Step 5.3 : Dst={3}{6}={3,6}
Step 6 : LI=6.
Step 7 : NI(6)=8
Step7.1: S2=nbd[8]={7,8,9,10}.
Step7.2: S3={8,9,10}.
Step7.3: S4={8,9,10}
Step7.4:c=9.
Step7.5 : Dst= Dst{9}={3,6}{9}={3,6,9}.
Step 8 : V={1,2,3,--------10}
1 4 7 10
2 6 8
953
To find a non-split strong dominating set of an interval graph using an algorithm
www.iosrjournals.org 8 | Page
Step 9 : |Dst|=3
Step10 : SN={1,2,3,4,5,6,8,10}
Step11 : for i=1, j=2, (1,2)E, plot 1 to 2
for i = 2 , j =3, (2,3)E, plot 2 to 3
for i = 3, j = 4, (4,5)E, plot 4 to 5
j = 5, (4,6)E, plot4 to 6
for i = 4, j = 5, (5,6)E, plot 5 to 6
j = 6, (5,7)E, plot 5 to 7
for i = 5, j=6, (6,7)E, plot 6 to7
for i = 6, j = 7, (7,8)E, plot 7 to 8
for i =7, j = 8, (8,10)E, plot 8 to 10
The induced sub graph G1=<V-Dst> is obtained.
Step12 : W(G1)=1
Therefore Dst is the non split dominating set .
Step13: End .
Out put : {3,6,9} is a non split strong dominating set .
Theorem 2 : If i and j are two intervals in I such that iDst where Dst is a minimum dominating set of G, j=1
and j is contained in i and if there is one more interval other than i that intersects j then non-split strong
domination occurs in G.
Proof : Let I = {I1,I2,I3,I4,------,In} be an interval family. Let j=1 be the interval contained in i where iDst,
where Dst is the minimum strong dominating set of G. Suppose k is an interval , k≠i and k intersect j. Since
iDst , the induced subgraph <V-Dst> does not contain i. Further in <V-Dst>, the vertex j is adjacent to the
vertex k and hence there will not be any disconnection in <V-Dst> . Therefore we get non split strong
domination in G .In this connection as follows an algorithm .
Interval family I
As follows an algorithm with illustration for neighbours as given interval family I. We construct an interval
graph G from interval family I={1,2,3,--------10} as follows
nbd[1]={1,2,3}, nbd[2]={1,2,3,4}, nbd[3]={1,2,3,4,6},
nbd [4]={2,3,4,6,7}, nbd [5]={5,6,7}, nbd[6]={3,4,5,6,7,8},
nbd[7]={4,5,6,7,8,9}, nbd[8]={6,7,8,9,10}, nbd [9]={ 7,8,9,10}, nbd[10]={8,9,10}.
Nsd(1)={2,3}, Nsd(2) ={3,4}, Nsd(3) = {4}, Nsd(4) ={7}, Nsd(5) ={7}, Nsd(6)= {7}, Nsd(7)= null, Nsd(8)=
null Nsd(9)=null, Nsd(10)=null.
NI(1)=4, NI(2)=5, NI(3)=5, NI(4)=5, NI(5)=8, NI(6)=9, NI(7)=10, NI(8)=null, NI(9)=null,
NI(10)=null.
Procedure for finding a non-split strong dominating set of an interval graph using an algorithm.
Step 1 : S1={1,2,3}
Step 2 : S={1,2,3}
Step 3 : Dst=3
Step 4 : LI=3
Step 5 : Nsd(3)=6
Step 6 : a=6
Step 7 : b=7
Step 8 : Dst={3}{7}={3,7}
Step 9 : LI=7
Step10 : NI(7)=10
Step10.1: S2={8,9,10}
Step10.2 : S3={10}
Step10.3 : S4={10}
Step10.4 : b=10
Step10.5 : Dst ={3,7,9}
Step11 : V={1,2,3,--------10}
Step12 : |Dst|=3
Step13 : SN={1,2,4,5,6,8,9}
92
1
3
4 5
6
8
7 10
To find a non-split strong dominating set of an interval graph using an algorithm
www.iosrjournals.org 9 | Page
Step14 : for i=1, j=2 ,(1,2)E , plot 1 to 2
for i = 2, j = 3, (2,4)E, plot 2 to 4
for i = 3, j = 4, (4,5)E, plot 4 to 5
for i = 4, j = 5, (5,6)E, plot 5 to 6
for i = 5, j =6, (6,8)E, plot 6 to 8
for i = 6,j =7, (8,9)E, plot 8 to 9
The induced subgraph G1 = <V-Dst > is obtained .
Step15 : W(G1)=1.
Therefore Dst is the non split strong dominating set.
Step16: End
Output : {3,7,10} is a non split strong dominating set .
Theorem 3 : Let Dst be a strong dominating set which is obtained by algorithm SDS. If i, j, k are three
consecutive intervals such that i < j< k and jDst, i intersects j, j intersect k and i interest k then non split strong
domination occurs in G .
Proof : Suppose I = {I1,I2,I3,------In} be an interval family . Let i, j, k be three consecutive intervals satisfying
the hypothesis. Now i and k intersect implies that i and k are adjacent induced sub graph < VDst > an algorithm
as follows .
Interval family I
As follows an algorithm with illustration for neighbours as given interval family I. We construct an interval
graph G from interval family I={1,2,3,--------10} as follows
nbd[1]={1,2,3}, nbd[2]={1,2,3,4}, nbd[3]={1,2,3,4,5},
nbd [4]={2,3,4,5,6}, nbd [5]={3,4,5,6,7}, nbd[6]={4,5,6,7,8},
nbd[7]={5,6,7,8,9}, nbd[8]={6,7,8,9}, nbd [9]={7,8,9,10}, nbd[10]={9,10}.
Nsd(1)={2,3}, Nsd(2)={3,4}, Nsd(3)=null, Nsd(4)=null, Nsd(5)=null, Nsd(6)=null, Nsd(7)=null,
Nsd(8)=null, Nsd(9)=null, Nsd(10)=null.
NI(1) = 4, NI(2) = 5, NI(3) = 6, NI(4) = 7, NI(5) = 8, NI(6) = 9, NI(7)=10, NI(8)=10, NI(9) =
null, NI(10) = null.
Procedure for finding a non-split strong dominating set of an interval graph using an algorithm.
Step 1 : S1={1,2,3}
Step 2 : S={1,2,3}
Step 3 : Dst=3
Step 4 : LI=3
Step 5 : NI(3)=6
Step 6 : Nbd[6]={4,5,6,7,8}
Step 6.1: S3 = {6,7,8}
Step 6.2 : S3 = {6,7,8}
Step 6.3 : S4 = {6,7,8}
Step 6.4 : c=8
Step 6.5 : Dst ={3,8}
Step 7 : LI=8
Step 8 : NI(8)=null
Step 9 : V={1,2,3,--------10}
Step10 : |Dst|=2
Step11: SN={1,2,4,5,6, 9,10}
Step12 : for i=1, j=2 ,(1,2)E, plot 1 to 2
for i=2, j=3, (2,4)E , plot 2 to 4
for i=3, j=4, (4,5)E, plot 4 to 5
j=5, (4,6)E, plot 4 to 6
for i=4, j=5, (5,6)E, plot 5 to 6
j=6, (5,7)E, plot 5 to 7
1
2
3
4
5
6
7
8
9
10
To find a non-split strong dominating set of an interval graph using an algorithm
www.iosrjournals.org 10 | Page
for i=5, j=6, (6,7)E, plot 6 to 7
for i=6,j=7, (7,9)E, plot 7 to 9
The induced sub graph G1 is obtained .
Step13:W(G1)=1
Therefore Dst is the non split strong dominating set.
Step14: End
Output: {3,8} is a non split strong dominating set .
IV. Conclusions
We studied the non-split strong domination in interval graphs. In this paper we discussed a
verification method algorithm for finding a non-split strong dominating set of an interval graph.
Acknowledgements
The authors would like to express their gratitude of the anonymous referees for their suggestions and
inspiring comments on this paper
References
[1]. T. W. Haynes, S.T. Hedetniemi and P.J.Slater, Fundamentals of domination in graphs, Marcel Dekker, Inc., New York (1998).
[2]. T. W. Haynes, S.T. Hedetniemi and P.J.Slater, Domination in Graphs: advanced topics , Marcel Dekker, Inc., New York (1998).
[3]. Hedetniemi, S. T, Laskar, R. C. , Bibliography on domination in graphs and some basic definitions of domination parameters, Discrete
Mathematics 86 (1–3), (1990), 257–277.
[4]. Sampathkumar, E., and Pushpa Latha, Strong weak domination and domination balance in graph, Discrete Math. Vol. 161, 1996, p.
235-242.
[5]. Domke et.al, On parameters related to strong and weak domination in graphs, Discrete Math. Vol. 258, (2002) p. ,1-11.
[6]. Hattingh J.H., Henning M.A., On strong domination in Graphs, J. Combin. Math. Combin. Comput. Vol.26, (1998) p. 73-92.
[7]. Rautenbach, D., Bounds on the strong domination number, Discrete Math. Vol. 215, (2000) p. 201-212.
[8]. Kulli, V. R. and Janakiram, B., The Non-Split domination number of graph, International Journal of management and systems.
Vol.19. No.2, p. 145-156, 2000.
[9]. Maheswari, B., Nagamuni Reddy, L., and A. Sudhakaraiah , Split and Non-split dominating set of circular-arc graphs, J. curr. Sci Vol
3. No.2, (2003)p. 369-372 .
[10]. Dr. A. Sudhakaraiah, V. Rama Latha, E. Gnana Deepika and T.Venkateswarulu, To Find Strong Dominating Set and Split Strong
Dominating Set of an Interval Graph Using an Algorithm, IJSER , Vol. 2,(2012), 1026-1034.

More Related Content

What's hot

Connected domination in block subdivision graphs of graphs
Connected domination in block subdivision graphs of  graphsConnected domination in block subdivision graphs of  graphs
Connected domination in block subdivision graphs of graphsAlexander Decker
 
A study on connectivity in graph theory june 18 123e
A study on connectivity in graph theory  june 18 123eA study on connectivity in graph theory  june 18 123e
A study on connectivity in graph theory june 18 123easwathymaths
 
IJCER (www.ijceronline.com) International Journal of computational Engineerin...
IJCER (www.ijceronline.com) International Journal of computational Engineerin...IJCER (www.ijceronline.com) International Journal of computational Engineerin...
IJCER (www.ijceronline.com) International Journal of computational Engineerin...ijceronline
 
Dissertation on petal graphs
Dissertation on petal graphsDissertation on petal graphs
Dissertation on petal graphsAngelSophia2
 
Algorithmic Aspects of Vertex Geo-dominating Sets and Geonumber in Graphs
Algorithmic Aspects of Vertex Geo-dominating Sets and Geonumber in GraphsAlgorithmic Aspects of Vertex Geo-dominating Sets and Geonumber in Graphs
Algorithmic Aspects of Vertex Geo-dominating Sets and Geonumber in GraphsIJERA Editor
 
Paper id 71201961
Paper id 71201961Paper id 71201961
Paper id 71201961IJRAT
 
Graph theory concepts complex networks presents-rouhollah nabati
Graph theory concepts   complex networks presents-rouhollah nabatiGraph theory concepts   complex networks presents-rouhollah nabati
Graph theory concepts complex networks presents-rouhollah nabatinabati
 
Graph theory and its applications
Graph theory and its applicationsGraph theory and its applications
Graph theory and its applicationsManikanta satyala
 
Discrete-Chapter 11 Graphs Part II
Discrete-Chapter 11 Graphs Part IIDiscrete-Chapter 11 Graphs Part II
Discrete-Chapter 11 Graphs Part IIWongyos Keardsri
 
Discrete-Chapter 11 Graphs Part I
Discrete-Chapter 11 Graphs Part IDiscrete-Chapter 11 Graphs Part I
Discrete-Chapter 11 Graphs Part IWongyos Keardsri
 
Multilayerity within multilayerity? On multilayer assortativity in social net...
Multilayerity within multilayerity? On multilayer assortativity in social net...Multilayerity within multilayerity? On multilayer assortativity in social net...
Multilayerity within multilayerity? On multilayer assortativity in social net...Moses Boudourides
 
Discrete-Chapter 11 Graphs Part III
Discrete-Chapter 11 Graphs Part IIIDiscrete-Chapter 11 Graphs Part III
Discrete-Chapter 11 Graphs Part IIIWongyos Keardsri
 
Graph Theory: Connectivity & Isomorphism
Graph Theory: Connectivity & Isomorphism Graph Theory: Connectivity & Isomorphism
Graph Theory: Connectivity & Isomorphism Ashikur Rahman
 
Dominating Sets, Multiple Egocentric Networks and Modularity Maximizing Clust...
Dominating Sets, Multiple Egocentric Networks and Modularity Maximizing Clust...Dominating Sets, Multiple Egocentric Networks and Modularity Maximizing Clust...
Dominating Sets, Multiple Egocentric Networks and Modularity Maximizing Clust...Moses Boudourides
 

What's hot (17)

Connected domination in block subdivision graphs of graphs
Connected domination in block subdivision graphs of  graphsConnected domination in block subdivision graphs of  graphs
Connected domination in block subdivision graphs of graphs
 
A study on connectivity in graph theory june 18 123e
A study on connectivity in graph theory  june 18 123eA study on connectivity in graph theory  june 18 123e
A study on connectivity in graph theory june 18 123e
 
IJCER (www.ijceronline.com) International Journal of computational Engineerin...
IJCER (www.ijceronline.com) International Journal of computational Engineerin...IJCER (www.ijceronline.com) International Journal of computational Engineerin...
IJCER (www.ijceronline.com) International Journal of computational Engineerin...
 
Dissertation on petal graphs
Dissertation on petal graphsDissertation on petal graphs
Dissertation on petal graphs
 
Algorithmic Aspects of Vertex Geo-dominating Sets and Geonumber in Graphs
Algorithmic Aspects of Vertex Geo-dominating Sets and Geonumber in GraphsAlgorithmic Aspects of Vertex Geo-dominating Sets and Geonumber in Graphs
Algorithmic Aspects of Vertex Geo-dominating Sets and Geonumber in Graphs
 
Paper id 71201961
Paper id 71201961Paper id 71201961
Paper id 71201961
 
Graph theory concepts complex networks presents-rouhollah nabati
Graph theory concepts   complex networks presents-rouhollah nabatiGraph theory concepts   complex networks presents-rouhollah nabati
Graph theory concepts complex networks presents-rouhollah nabati
 
Connectivity of graph
Connectivity of graphConnectivity of graph
Connectivity of graph
 
Graph theory and its applications
Graph theory and its applicationsGraph theory and its applications
Graph theory and its applications
 
Discrete-Chapter 11 Graphs Part II
Discrete-Chapter 11 Graphs Part IIDiscrete-Chapter 11 Graphs Part II
Discrete-Chapter 11 Graphs Part II
 
Aj26225229
Aj26225229Aj26225229
Aj26225229
 
Discrete-Chapter 11 Graphs Part I
Discrete-Chapter 11 Graphs Part IDiscrete-Chapter 11 Graphs Part I
Discrete-Chapter 11 Graphs Part I
 
Multilayerity within multilayerity? On multilayer assortativity in social net...
Multilayerity within multilayerity? On multilayer assortativity in social net...Multilayerity within multilayerity? On multilayer assortativity in social net...
Multilayerity within multilayerity? On multilayer assortativity in social net...
 
thesis
thesisthesis
thesis
 
Discrete-Chapter 11 Graphs Part III
Discrete-Chapter 11 Graphs Part IIIDiscrete-Chapter 11 Graphs Part III
Discrete-Chapter 11 Graphs Part III
 
Graph Theory: Connectivity & Isomorphism
Graph Theory: Connectivity & Isomorphism Graph Theory: Connectivity & Isomorphism
Graph Theory: Connectivity & Isomorphism
 
Dominating Sets, Multiple Egocentric Networks and Modularity Maximizing Clust...
Dominating Sets, Multiple Egocentric Networks and Modularity Maximizing Clust...Dominating Sets, Multiple Egocentric Networks and Modularity Maximizing Clust...
Dominating Sets, Multiple Egocentric Networks and Modularity Maximizing Clust...
 

Viewers also liked

The prediction of moisture through the use of neural networks MLP type
The prediction of moisture through the use of neural networks MLP typeThe prediction of moisture through the use of neural networks MLP type
The prediction of moisture through the use of neural networks MLP typeIOSR Journals
 
Performance analysis of Fuzzy logic based speed control of DC motor
Performance analysis of Fuzzy logic based speed control of DC motorPerformance analysis of Fuzzy logic based speed control of DC motor
Performance analysis of Fuzzy logic based speed control of DC motorIOSR Journals
 
Guide to iBeacons: How they work and how they can be used
Guide to iBeacons: How they work and how they can be used Guide to iBeacons: How they work and how they can be used
Guide to iBeacons: How they work and how they can be used Phill Hunt
 
Scalable Transaction Management on Cloud Data Management Systems
Scalable Transaction Management on Cloud Data Management SystemsScalable Transaction Management on Cloud Data Management Systems
Scalable Transaction Management on Cloud Data Management SystemsIOSR Journals
 
Pattern Mapping Approach for Detecting Xss Attacks In Multi-Tier Web Applicat...
Pattern Mapping Approach for Detecting Xss Attacks In Multi-Tier Web Applicat...Pattern Mapping Approach for Detecting Xss Attacks In Multi-Tier Web Applicat...
Pattern Mapping Approach for Detecting Xss Attacks In Multi-Tier Web Applicat...IOSR Journals
 
Comparative Analysis of Collaborative Filtering Technique
Comparative Analysis of Collaborative Filtering TechniqueComparative Analysis of Collaborative Filtering Technique
Comparative Analysis of Collaborative Filtering TechniqueIOSR Journals
 
Enhancing Privacy in Cloud Service Provider Using Cryptographic Algorithm
Enhancing Privacy in Cloud Service Provider Using Cryptographic AlgorithmEnhancing Privacy in Cloud Service Provider Using Cryptographic Algorithm
Enhancing Privacy in Cloud Service Provider Using Cryptographic AlgorithmIOSR Journals
 
CLUBNIK угадай-ка
CLUBNIK угадай-каCLUBNIK угадай-ка
CLUBNIK угадай-каMihail Nadymov
 
Dynamic AI-Geo Health Application based on BIGIS-DSS Approach
Dynamic AI-Geo Health Application based on BIGIS-DSS ApproachDynamic AI-Geo Health Application based on BIGIS-DSS Approach
Dynamic AI-Geo Health Application based on BIGIS-DSS ApproachIOSR Journals
 
Wireless Speed Control of an Induction Motor Using Pwm Technique with Gsm
Wireless Speed Control of an Induction Motor Using Pwm Technique with GsmWireless Speed Control of an Induction Motor Using Pwm Technique with Gsm
Wireless Speed Control of an Induction Motor Using Pwm Technique with GsmIOSR Journals
 
Tools for Ontology Building from Texts: Analysis and Improvement of the Resul...
Tools for Ontology Building from Texts: Analysis and Improvement of the Resul...Tools for Ontology Building from Texts: Analysis and Improvement of the Resul...
Tools for Ontology Building from Texts: Analysis and Improvement of the Resul...IOSR Journals
 
Role of Machine Translation and Word Sense Disambiguation in Natural Language...
Role of Machine Translation and Word Sense Disambiguation in Natural Language...Role of Machine Translation and Word Sense Disambiguation in Natural Language...
Role of Machine Translation and Word Sense Disambiguation in Natural Language...IOSR Journals
 
Improving Security Measures of E-Learning Database
Improving Security Measures of E-Learning DatabaseImproving Security Measures of E-Learning Database
Improving Security Measures of E-Learning DatabaseIOSR Journals
 
Three Phase Digitally Controlled Power Factor Improvement System
Three Phase Digitally Controlled Power Factor Improvement SystemThree Phase Digitally Controlled Power Factor Improvement System
Three Phase Digitally Controlled Power Factor Improvement SystemIOSR Journals
 
International Medical Careers Forum Oct 15 2016
International Medical Careers Forum Oct 15 2016International Medical Careers Forum Oct 15 2016
International Medical Careers Forum Oct 15 2016Odyssey Recruitment
 
A New Approach of Protein Sequence Compression using Repeat Reduction and ASC...
A New Approach of Protein Sequence Compression using Repeat Reduction and ASC...A New Approach of Protein Sequence Compression using Repeat Reduction and ASC...
A New Approach of Protein Sequence Compression using Repeat Reduction and ASC...IOSR Journals
 
Incidence of Equine Hoof Derangements in Malaysian Horse Population
Incidence of Equine Hoof Derangements in Malaysian Horse PopulationIncidence of Equine Hoof Derangements in Malaysian Horse Population
Incidence of Equine Hoof Derangements in Malaysian Horse PopulationIOSR Journals
 
Enhanced Clustering Algorithm for Processing Online Data
Enhanced Clustering Algorithm for Processing Online DataEnhanced Clustering Algorithm for Processing Online Data
Enhanced Clustering Algorithm for Processing Online DataIOSR Journals
 
Implementation of RISC-Based Architecture for Low power applications
Implementation of RISC-Based Architecture for Low power applicationsImplementation of RISC-Based Architecture for Low power applications
Implementation of RISC-Based Architecture for Low power applicationsIOSR Journals
 
Optimization of Mining Association Rule from XML Documents
Optimization of Mining Association Rule from XML DocumentsOptimization of Mining Association Rule from XML Documents
Optimization of Mining Association Rule from XML DocumentsIOSR Journals
 

Viewers also liked (20)

The prediction of moisture through the use of neural networks MLP type
The prediction of moisture through the use of neural networks MLP typeThe prediction of moisture through the use of neural networks MLP type
The prediction of moisture through the use of neural networks MLP type
 
Performance analysis of Fuzzy logic based speed control of DC motor
Performance analysis of Fuzzy logic based speed control of DC motorPerformance analysis of Fuzzy logic based speed control of DC motor
Performance analysis of Fuzzy logic based speed control of DC motor
 
Guide to iBeacons: How they work and how they can be used
Guide to iBeacons: How they work and how they can be used Guide to iBeacons: How they work and how they can be used
Guide to iBeacons: How they work and how they can be used
 
Scalable Transaction Management on Cloud Data Management Systems
Scalable Transaction Management on Cloud Data Management SystemsScalable Transaction Management on Cloud Data Management Systems
Scalable Transaction Management on Cloud Data Management Systems
 
Pattern Mapping Approach for Detecting Xss Attacks In Multi-Tier Web Applicat...
Pattern Mapping Approach for Detecting Xss Attacks In Multi-Tier Web Applicat...Pattern Mapping Approach for Detecting Xss Attacks In Multi-Tier Web Applicat...
Pattern Mapping Approach for Detecting Xss Attacks In Multi-Tier Web Applicat...
 
Comparative Analysis of Collaborative Filtering Technique
Comparative Analysis of Collaborative Filtering TechniqueComparative Analysis of Collaborative Filtering Technique
Comparative Analysis of Collaborative Filtering Technique
 
Enhancing Privacy in Cloud Service Provider Using Cryptographic Algorithm
Enhancing Privacy in Cloud Service Provider Using Cryptographic AlgorithmEnhancing Privacy in Cloud Service Provider Using Cryptographic Algorithm
Enhancing Privacy in Cloud Service Provider Using Cryptographic Algorithm
 
CLUBNIK угадай-ка
CLUBNIK угадай-каCLUBNIK угадай-ка
CLUBNIK угадай-ка
 
Dynamic AI-Geo Health Application based on BIGIS-DSS Approach
Dynamic AI-Geo Health Application based on BIGIS-DSS ApproachDynamic AI-Geo Health Application based on BIGIS-DSS Approach
Dynamic AI-Geo Health Application based on BIGIS-DSS Approach
 
Wireless Speed Control of an Induction Motor Using Pwm Technique with Gsm
Wireless Speed Control of an Induction Motor Using Pwm Technique with GsmWireless Speed Control of an Induction Motor Using Pwm Technique with Gsm
Wireless Speed Control of an Induction Motor Using Pwm Technique with Gsm
 
Tools for Ontology Building from Texts: Analysis and Improvement of the Resul...
Tools for Ontology Building from Texts: Analysis and Improvement of the Resul...Tools for Ontology Building from Texts: Analysis and Improvement of the Resul...
Tools for Ontology Building from Texts: Analysis and Improvement of the Resul...
 
Role of Machine Translation and Word Sense Disambiguation in Natural Language...
Role of Machine Translation and Word Sense Disambiguation in Natural Language...Role of Machine Translation and Word Sense Disambiguation in Natural Language...
Role of Machine Translation and Word Sense Disambiguation in Natural Language...
 
Improving Security Measures of E-Learning Database
Improving Security Measures of E-Learning DatabaseImproving Security Measures of E-Learning Database
Improving Security Measures of E-Learning Database
 
Three Phase Digitally Controlled Power Factor Improvement System
Three Phase Digitally Controlled Power Factor Improvement SystemThree Phase Digitally Controlled Power Factor Improvement System
Three Phase Digitally Controlled Power Factor Improvement System
 
International Medical Careers Forum Oct 15 2016
International Medical Careers Forum Oct 15 2016International Medical Careers Forum Oct 15 2016
International Medical Careers Forum Oct 15 2016
 
A New Approach of Protein Sequence Compression using Repeat Reduction and ASC...
A New Approach of Protein Sequence Compression using Repeat Reduction and ASC...A New Approach of Protein Sequence Compression using Repeat Reduction and ASC...
A New Approach of Protein Sequence Compression using Repeat Reduction and ASC...
 
Incidence of Equine Hoof Derangements in Malaysian Horse Population
Incidence of Equine Hoof Derangements in Malaysian Horse PopulationIncidence of Equine Hoof Derangements in Malaysian Horse Population
Incidence of Equine Hoof Derangements in Malaysian Horse Population
 
Enhanced Clustering Algorithm for Processing Online Data
Enhanced Clustering Algorithm for Processing Online DataEnhanced Clustering Algorithm for Processing Online Data
Enhanced Clustering Algorithm for Processing Online Data
 
Implementation of RISC-Based Architecture for Low power applications
Implementation of RISC-Based Architecture for Low power applicationsImplementation of RISC-Based Architecture for Low power applications
Implementation of RISC-Based Architecture for Low power applications
 
Optimization of Mining Association Rule from XML Documents
Optimization of Mining Association Rule from XML DocumentsOptimization of Mining Association Rule from XML Documents
Optimization of Mining Association Rule from XML Documents
 

Similar to B0620510

IJCER (www.ijceronline.com) International Journal of computational Engineerin...
IJCER (www.ijceronline.com) International Journal of computational Engineerin...IJCER (www.ijceronline.com) International Journal of computational Engineerin...
IJCER (www.ijceronline.com) International Journal of computational Engineerin...ijceronline
 
The Total Strong Split Domination Number of Graphs
The Total Strong Split Domination Number of GraphsThe Total Strong Split Domination Number of Graphs
The Total Strong Split Domination Number of Graphsinventionjournals
 
Equi independent equitable domination number of cycle and bistar related graphs
Equi independent equitable domination number of cycle and bistar related graphsEqui independent equitable domination number of cycle and bistar related graphs
Equi independent equitable domination number of cycle and bistar related graphsiosrjce
 
IRJET- On Strong Domination Number of Jumpgraphs
IRJET- On Strong Domination Number of JumpgraphsIRJET- On Strong Domination Number of Jumpgraphs
IRJET- On Strong Domination Number of JumpgraphsIRJET Journal
 
ICAMS033-G.NITHYA.pptx
ICAMS033-G.NITHYA.pptxICAMS033-G.NITHYA.pptx
ICAMS033-G.NITHYA.pptxmathematicssac
 
Non Split Edge Domination in Fuzzy Graphs
Non Split Edge Domination in Fuzzy GraphsNon Split Edge Domination in Fuzzy Graphs
Non Split Edge Domination in Fuzzy Graphspaperpublications3
 
Algorithmic Aspects of Vertex Geo-dominating Sets and Geonumber in Graphs
Algorithmic Aspects of Vertex Geo-dominating Sets and Geonumber in GraphsAlgorithmic Aspects of Vertex Geo-dominating Sets and Geonumber in Graphs
Algorithmic Aspects of Vertex Geo-dominating Sets and Geonumber in GraphsIJERA Editor
 
V1_I2_2012_Paper1.doc
V1_I2_2012_Paper1.docV1_I2_2012_Paper1.doc
V1_I2_2012_Paper1.docpraveena06
 
International Journal of Computational Engineering Research(IJCER)
 International Journal of Computational Engineering Research(IJCER)  International Journal of Computational Engineering Research(IJCER)
International Journal of Computational Engineering Research(IJCER) ijceronline
 
Global Domination Set in Intuitionistic Fuzzy Graph
Global Domination Set in Intuitionistic Fuzzy GraphGlobal Domination Set in Intuitionistic Fuzzy Graph
Global Domination Set in Intuitionistic Fuzzy Graphijceronline
 
IRJET- Independent Middle Domination Number in Jump Graph
IRJET- Independent Middle Domination Number in Jump GraphIRJET- Independent Middle Domination Number in Jump Graph
IRJET- Independent Middle Domination Number in Jump GraphIRJET Journal
 
Topics of Complex Social Networks: Domination, Influence and Assortativity
Topics of Complex Social Networks: Domination, Influence and AssortativityTopics of Complex Social Networks: Domination, Influence and Assortativity
Topics of Complex Social Networks: Domination, Influence and AssortativityMoses Boudourides
 
International Refereed Journal of Engineering and Science (IRJES)
International Refereed Journal of Engineering and Science (IRJES)International Refereed Journal of Engineering and Science (IRJES)
International Refereed Journal of Engineering and Science (IRJES)irjes
 
Cs6702 2marks rejinpaul
Cs6702 2marks rejinpaulCs6702 2marks rejinpaul
Cs6702 2marks rejinpaulstalinjothi
 
Cs6702 graph theory and applications 2 marks questions and answers
Cs6702 graph theory and applications 2 marks questions and answersCs6702 graph theory and applications 2 marks questions and answers
Cs6702 graph theory and applications 2 marks questions and answersappasami
 

Similar to B0620510 (20)

IJCER (www.ijceronline.com) International Journal of computational Engineerin...
IJCER (www.ijceronline.com) International Journal of computational Engineerin...IJCER (www.ijceronline.com) International Journal of computational Engineerin...
IJCER (www.ijceronline.com) International Journal of computational Engineerin...
 
The Total Strong Split Domination Number of Graphs
The Total Strong Split Domination Number of GraphsThe Total Strong Split Domination Number of Graphs
The Total Strong Split Domination Number of Graphs
 
Equi independent equitable domination number of cycle and bistar related graphs
Equi independent equitable domination number of cycle and bistar related graphsEqui independent equitable domination number of cycle and bistar related graphs
Equi independent equitable domination number of cycle and bistar related graphs
 
E021201032037
E021201032037E021201032037
E021201032037
 
IRJET- On Strong Domination Number of Jumpgraphs
IRJET- On Strong Domination Number of JumpgraphsIRJET- On Strong Domination Number of Jumpgraphs
IRJET- On Strong Domination Number of Jumpgraphs
 
ICAMS033-G.NITHYA.pptx
ICAMS033-G.NITHYA.pptxICAMS033-G.NITHYA.pptx
ICAMS033-G.NITHYA.pptx
 
Non Split Edge Domination in Fuzzy Graphs
Non Split Edge Domination in Fuzzy GraphsNon Split Edge Domination in Fuzzy Graphs
Non Split Edge Domination in Fuzzy Graphs
 
Algorithmic Aspects of Vertex Geo-dominating Sets and Geonumber in Graphs
Algorithmic Aspects of Vertex Geo-dominating Sets and Geonumber in GraphsAlgorithmic Aspects of Vertex Geo-dominating Sets and Geonumber in Graphs
Algorithmic Aspects of Vertex Geo-dominating Sets and Geonumber in Graphs
 
V1_I2_2012_Paper1.doc
V1_I2_2012_Paper1.docV1_I2_2012_Paper1.doc
V1_I2_2012_Paper1.doc
 
International Journal of Computational Engineering Research(IJCER)
 International Journal of Computational Engineering Research(IJCER)  International Journal of Computational Engineering Research(IJCER)
International Journal of Computational Engineering Research(IJCER)
 
H0412071074
H0412071074H0412071074
H0412071074
 
Global Domination Set in Intuitionistic Fuzzy Graph
Global Domination Set in Intuitionistic Fuzzy GraphGlobal Domination Set in Intuitionistic Fuzzy Graph
Global Domination Set in Intuitionistic Fuzzy Graph
 
R04602118121
R04602118121R04602118121
R04602118121
 
IRJET- Independent Middle Domination Number in Jump Graph
IRJET- Independent Middle Domination Number in Jump GraphIRJET- Independent Middle Domination Number in Jump Graph
IRJET- Independent Middle Domination Number in Jump Graph
 
Topics of Complex Social Networks: Domination, Influence and Assortativity
Topics of Complex Social Networks: Domination, Influence and AssortativityTopics of Complex Social Networks: Domination, Influence and Assortativity
Topics of Complex Social Networks: Domination, Influence and Assortativity
 
International Refereed Journal of Engineering and Science (IRJES)
International Refereed Journal of Engineering and Science (IRJES)International Refereed Journal of Engineering and Science (IRJES)
International Refereed Journal of Engineering and Science (IRJES)
 
Cs6702 2marks rejinpaul
Cs6702 2marks rejinpaulCs6702 2marks rejinpaul
Cs6702 2marks rejinpaul
 
Cs6702 GCC
Cs6702 GCCCs6702 GCC
Cs6702 GCC
 
Graph
GraphGraph
Graph
 
Cs6702 graph theory and applications 2 marks questions and answers
Cs6702 graph theory and applications 2 marks questions and answersCs6702 graph theory and applications 2 marks questions and answers
Cs6702 graph theory and applications 2 marks questions and answers
 

More from IOSR Journals (20)

A011140104
A011140104A011140104
A011140104
 
M0111397100
M0111397100M0111397100
M0111397100
 
L011138596
L011138596L011138596
L011138596
 
K011138084
K011138084K011138084
K011138084
 
J011137479
J011137479J011137479
J011137479
 
I011136673
I011136673I011136673
I011136673
 
G011134454
G011134454G011134454
G011134454
 
H011135565
H011135565H011135565
H011135565
 
F011134043
F011134043F011134043
F011134043
 
E011133639
E011133639E011133639
E011133639
 
D011132635
D011132635D011132635
D011132635
 
C011131925
C011131925C011131925
C011131925
 
B011130918
B011130918B011130918
B011130918
 
A011130108
A011130108A011130108
A011130108
 
I011125160
I011125160I011125160
I011125160
 
H011124050
H011124050H011124050
H011124050
 
G011123539
G011123539G011123539
G011123539
 
F011123134
F011123134F011123134
F011123134
 
E011122530
E011122530E011122530
E011122530
 
D011121524
D011121524D011121524
D011121524
 

Recently uploaded

The State of Passkeys with FIDO Alliance.pptx
The State of Passkeys with FIDO Alliance.pptxThe State of Passkeys with FIDO Alliance.pptx
The State of Passkeys with FIDO Alliance.pptxLoriGlavin3
 
DevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache MavenDevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache MavenHervé Boutemy
 
Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024BookNet Canada
 
How AI, OpenAI, and ChatGPT impact business and software.
How AI, OpenAI, and ChatGPT impact business and software.How AI, OpenAI, and ChatGPT impact business and software.
How AI, OpenAI, and ChatGPT impact business and software.Curtis Poe
 
"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii Soldatenko"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii SoldatenkoFwdays
 
Advanced Computer Architecture – An Introduction
Advanced Computer Architecture – An IntroductionAdvanced Computer Architecture – An Introduction
Advanced Computer Architecture – An IntroductionDilum Bandara
 
SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024Lorenzo Miniero
 
Scanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL CertsScanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL CertsRizwan Syed
 
unit 4 immunoblotting technique complete.pptx
unit 4 immunoblotting technique complete.pptxunit 4 immunoblotting technique complete.pptx
unit 4 immunoblotting technique complete.pptxBkGupta21
 
Connect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck PresentationConnect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck PresentationSlibray Presentation
 
DSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine TuningDSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine TuningLars Bell
 
Unraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfUnraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfAlex Barbosa Coqueiro
 
Passkey Providers and Enabling Portability: FIDO Paris Seminar.pptx
Passkey Providers and Enabling Portability: FIDO Paris Seminar.pptxPasskey Providers and Enabling Portability: FIDO Paris Seminar.pptx
Passkey Providers and Enabling Portability: FIDO Paris Seminar.pptxLoriGlavin3
 
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024BookNet Canada
 
New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024BookNet Canada
 
A Deep Dive on Passkeys: FIDO Paris Seminar.pptx
A Deep Dive on Passkeys: FIDO Paris Seminar.pptxA Deep Dive on Passkeys: FIDO Paris Seminar.pptx
A Deep Dive on Passkeys: FIDO Paris Seminar.pptxLoriGlavin3
 
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)Mark Simos
 
Are Multi-Cloud and Serverless Good or Bad?
Are Multi-Cloud and Serverless Good or Bad?Are Multi-Cloud and Serverless Good or Bad?
Are Multi-Cloud and Serverless Good or Bad?Mattias Andersson
 
Dev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebDev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebUiPathCommunity
 
The Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsThe Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsPixlogix Infotech
 

Recently uploaded (20)

The State of Passkeys with FIDO Alliance.pptx
The State of Passkeys with FIDO Alliance.pptxThe State of Passkeys with FIDO Alliance.pptx
The State of Passkeys with FIDO Alliance.pptx
 
DevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache MavenDevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache Maven
 
Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
 
How AI, OpenAI, and ChatGPT impact business and software.
How AI, OpenAI, and ChatGPT impact business and software.How AI, OpenAI, and ChatGPT impact business and software.
How AI, OpenAI, and ChatGPT impact business and software.
 
"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii Soldatenko"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii Soldatenko
 
Advanced Computer Architecture – An Introduction
Advanced Computer Architecture – An IntroductionAdvanced Computer Architecture – An Introduction
Advanced Computer Architecture – An Introduction
 
SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024
 
Scanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL CertsScanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL Certs
 
unit 4 immunoblotting technique complete.pptx
unit 4 immunoblotting technique complete.pptxunit 4 immunoblotting technique complete.pptx
unit 4 immunoblotting technique complete.pptx
 
Connect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck PresentationConnect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck Presentation
 
DSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine TuningDSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine Tuning
 
Unraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfUnraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdf
 
Passkey Providers and Enabling Portability: FIDO Paris Seminar.pptx
Passkey Providers and Enabling Portability: FIDO Paris Seminar.pptxPasskey Providers and Enabling Portability: FIDO Paris Seminar.pptx
Passkey Providers and Enabling Portability: FIDO Paris Seminar.pptx
 
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
 
New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
New from BookNet Canada for 2024: Loan Stars - Tech Forum 2024
 
A Deep Dive on Passkeys: FIDO Paris Seminar.pptx
A Deep Dive on Passkeys: FIDO Paris Seminar.pptxA Deep Dive on Passkeys: FIDO Paris Seminar.pptx
A Deep Dive on Passkeys: FIDO Paris Seminar.pptx
 
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
 
Are Multi-Cloud and Serverless Good or Bad?
Are Multi-Cloud and Serverless Good or Bad?Are Multi-Cloud and Serverless Good or Bad?
Are Multi-Cloud and Serverless Good or Bad?
 
Dev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebDev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio Web
 
The Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsThe Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and Cons
 

B0620510

  • 1. IOSR Journal of Mathematics (IOSR-JM) e-ISSN: 2278-5728,p-ISSN: 2319-765X, Volume 6, Issue 2 (Mar. - Apr. 2013), PP 05-10 www.iosrjournals.org www.iosrjournals.org 5 | Page To find a non-split strong dominating set of an interval graph using an algorithm Dr. A. Sudhakaraiah*, A. Sreenivasulu1 ,V. Rama Latha2 , E. Gnana Deepika3 , Department of Mathematics, S. V . University, Tirupati-517502, Andhra Pradesh, India. Abstract: In graph theory, a connected component of an undirected graph is a sub graph in which any two vertices are connected to each other by paths. For a graph G, if the subgraph of G itself is a connected component then the graph is called connected, else the graph G is called disconnected and each connected component sub graph is called it’s components. A dominating set Dst of graph G=(V,E) is a non-split strong dominating set if the induced sub graph < V-Dst > is connected. The non-split strong domination number of G is the minimum cardinality of a non-split strong dominating set . In this paper constructed a verification method algorithm for finding a non-split strong dominating set of an interval graph. Keywords: Domination number, Interval graph, Strong dominating set, Strong domination number , split dominating set. I. Introduction Let I = {I1,I2 ,….,I n} be the given interval family. Each interval i in I is represented by [ , ]i ia b , for 1,2,.....,i n . Here ia is called the left endpoint and ib the right endpoint of the interval I i .Without loss of generality we may assume that all end points of the intervals in I which are distinct between 1and 2n. The intervals are labelled in the increasing order of their right endpoints. Two intervals i and j are said to intersect each other, if they have non-empty intersection. Interval graphs play important role in numerous applications, many of which are scheduling problems. A graph ( , )G V E is called an interval graph if there is a one-to-one correspondence between V and I such that two vertices of G are joined by an edge in E if and only if their corresponding intervals in I intersect. That is, if [ , ]i ii a b and [ , ]j jj a b , then i and j intersect means either j ia b or i ja b . Let G be a graph, with vertex set V and edge set E . The open neighbourhood set of a vertex v V is ( ) { / }nbd v u V uv E   . The closed neighbourhood set of a vertex v V is [ ] ( ) { }nbd v nbd v v  . A vertex in a graph G dominates itself and its neighbors. A set D V is called dominating set if every vertex in V D   is adjacent to some vertex in D. The domination studied in [1-2]. The domination number  of G is the minimum cardinality of a dominating set. The domination number is well-studied parameter. We can see this from the bibliography [3] on domination. In [4] , Sampathkumar and Pushpa Latha have introduced the concept of strong domination in graphs. Strong domination has been studied [5-7]. Kulli. V. R. et all [8] introduced the concept of split and non-split domination[9] in graphs. Also Dr.A. Sudhakaraiah et all [10] discussed an algorithm for finding a strong dominating set of an interval graph using an algorithm . A dominating set D is called split dominating set if the induced subgraph V D   is disconnected. The split domination number of s of G is the minimum cardinality of a split dominating set. Let ( , )G V E be a graph and ,u v V . Then u strongly dominates v if (i) uv E (ii) deg v deg u . A set Dst  V is a strong dominating set of G if every vertex in stV D is strongly dominated by at least one vertex in stD . The strong domination number ( )st G of G is the minimum cardinality of a strong dominating set. A dominating set stD V of a graph G is a Non-split strong dominating set if the induced subgraph V D   is connected.Define ( ) , if bi jNI i j a  and there do not exist an interval k such that i k jb a a  . If there is no such j , then define ( )NI i null . Nsd (i) is the set of all neighbors whose degree is greater than degree
  • 2. To find a non-split strong dominating set of an interval graph using an algorithm www.iosrjournals.org 6 | Page of i and also greater than i.If there is no such neighbor then defines ( ) .sdN i null M (S) is the largest highest degree vertex in the set S. II. Algorithms. 2.1.To find a Strong dominating set (SDS) of an interval graph using an algorithm[9]. Input : Interval family 1 2{ , ,....., }nI I I I . Output : Strong dominating set of an interval graph of a given interval family. 11 : [1]Step S nbd . 1 12 : S = The set of vertices in S which are adjacent to all other vertices in S .Step 3 : D The largest highest degree interval in S.stStep  4 : LI The largest interval in DstStep  5 : If N ( ) existssdStep LI 5.1 : a = M(N ( ))sdStep LI .  5.2 : b The largest highest degree interval in nbd a .Step  5.3 : D { }st stStep D b  goto step 4. end if else 6 : Find NI(LI)Step 6.1: If NI(LI) null goto step 7Step . 26.2 : S [ ( )]Step nbd NI LI . 36.3 : S The set of all neighbors of ( ) which are greaterthan or equalto ( ).Step NI LI NI LI 4 3 36.4 : S The set of all vertices in S which are adjacent to all vertices in S .Step  46.5 : c = The largest highest degree interval in S .Step 6.6 : D { }st stStep D c  goto step 4. 7 : End.Step 2.2.To find a Non-split Strong dominating set (NSSDS) of an interval graph using an algorithm. Input : Interval family I= {I1,I2,I3,-------------In} . Output : Whether a strong dominating set is a non split strong dominating set or not. Step1 : S1=nbd[1] Step2 : S=The set of vertices in S1 which are adjacent to all other vertices in S1. Step3 : Dst=The largest highest degree interval in S . Step4 : LI=The largest interval in Dst Step5 : If Wsd (LI) exists Step 5.1 : a = M(Nsd(LI)) Step 5.2 : b=The largest highest degree interval in nbd[a] Step 5.3 : Dst = Dst{b} go to step 4 End if Else Step 6 : Find NI(LI). Step 6.1 : If NI(LI)=null go to step 7. Step 6.2 : S2=nbd[NI(LI)] 36.3 : S The set of all neighbors of ( ) which are greater than or equalto ( ). Step NI LI NI LI  4 3 3 6.4 : S The set of all vertices in S which are adjacent to all vertices in S . Step  46.5 : c = The largest highest degree interval in S .Step 6.6 : D { }st stStep D c  goto step 4. Step 7 : V={1, 2,3,------------,n} Step 8 : |Dst|=k Step 9 : SN={V-Dst}={S1,S2,S3,-----------,Sk}, k1≤ n-k
  • 3. To find a non-split strong dominating set of an interval graph using an algorithm www.iosrjournals.org 7 | Page Step 10 : for (i = 1 to k1-1) { For ( j = i+1 to k1 ) { If (Si,Sj)E of G then plot Si to Sj } } The induced sub graph G1=V-Dst is obtained Step11 : If W(G1)=1 Dst is non split strong dominating set Else Dst is split strong dominating set End. III. Main Theorems Theroem 1 : Let G be an interval graph corresponding to an interval family I={I1,I2,I3,------.In}. If i and j are any two intervals in I such that iDst is minimum strong dominating set of the given interval graph G, j≠1 and j is contained in i and if there is at least one interval to the left of j that intersects j and at least one interval k≠ i to the right of j that intersects j then Dst is a non split strong domination. Proof : Let G be an interval graph corresponding to an interval family I = {I1,I2,I3,------In}. Let i and j be any two intervals in I such that i Dst ,where Dst is a minimum strong dominating set of the given interval graph G, j ≠1 and j is contained in i and suppose there is at least one interval to the left of j that intersects j and at least one interval k ≠ i to the right of j that intersects j.Then it is obviously we know that j is adjacent to k in the induced subgraph <V-Dst>.Then there will be a connection in <V-Dst> to its left. Interval family I As follows an algorithm with illustration for neighbours as given interval family I. We construct an interval graph G from interval family I={1,2,3,--------10} as follows nbd[1]={1,2,3}, nbd[2]={1,2,3,4}, nbd[3]={1,2,3,4,6}, nbd [4]={2,3,4,5,6}, nbd [5]={4,5,6,7}, nbd[6]={3,4,5,6,7,9}, nbd[7]={5,6,7,8,9}, nbd[8]={7,8,9,10}, nbd [9]={6,7,8,9,10}, nbd[10]={8,9,10}. Nsd(1)={2,3}, Nsd(2)={3,4}, Nsd(3)={6}, Nsd(4)=6, Nsd(5)={6}, Nsd(6)=null, Nsd(7)=null, Nsd(8)={9}, Nsd(9)=null, Nsd(10)=null. NI(1)=4, NI(2)=5, NI(3)=5, NI(4)=7, NI(5)=8, NI(6)=8, NI(7)=10, NI(8)=null, NI(9)=null, NI(10)=null. Procedure for finding a non-split strong dominating set of an interval graph using an algorithm. Step 1: S1={1,2,3}. Step 2: S={1,2,3}. Step 3 : Dst={3}. Step 4 : LI=3. Step 5 : Nsd(3)={6}. Step 5.1 : a=M(Nsd(3))=M({6})=6. Step 5.2 : b=6. Step 5.3 : Dst={3}{6}={3,6} Step 6 : LI=6. Step 7 : NI(6)=8 Step7.1: S2=nbd[8]={7,8,9,10}. Step7.2: S3={8,9,10}. Step7.3: S4={8,9,10} Step7.4:c=9. Step7.5 : Dst= Dst{9}={3,6}{9}={3,6,9}. Step 8 : V={1,2,3,--------10} 1 4 7 10 2 6 8 953
  • 4. To find a non-split strong dominating set of an interval graph using an algorithm www.iosrjournals.org 8 | Page Step 9 : |Dst|=3 Step10 : SN={1,2,3,4,5,6,8,10} Step11 : for i=1, j=2, (1,2)E, plot 1 to 2 for i = 2 , j =3, (2,3)E, plot 2 to 3 for i = 3, j = 4, (4,5)E, plot 4 to 5 j = 5, (4,6)E, plot4 to 6 for i = 4, j = 5, (5,6)E, plot 5 to 6 j = 6, (5,7)E, plot 5 to 7 for i = 5, j=6, (6,7)E, plot 6 to7 for i = 6, j = 7, (7,8)E, plot 7 to 8 for i =7, j = 8, (8,10)E, plot 8 to 10 The induced sub graph G1=<V-Dst> is obtained. Step12 : W(G1)=1 Therefore Dst is the non split dominating set . Step13: End . Out put : {3,6,9} is a non split strong dominating set . Theorem 2 : If i and j are two intervals in I such that iDst where Dst is a minimum dominating set of G, j=1 and j is contained in i and if there is one more interval other than i that intersects j then non-split strong domination occurs in G. Proof : Let I = {I1,I2,I3,I4,------,In} be an interval family. Let j=1 be the interval contained in i where iDst, where Dst is the minimum strong dominating set of G. Suppose k is an interval , k≠i and k intersect j. Since iDst , the induced subgraph <V-Dst> does not contain i. Further in <V-Dst>, the vertex j is adjacent to the vertex k and hence there will not be any disconnection in <V-Dst> . Therefore we get non split strong domination in G .In this connection as follows an algorithm . Interval family I As follows an algorithm with illustration for neighbours as given interval family I. We construct an interval graph G from interval family I={1,2,3,--------10} as follows nbd[1]={1,2,3}, nbd[2]={1,2,3,4}, nbd[3]={1,2,3,4,6}, nbd [4]={2,3,4,6,7}, nbd [5]={5,6,7}, nbd[6]={3,4,5,6,7,8}, nbd[7]={4,5,6,7,8,9}, nbd[8]={6,7,8,9,10}, nbd [9]={ 7,8,9,10}, nbd[10]={8,9,10}. Nsd(1)={2,3}, Nsd(2) ={3,4}, Nsd(3) = {4}, Nsd(4) ={7}, Nsd(5) ={7}, Nsd(6)= {7}, Nsd(7)= null, Nsd(8)= null Nsd(9)=null, Nsd(10)=null. NI(1)=4, NI(2)=5, NI(3)=5, NI(4)=5, NI(5)=8, NI(6)=9, NI(7)=10, NI(8)=null, NI(9)=null, NI(10)=null. Procedure for finding a non-split strong dominating set of an interval graph using an algorithm. Step 1 : S1={1,2,3} Step 2 : S={1,2,3} Step 3 : Dst=3 Step 4 : LI=3 Step 5 : Nsd(3)=6 Step 6 : a=6 Step 7 : b=7 Step 8 : Dst={3}{7}={3,7} Step 9 : LI=7 Step10 : NI(7)=10 Step10.1: S2={8,9,10} Step10.2 : S3={10} Step10.3 : S4={10} Step10.4 : b=10 Step10.5 : Dst ={3,7,9} Step11 : V={1,2,3,--------10} Step12 : |Dst|=3 Step13 : SN={1,2,4,5,6,8,9} 92 1 3 4 5 6 8 7 10
  • 5. To find a non-split strong dominating set of an interval graph using an algorithm www.iosrjournals.org 9 | Page Step14 : for i=1, j=2 ,(1,2)E , plot 1 to 2 for i = 2, j = 3, (2,4)E, plot 2 to 4 for i = 3, j = 4, (4,5)E, plot 4 to 5 for i = 4, j = 5, (5,6)E, plot 5 to 6 for i = 5, j =6, (6,8)E, plot 6 to 8 for i = 6,j =7, (8,9)E, plot 8 to 9 The induced subgraph G1 = <V-Dst > is obtained . Step15 : W(G1)=1. Therefore Dst is the non split strong dominating set. Step16: End Output : {3,7,10} is a non split strong dominating set . Theorem 3 : Let Dst be a strong dominating set which is obtained by algorithm SDS. If i, j, k are three consecutive intervals such that i < j< k and jDst, i intersects j, j intersect k and i interest k then non split strong domination occurs in G . Proof : Suppose I = {I1,I2,I3,------In} be an interval family . Let i, j, k be three consecutive intervals satisfying the hypothesis. Now i and k intersect implies that i and k are adjacent induced sub graph < VDst > an algorithm as follows . Interval family I As follows an algorithm with illustration for neighbours as given interval family I. We construct an interval graph G from interval family I={1,2,3,--------10} as follows nbd[1]={1,2,3}, nbd[2]={1,2,3,4}, nbd[3]={1,2,3,4,5}, nbd [4]={2,3,4,5,6}, nbd [5]={3,4,5,6,7}, nbd[6]={4,5,6,7,8}, nbd[7]={5,6,7,8,9}, nbd[8]={6,7,8,9}, nbd [9]={7,8,9,10}, nbd[10]={9,10}. Nsd(1)={2,3}, Nsd(2)={3,4}, Nsd(3)=null, Nsd(4)=null, Nsd(5)=null, Nsd(6)=null, Nsd(7)=null, Nsd(8)=null, Nsd(9)=null, Nsd(10)=null. NI(1) = 4, NI(2) = 5, NI(3) = 6, NI(4) = 7, NI(5) = 8, NI(6) = 9, NI(7)=10, NI(8)=10, NI(9) = null, NI(10) = null. Procedure for finding a non-split strong dominating set of an interval graph using an algorithm. Step 1 : S1={1,2,3} Step 2 : S={1,2,3} Step 3 : Dst=3 Step 4 : LI=3 Step 5 : NI(3)=6 Step 6 : Nbd[6]={4,5,6,7,8} Step 6.1: S3 = {6,7,8} Step 6.2 : S3 = {6,7,8} Step 6.3 : S4 = {6,7,8} Step 6.4 : c=8 Step 6.5 : Dst ={3,8} Step 7 : LI=8 Step 8 : NI(8)=null Step 9 : V={1,2,3,--------10} Step10 : |Dst|=2 Step11: SN={1,2,4,5,6, 9,10} Step12 : for i=1, j=2 ,(1,2)E, plot 1 to 2 for i=2, j=3, (2,4)E , plot 2 to 4 for i=3, j=4, (4,5)E, plot 4 to 5 j=5, (4,6)E, plot 4 to 6 for i=4, j=5, (5,6)E, plot 5 to 6 j=6, (5,7)E, plot 5 to 7 1 2 3 4 5 6 7 8 9 10
  • 6. To find a non-split strong dominating set of an interval graph using an algorithm www.iosrjournals.org 10 | Page for i=5, j=6, (6,7)E, plot 6 to 7 for i=6,j=7, (7,9)E, plot 7 to 9 The induced sub graph G1 is obtained . Step13:W(G1)=1 Therefore Dst is the non split strong dominating set. Step14: End Output: {3,8} is a non split strong dominating set . IV. Conclusions We studied the non-split strong domination in interval graphs. In this paper we discussed a verification method algorithm for finding a non-split strong dominating set of an interval graph. Acknowledgements The authors would like to express their gratitude of the anonymous referees for their suggestions and inspiring comments on this paper References [1]. T. W. Haynes, S.T. Hedetniemi and P.J.Slater, Fundamentals of domination in graphs, Marcel Dekker, Inc., New York (1998). [2]. T. W. Haynes, S.T. Hedetniemi and P.J.Slater, Domination in Graphs: advanced topics , Marcel Dekker, Inc., New York (1998). [3]. Hedetniemi, S. T, Laskar, R. C. , Bibliography on domination in graphs and some basic definitions of domination parameters, Discrete Mathematics 86 (1–3), (1990), 257–277. [4]. Sampathkumar, E., and Pushpa Latha, Strong weak domination and domination balance in graph, Discrete Math. Vol. 161, 1996, p. 235-242. [5]. Domke et.al, On parameters related to strong and weak domination in graphs, Discrete Math. Vol. 258, (2002) p. ,1-11. [6]. Hattingh J.H., Henning M.A., On strong domination in Graphs, J. Combin. Math. Combin. Comput. Vol.26, (1998) p. 73-92. [7]. Rautenbach, D., Bounds on the strong domination number, Discrete Math. Vol. 215, (2000) p. 201-212. [8]. Kulli, V. R. and Janakiram, B., The Non-Split domination number of graph, International Journal of management and systems. Vol.19. No.2, p. 145-156, 2000. [9]. Maheswari, B., Nagamuni Reddy, L., and A. Sudhakaraiah , Split and Non-split dominating set of circular-arc graphs, J. curr. Sci Vol 3. No.2, (2003)p. 369-372 . [10]. Dr. A. Sudhakaraiah, V. Rama Latha, E. Gnana Deepika and T.Venkateswarulu, To Find Strong Dominating Set and Split Strong Dominating Set of an Interval Graph Using an Algorithm, IJSER , Vol. 2,(2012), 1026-1034.