Search

Given a graph $G$ with a terminal set $R \subseteq V(G)$, the Steiner tree problem (STREE) asks for a set $S\subseteq V(G) \setminus R$ such that the graph induced on $S\cup R$ is connected. A split graph is a graph which can be partitioned into a clique and an independent set. It is known that STREE is NP-complete on split graphs \cite{white1985steiner}. To strengthen this result, we introduce convex ordering on one of the partitions (clique or independent set), and prove that STREE is polynomial-time solvable for tree-convex split graphs with convexity on clique ($K$), whereas STREE is NP-complete on tree-convex split graphs with convexity on independent set ($I$). We further strengthen our NP-complete result by establishing a dichotomy which says that for unary-tree-convex split graphs (path-convex split graphs), STREE is polynomial-time solvable, and NP-complete for binary-tree-convex split graphs (comb-convex split graphs). We also show that STREE is polynomial-time solvable for triad-convex split graphs with convexity on $I$, and circular-convex split graphs. Further, we show that STREE can be used as a framework for the dominating set problem (DS) on split graphs, and hence the classical complexity (P vs NPC) of STREE and DS is the same for all these subclasses of split graphs. Furthermore, it is important to highlight that in \cite{CHLEBIK20081264}, it is incorrectly claimed that the problem of finding a minimum dominating set on split graphs cannot be approximated within $(1-\epsilon)\ln |V(G)|$ in polynomial-time for any $\epsilon >0$ unless NP $\subseteq$ DTIME $n^{O(\log \log n)}$. When the input is restricted to split graphs, we show that the minimum dominating set problem has $2-\frac{1}{|I|}$-approximation algorithm that runs in polynomial time.

The class of $k$-star caterpillar convex bipartite graphs generalizes the class of convex bipartite graphs. For a bipartite graph with partitions $X$ and $Y$, we associate a $k$-star caterpillar on $X$ such that for each vertex in $Y$, its neighborhood induces a tree. The $k$-star caterpillar on $X$ is imaginary and if the imaginary structure is a path ($0$-star caterpillar), then it is the class of convex bipartite graphs. The minimum Steiner tree problem (STREE) is defined as follows: given a connected graph $G=(V,E)$ and a subset of vertices $R \subseteq V(G)$, the objective is to find a minimum cardinality set $S \subseteq V(G)$ such that the set $R \cup S$ induces a connected subgraph. STREE is known to be NP-complete on general graphs as well as for special graph classes such as chordal graphs, bipartite graphs, and chordal bipartite graphs. The complexity of STREE in convex bipartite graphs, which is a popular subclass of chordal bipartite graphs, is open. In this paper, we introduce $k$-star caterpillar convex bipartite graphs, and show that STREE is NP-complete for $1$-star caterpillar convex bipartite graphs and polynomial-time solvable for $0$-star caterpillar convex bipartite graphs (also known as convex bipartite graphs). In \cite{muller1987np}, it is shown that STREE in chordal bipartite graphs is NP-complete. A close look at the reduction instances reveal that the instances are $3$-star caterpillar convex bipartite graphs, and in this paper, we strengthen the result of \cite{muller1987np}., Comment: 19 pages, 10 figures, 1 table

A bipartite graph is chordal bipartite if every cycle of length at least six has a chord in it. M$\ddot{\rm u}$ller \cite {muller1996Hamiltonian} has shown that the Hamiltonian cycle problem is NP-complete on chordal bipartite graphs by presenting a polynomial-time reduction from the satisfiability problem. The microscopic view of the reduction instances reveals that the instances are $P_9$-free chordal bipartite graphs, and hence the status of Hamiltonicity in $P_8$-free chordal bipartite graphs is open. In this paper, we identify the first non-trivial subclass of $P_8$-free chordal bipartite graphs which is $P_5$-free chordal bipartite graphs, and present structural and algorithmic results on $P_5$-free chordal bipartite graphs. We investigate the structure of $P_5$-free chordal bipartite graphs and show that these graphs have a {\em Nested Neighborhood Ordering (NNO)}, a special ordering among its vertices. Further, using this ordering, we present polynomial-time algorithms for classical problems such as the Hamiltonian cycle (path), also the variants and generalizations of the Hamiltonian cycle (path) problem. We also obtain polynomial-time algorithms for treewidth (pathwidth), and minimum fill-in in $P_5$-free chordal bipartite graph. We also present some results on complement graphs of $P_5$-free chordal bipartite graphs., Comment: 23 pages, 8 figures

For a connected graph, the Hamiltonian cycle (path) is a simple cycle (path) that spans all the vertices in the graph. It is known from \cite{muller,garey} that HAMILTONIAN CYCLE (PATH) are NP-complete in general graphs and chordal bipartite graphs. A convex bipartite graph $G$ with bipartition $(X,Y)$ and an ordering $X=(x_1,\ldots,x_n)$, is a bipartite graph such that for each $y \in Y$, the neighborhood of $y$ in $X$ appears consecutively. $G$ is said to have convexity with respect to $X$. Further, convex bipartite graphs are a subclass of chordal bipartite graphs. In this paper, we present a necessary and sufficient condition for the existence of a Hamiltonian cycle in convex bipartite graphs and further we obtain a linear-time algorithm for this graph class. We also show that Chvatal's necessary condition is sufficient for convex bipartite graphs. The closely related problem is HAMILTONIAN PATH whose complexity is open in convex bipartite graphs. We classify the class of convex bipartite graphs as {\em monotone} and {\em non-monotone} graphs. For monotone convex bipartite graphs, we present a linear-time algorithm to output a Hamiltonian path. We believe that these results can be used to obtain algorithms for Hamiltonian path problem in non-monotone convex bipartite graphs. It is important to highlight (a) in \cite{keil,esha}, it is incorrectly claimed that Hamiltonian path problem in convex bipartite graphs is polynomial-time solvable by referring to \cite{muller} which actually discusses Hamiltonian cycle (b) the algorithm appeared in \cite{esha} for the longest path problem (Hamiltonian path problem) in biconvex and convex bipartite graphs have an error and it does not compute an optimum solution always. We present an infinite set of counterexamples in support of our claim.

The family of graphs that can be constructed from isolated vertices by disjoint union and graph join operations are called cographs. These graphs can be represented in a tree-like representation termed parse tree or cotree. In this paper, we study some popular combinatorial problems restricted to cographs. We first present a structural characterization of minimal vertex separators in cographs. Further, we show that listing all minimal vertex separators and the complexity of some constrained vertex separators are polynomial-time solvable in cographs. We propose polynomial-time algorithms for connectivity augmentation problems and its variants in cographs, preserving the cograph property. Finally, using the dynamic programming paradigm, we present a generic framework to solve classical optimization problems such as the longest path, the Steiner path and the minimum leaf spanning tree problems restricted to cographs, our framework yields polynomial-time algorithms for all three problems., Comment: 21 pages, 4 figures

In this paper, we investigate Hamiltonian path problem in the context of split graphs, and produce a dichotomy result on the complexity of the problem. Our main result is a deep investigation of the structure of $K_{1,4}$-free split graphs in the context of Hamiltonian path problem, and as a consequence, we obtain a polynomial-time algorithm to the Hamiltonian path problem in $K_{1,4}$-free split graphs. We close this paper with the hardness result: we show that, unless P=NP, Hamiltonian path problem is NP-complete in $K_{1,5}$-free split graphs by reducing from Hamiltonian cycle problem in $K_{1,5}$-free split graphs. Thus this paper establishes a "thin complexity line" separating NP-complete instances and polynomial-time solvable instances., Comment: 39 pages, 4 figures, CALDAM 2018

A bipartite graph is chordal bipartite if every cycle of length at least 6 has a chord in it. In this paper, we investigate the structure of $P_5$-free chordal bipartite graphs and show that these graphs have a Nested Neighborhood Ordering, a special ordering among its vertices. Further, using this ordering, we present polynomial-time algorithms for classical problems such as Hamiltonian cycle (path) and longest path. Two variants of Hamiltonian path include Steiner path and minimum leaf spanning tree, and we obtain polynomial-time algorithms for these problems as well restricted to $P_5$-free chordal bipartite graphs., Comment: Presented in ICMCE 2017

The focus of this paper is two fold. Firstly, we present a logical approach to graph modification problems such as minimum node deletion, edge deletion, edge augmentation problems by expressing them as an expression in first order (FO) logic. As a consequence, it follows that these problems have constant factor polynomial-time approximation algorithms. In particular, node deletion/edge deletion on a graph $G$ whose resultant is cograph, split, threshold, comparable, interval and permutation are $O(1)$ approximable. Secondly, we present a monadic second order (MSO) logic to minimum graph modification problems, minimum dominating set problem and minimum coloring problem and their variants. As a consequence, it follows that these problems have linear-time algorithms on bounded tree-width graphs. In particular, we show the existance of linear-time algorithms on bounded tree-width graphs for star coloring, cd-coloring, rainbow coloring, equitable coloring, total dominating set, connected dominating set. In a nut shell, this paper presents a unified framework and an algorithmic scheme through logical expressions for some graph problems through FO and MSO.

In this paper, we investigate the well-studied Hamiltonian cycle problem (HCYCLE), and present an interesting dichotomy result on split graphs. T. Akiyama et al. (1980) have shown that HCYCLE is NP-complete in planar bipartite graphs with maximum degree $3$. Using this reduction, we show that HCYCLE is NP-complete in split graphs. In particular, we show that the problem is NP-complete in $K_{1,5}$-free split graphs. Further, we present polynomial-time algorithms for Hamiltonian cycle in $K_{1,3}$-free and $K_{1,4}$-free split graphs. We believe that the structural results presented in this paper can be used to show similar dichotomy result for Hamiltonian path problem (HPATH) and other variants of HCYCLE., Comment: 18 pages

\emph{Strictly Chordality-$k$ graphs ($SC_k$)} are graphs which are either cycle-free or every induced cycle is of length exactly $k, k \geq 3$. Strictly chordality-3 and strictly chordality-4 graphs are well known chordal and chordal bipartite graphs, respectively. For $k\geq 5$, the study has been recently initiated in \cite{sadagopan} and various structural and algorithmic results are reported. In this paper, we show that maximum independent set (MIS), minimum vertex cover, minimum dominating set, feedback vertex set (FVS), odd cycle transversal (OCT), even cycle transversal (ECT) and Steiner tree problem are polynomial time solvable on $SC_k$ graphs, $k\geq 5$. We next consider $2K_2$-free graphs and show that FVS, OCT, ECT, Steiner tree problem are polynomial time solvable on subclasses of $2K_2$-free graphs., Comment: 15 pages, 3 figures, submitted to CALDAM 2017. arXiv admin note: text overlap with arXiv:1602.03802

A \emph{vertex separator} of a connected graph $G$ is a set of vertices removing which will result in two or more connected components and a \emph{minimum vertex separator} is a set which contains the minimum number of such vertices, i.e., the cardinality of this set is least among all possible vertex separator sets. The cardinality of the minimum vertex separator refers to the connectivity of the graph G. A connected graph is said to be $k-connected$ if removing exactly $k$ vertices, $ k\geq 1$, from the graph, will result in two or more connected components and on removing any $(k-1)$ vertices, the graph is still connected. A \emph{connectivity augmentation} set is a set of edges which when augmented to a $k$-connected graph $G$ will increase the connectivity of $G$ by $r$, $r \geq 1$, making the graph $(k+r)$-$connected$ and a \emph{minimum connectivity augmentation} set is such a set which contains a minimum number of edges required to increase the connectivity by $r$. In this paper, we shall investigate a $r$-$connectivity$ augmentation in trees, $r \geq 2$. As part of lower bound study, we show that any minimum $r$-connectivity augmentation set in trees requires at least $ \lceil\frac{1}{2} \sum\limits_{i=1}^{r-1} (r-i) \times l_{i} \rceil $ edges, where $l_i$ is the number of vertices with degree $i$. Further, we shall present an algorithm that will augment a minimum number of edges to make a tree $(k+r)$-connected., Comment: 5 figures, 3 algorithms, presented in RMS 31st Annual Conference

A spanning tree of a graph $G$ is a connected acyclic spanning subgraph of $G$. We consider enumeration of spanning trees when $G$ is a $2$-tree, meaning that $G$ is obtained from one edge by iteratively adding a vertex whose neighborhood consists of two adjacent vertices. We use this construction order both to inductively list the spanning trees without repetition and to give bounds on the number of them. We determine the $n$-vertex $2$-trees having the most and the fewest spanning trees. The $2$-tree with the fewest is unique; it has $n-2$ vertices of degree $2$ and has $n2^{n-3}$ spanning trees. Those with the most are all those having exactly two vertices of degree $2$, and their number of spanning trees is the Fibonacci number $F_{2n-2}$., Comment: 10 Pages, 4 Figures

Strictly Chordality-k graphs (SC_k graphs) are graphs which are either cycle free or every induced cycle is exactly k, for some fixed k, k \geq 3. Note that k = 3 and k = 4 are precisely the Chordal graphs and Chordal Bipartite graphs, respectively. In this paper, we initiate a structural and an algorithmic study of SCk, k \geq 5 graphs., Comment: 25 pages, 11 figures, 2 tables, 3 algorithms, In revision in Discrete Applied Mathematics

A connected graph is 2K2-free if it does not contain a pair of independent edges as an induced subgraph. In this paper, we present the structural characterization of minimal vertex separator and show that there are polynomial number of minimal vertex separators in 2K2-free graphs. Further, using the enumeration we show that finding minimum connected vertex separator in 2K2-free graphs is polynomial time solvable. We highlight that finding minimum connected vertex separator is NP-complete in Chordality 5 graphs, which is a super graph class of 2K2-free graphs. Other study includes, enumeration of all distinct maximal independent sets and testing 2K2-free graphs. Also, we present an polynomial time algorithm for feedback vertex set problem in the subclass of 2K2-free graphs., Comment: 15 pages, 5 figures, 4 algorithms, Presented in ICMCE 2015

For a connected graph, a {\em minimum vertex separator} is a minimum set of vertices whose removal creates at least two connected components. The vertex connectivity of the graph refers to the size of the minimum vertex separator and a graph is $k$-vertex connected if its vertex connectivity is $k$, $k\geq 1$. Given a $k$-vertex connected graph $G$, the combinatorial problem {\em vertex connectivity augmentation} asks for a minimum number of edges whose augmentation to $G$ makes the resulting graph $(k+1)$-vertex connected. In this paper, we initiate the study of $r$-vertex connectivity augmentation whose objective is to find a $(k+r)$-vertex connected graph by augmenting a minimum number of edges to a $k$-vertex connected graph, $r \geq 1$. We shall investigate this question for the special case when $G$ is a tree and $r=2$. In particular, we present a polynomial-time algorithm to find a minimum set of edges whose augmentation to a tree makes it 3-vertex connected. Using lower bound arguments, we show that any tri-vertex connectivity augmentation of trees requires at least $\lceil \frac {2l_1+l_2}{2} \rceil$ edges, where $l_1$ and $l_2$ denote the number of degree one vertices and degree two vertices, respectively. Further, we establish that our algorithm indeed augments this number, thus yielding an optimum algorithm., Comment: 10 pages, 2 figures, 3 algorithms, Presented in ICGTA 2015

For a connected graph, a path containing all vertices is known as \emph{Hamiltonian path}. For general graphs, there is no known necessary and sufficient condition for the existence of Hamiltonian paths and the complexity of finding a Hamiltonian path in general graphs is NP-Complete. We present a necessary and sufficient condition for the existence of Hamiltonian paths in 2-trees. Using our characterization, we also present a linear-time algorithm for the existence of Hamiltonian paths in 2-trees. Our characterization is based on a deep understanding of the structure of 2-trees and the combinatorics presented here may be used in other combinatorial problems restricted to 2-trees., Comment: 16 pages, 7 figures

For a connected labelled graph $G$, a {\em spanning tree} $T$ is a connected and an acyclic subgraph that spans all vertices of $G$. In this paper, we consider a classical combinatorial problem which is to list all spanning trees of $G$. A Halin graph is a graph obtained from a tree with no degree two vertices and by joining all leaves with a cycle. We present a sequential and parallel algorithm to enumerate all spanning trees in Halin graphs. Our approach enumerates without repetitions and we make use of $O((2pd)^{p})$ processors for parallel algorithmics, where $d$ and $p$ are the depth, the number of leaves, respectively, of the Halin graph. We also prove that the number of spanning trees in Halin graphs is $O((2pd)^{p})$., Comment: 13 pages, 5 figures

Given a connected graph $G$ and a terminal set $R \subseteq V(G)$, {\em Steiner tree} asks for a tree that includes all of $R$ with at most $r$ edges for some integer $r \geq 0$. It is known from [ND12,Garey et. al \cite{steinernpc}] that Steiner tree is NP-complete in general graphs. {\em Split graph} is a graph which can be partitioned into a clique and an independent set. K. White et. al \cite{white} has established that Steiner tree in split graphs is NP-complete. In this paper, we present an interesting dichotomy: we show that Steiner tree on $K_{1,4}$-free split graphs is polynomial-time solvable, whereas, Steiner tree on $K_{1,5}$-free split graphs is NP-complete. We investigate $K_{1,4}$-free and $K_{1,3}$-free (also known as claw-free) split graphs from a structural perspective. Further, using our structural study, we present polynomial-time algorithms for Steiner tree in $K_{1,4}$-free and $K_{1,3}$-free split graphs. Although, polynomial-time solvability of $K_{1,3}$-free split graphs is implied from $K_{1,4}$-free split graphs, we wish to highlight our structural observations on $K_{1,3}$-free split graphs which may be used in other combinatorial problems., Comment: 12 pages, 2 figures, CALDAM 2016

Let $T$ be a tree with no degree 2 vertices and $L(T)=\{l_1,\ldots,l_r\}, r \geq 2$ denote the set of leaves in $T$. An Halin graph $G$ is a graph obtained from $T$ such that $V(G)=V(T)$ and $E(G)=E(T) \cup \{\{l_i,l_{i+1}\} ~|~ 1 \leq i \leq r-1\} \cup \{l_1,l_r\}$. In this paper, we investigate combinatorial problems such as, testing whether a given graph is Halin or not, chromatic bounds, an algorithm to color Halin graphs with the minimum number of colors. Further, we present polynomial-time algorithms for testing and coloring problems.

For a connected graph, a vertex separator is a set of vertices whose removal creates at least two components. A vertex separator $S$ is minimal if it contains no other separator as a strict subset and a minimum vertex separator is a minimal vertex separator of least cardinality. A {\em clique} is a set of mutually adjacent vertices. A 2-tree is a connected graph in which every maximal clique is of size three and every minimal vertex separator is of size two. A spanning tree of a graph $G$ is a connected and an acyclic subgraph of $G$. In this paper, we focus our attention on two enumeration problems, both from sequential and parallel perspective. In particular, we consider listing all possible spanning trees of a 2-tree and listing all perfect elimination orderings of a chordal graph. As far as enumeration of spanning trees is concerned, our approach is incremental in nature and towards this end, we work with the construction order of the 2-tree, i.e. enumeration of $n$-vertex trees are from $n-1$ vertex trees, $n \geq 4$. Further, we also present a parallel algorithm for spanning tree enumeration using $O(2^n)$ processors. To our knowledge, this paper makes the first attempt in designing a parallel algorithm for this problem. We conclude this paper by presenting a sequential and parallel algorithm for enumerating all Perfect Elimination Orderings of a chordal graph., Comment: 9 pages, 2 figures

A graph is unichord free if it does not contain a cycle with exactly one chord as its subgraph. In [3], it is shown that a graph is unichord free if and only if every minimal vertex separator is a stable set. In this paper, we first show that such a graph can be recognized in polynomial time. Further, we show that the chromatic number of unichord free graphs is one of (2,3, \omega(G)). We also present a polynomial-time algorithm to produce a coloring with \omega(G) colors., Comment: This paper has been withdrawn due to a bug in the algorithm

For a connected graph, a vertex separator is a set of vertices whose removal creates at least two components and a minimum vertex separator is a vertex separator of least cardinality. The vertex connectivity refers to the size of a minimum vertex separator. For a connected graph $G$ with vertex connectivity $k (k \geq 1)$, the connectivity augmentation refers to a set $S$ of edges whose augmentation to $G$ increases its vertex connectivity by one. A minimum connectivity augmentation of $G$ is the one in which $S$ is minimum. In this paper, we focus our attention on connectivity augmentation of trees. Towards this end, we present a new sequential algorithm for biconnectivity augmentation in trees by simplifying the algorithm reported in \cite{nsn}. The simplicity is achieved with the help of edge contraction tool. This tool helps us in getting a recursive subproblem preserving all connectivity information. Subsequently, we present a parallel algorithm to obtain a minimum connectivity augmentation set in trees. Our parallel algorithm essentially follows the overall structure of sequential algorithm. Our implementation is based on CREW PRAM model with $O(\Delta)$ processors, where $\Delta$ refers to the maximum degree of a tree. We also show that our parallel algorithm is optimal whose processor-time product is O(n) where $n$ is the number of vertices of a tree, which is an improvement over the parallel algorithm reported in \cite{hsu}.

In this paper, we revisit the classical data compression problem for domain specific texts. It is well-known that classical Huffman algorithm is optimal with respect to prefix encoding and the compression is done at character level. Since many data transfer are domain specific, for example, downloading of lecture notes, web-blogs, etc., it is natural to think of data compression in larger dimensions (i.e. word level rather than character level). Our framework employs a two-level compression scheme in which the first level identifies frequent patterns in the text using classical frequent pattern algorithms. The identified patterns are replaced with special strings and to acheive a better compression ratio the length of a special string is ensured to be shorter than the length of the corresponding pattern. After this transformation, on the resultant text, we employ classical Huffman data compression algorithm. In short, in the first level compression is done at word level and in the second level it is at character level. Interestingly, this two level compression technique for domain specific text outperforms classical Huffman technique. To support our claim, we have presented both theoretical and simulation results for domain specific texts.

Search pattern experienced by the processor to search an element in secondary storage devices follows a random sequence. Formally, it is a random walk and its modeling is crucial in studying performance metrics like memory access time. In this paper, we first model the random walk using extended Fibonacci series. Our simulation is done on a parallel computing model (PRAM) with EREW strategy. Three search primitives are proposed under parallel computing model and each primitive is thoroughly tested on an array of size $10^7$ with the size of random walk being $10^4$. Our findings reveal that search primitive with pointer jumping is better than the other two primitives. Our key contribution lies in modeling random walk as an extended Fibonacci series generator and simulating the same with various search primitives., Comment: 7 pages, 5 figures This paper has been withdrawn by the author due to an error in the simulation

Characterization of k-chordal graphs based on the existence of a "simplicial path" was shown in [Chv{\'a}tal et al. Note: Dirac-type characterizations of graphs without long chordless cycles. Discrete Mathematics, 256, 445-448, 2002]. We give a characterization of k-chordal graphs which is a generalization of the known characterization of chordal graphs due to [G. A. Dirac. On rigid circuit graphs. Abh. Math. Sem. Univ. Hamburg, 25, 71-76, 1961] that use notions of a "simplicial vertex" and a "simplicial ordering"., Comment: 3 pages

We show that minimum connected $(s,t)$-vertex separator ($(s,t)$-CVS) is $\Omega(log^{2-\epsilon}n)$-hard for any $\epsilon >0$ unless NP has quasi-polynomial Las-Vegas algorithms. i.e., for any $\epsilon >0$ and for some $\delta >0$, $(s,t)$-CVS is unlikely to have $\delta.log^{2-\epsilon}n$-approximation algorithm. We show that $(s,t)$-CVS is NP-complete on graphs with chordality at least 5 and present a polynomial-time algorithm for $(s,t)$-CVS on bipartite chordality 4 graphs. We also present a $\lceil\frac{c}{2}\rceil$-approximation algorithm for $(s,t)$-CVS on graphs with chordality $c$. Finally, from the parameterized setting, we show that $(s,t)$-CVS parameterized above the $(s,t)$-vertex connectivity is $W[2]$-hard.

In this paper, our goal is to characterize two graph classes based on the properties of minimal vertex (edge) separators. We first present a structural characterization of graphs in which every minimal vertex separator is a stable set. We show that such graphs are precisely those in which the induced subgraph, namely, a cycle with exactly one chord is forbidden. We also show that deciding maximum such forbidden subgraph is NP-complete by establishing a polynomial time reduction from maximum induced cycle problem [1]. This result is of independent interest and can be used in other combinatorial problems. Secondly, we prove that a graph has the following property: every minimal edge separator induces a matching (that is no two edges share a vertex in common) if and only if it is a tree.

Contraction of an edge merges its end points into a new vertex which is adjacent to each neighbor of the end points of the edge. An edge in a $k$-connected graph is {\em contractible} if its contraction does not result in a graph of lower connectivity. We characterize contractible edges in chordal graphs using properties of tree decompositions with respect to minimal vertex separators.