Results 1  10
of
195
Network Coding in Undirected Networks
, 2004
"... Recent work in network coding shows that, it is necessary to consider both the routing and coding strategies to achieve optimal throughput of information transmission in data networks. So far, most research on network coding has focused on the model of directed networks, where each communication li ..."
Abstract

Cited by 83 (18 self)
 Add to MetaCart
Recent work in network coding shows that, it is necessary to consider both the routing and coding strategies to achieve optimal throughput of information transmission in data networks. So far, most research on network coding has focused on the model of directed networks, where each communication link has a fixed direction. In this paper, we study the benefits of network coding in undirected networks, where each communication link is bidirectional. Our theoretical results show that, for a single unicast or broadcast session, there are no improvements with respect to throughput due to network coding. In the case of a single multicast session, such an improvement is bounded by a factor of two, as long as half integer routing is permitted. This is dramatically different from previous results obtained in directed networks. We also show that multicast throughput in an undirected network is independent of the selection of the sender within the multicast group. We finally show that, rather than improving the optimal achievable throughput, the benefit of network coding is to significantly facilitate the design of efficient algorithms to compute and achieve such optimal throughput. I.
A DomainSpecific Visual Language for Domain Model Evolution
 Journal of Visual Languages and Computing
, 2004
"... Domainspecific visual languages (DSVLs) are concise and useful tools that allow the rapid development of the behavior and/or structure of applications in welldefined domains. These languages are typically developed specifically for a domain, and have a strong cohesion to the domain concepts, which ..."
Abstract

Cited by 54 (6 self)
 Add to MetaCart
(Show Context)
Domainspecific visual languages (DSVLs) are concise and useful tools that allow the rapid development of the behavior and/or structure of applications in welldefined domains. These languages are typically developed specifically for a domain, and have a strong cohesion to the domain concepts, which often appear as primitives in the language. The strong cohesion between DSVL language primitives and the domain is a benefit for development by domain experts, but can be a drawback when the domain evolves – even when that evolution appears insignificant. This paper presents a domainspecific visual language developed expressly for the evolution of domainspecific visual languages, and uses concepts from graphrewriting to specify and carry out the transformation of the models built using the original DSVL. 1.
Prioritized Interaction Testing for Pairwise Coverage with Seeding and Contraints
, 2006
"... ..."
(Show Context)
Properly colored subgraphs and rainbow subgraphs in edgecolorings with local constraints
 ALGORITHMS
, 2003
"... We consider a canonical Ramsey type problem. An edgecoloring of a graph is called mgood if each color appears at most m times at each vertex. Fixing a graph G and a positive integer m, let f(m, G) denote the smallest n such that every mgood edgecoloring of K n yields a properly edgecolored ..."
Abstract

Cited by 33 (1 self)
 Add to MetaCart
(Show Context)
We consider a canonical Ramsey type problem. An edgecoloring of a graph is called mgood if each color appears at most m times at each vertex. Fixing a graph G and a positive integer m, let f(m, G) denote the smallest n such that every mgood edgecoloring of K n yields a properly edgecolored copy of G, and let g(m, G) denote the smallest n such that every mgood edgecoloring of K n yields a rainbow copy of G. We give bounds on f(m, G) and g(m, G). For complete graphs G � K t, we have c 1mt 2 /ln t � f(m, K t) � c 2mt 2, and c � 1mt 3 /ln t � g(m, K t) � c � 2mt 3 /ln t, where c 1, c 2, c � 1, c � 2 are absolute constants. We also give bounds on f(m, G) and g(m, G) for general graphs G in terms of degrees in G. In particular, we show that for fixed m and d, and all sufficiently large n compared to m and d, f(m, G) � n for all graphs G with n vertices and
THE FREQUENCY SPACE OF A FREE GROUP
, 2003
"... We analyze the structure of the frequency space Q ∞ of a free group Fk consisting of all shiftinvariant Borel probability measures on ∂Fk and study the natural action of Out(Fk) on Q∞. In particular we prove that for any outer automorphism φ of Fk the conjugacy distortion spectrum of φ, consisting ..."
Abstract

Cited by 30 (15 self)
 Add to MetaCart
We analyze the structure of the frequency space Q ∞ of a free group Fk consisting of all shiftinvariant Borel probability measures on ∂Fk and study the natural action of Out(Fk) on Q∞. In particular we prove that for any outer automorphism φ of Fk the conjugacy distortion spectrum of φ, consisting of all numbers φ(w)/w, where w is a nontrivial conjugacy class, is a convex subset of Q.
A novel spectral coding in a large graph database
 In Proceedings of the International Conference on Extending Database Technology
, 2008
"... Retrieving related graphs containing a query graph from a large graph database is a key issue in many graphbased applications, such as drug discovery and structural pattern recognition. Because subgraph isomorphism is a NPcomplete problem [4], we have to employ a filterandverification framework ..."
Abstract

Cited by 30 (2 self)
 Add to MetaCart
(Show Context)
Retrieving related graphs containing a query graph from a large graph database is a key issue in many graphbased applications, such as drug discovery and structural pattern recognition. Because subgraph isomorphism is a NPcomplete problem [4], we have to employ a filterandverification framework to speed up the search efficiency, that is, using an effective and efficient pruning strategy to filter out the false positives (graphs that are not possible in the results) as many as possible first, then validating the remaining candidates by subgraph isomorphism checking. In this paper, we propose a novel filtering method, a spectral encoding method, i.e. GCoding. Specifically, we assign a signature to each vertex based on its local structures. Then, we generate a spectral graph code by combining all vertex signatures in a graph. Based on spectral graph codes, we derive a necessary condition for subgraph isomorphism. Then we propose two pruning rules for subgraph search problem, and prove that they satisfy the nofalsenegative requirement (no dismissal in answers). Since graph codes are in numerical space, we take this advantage and conduct efficient filtering over graph codes. Extensive experiments show that GCoding outperforms existing counterpart methods. 1.
A Survey of Frequent Subgraph Mining Algorithms
 THE KNOWLEDGE ENGINEERING REVIEW
, 2004
"... Graph mining is an important research area within the domain of data mining. The field of study concentrates on the identification of frequent subgraphs within graph data sets. The research goals are directed at: (i) effective mechanisms for generating candidate subgraphs (without generating duplica ..."
Abstract

Cited by 27 (1 self)
 Add to MetaCart
Graph mining is an important research area within the domain of data mining. The field of study concentrates on the identification of frequent subgraphs within graph data sets. The research goals are directed at: (i) effective mechanisms for generating candidate subgraphs (without generating duplicates) and (ii) how best to process the generated candidate subgraphs so as to identify the desired frequent subgraphs in a way that is computationally efficient and procedurally effective. This paper presents a survey of current research in the field of frequent subgraph mining, and proposed solutions to address the main research issues.
Metamodel driven model migration
 Vanderbilt University
, 2003
"... I love you, and I’m proud of you too. Thanks for being here for me. Jon iii ACKNOWLEDGEMENTS I give many thanks to my advisor, Dr. Gabor Karsai for being the Best AllAround Advisor™. Gabor, without your excellent teaching skills and motivational abilities, I would not be in the position I am today. ..."
Abstract

Cited by 24 (2 self)
 Add to MetaCart
(Show Context)
I love you, and I’m proud of you too. Thanks for being here for me. Jon iii ACKNOWLEDGEMENTS I give many thanks to my advisor, Dr. Gabor Karsai for being the Best AllAround Advisor™. Gabor, without your excellent teaching skills and motivational abilities, I would not be in the position I am today. Vanderbilt is lucky to have you, as will be any other student under your tutelage. I also thank very heartily the other members of my committee. Dr. Janos Sztipanovits, for his political insight (and vision for my future career); Dr. Akos Ledeczi, for holding my feet to the fire when it comes to sticking up for the value of my research, and also social interactions within ISIS; Dr. Greg Nordstrom, for (as usual) providing valuable comments in the discussion of all things metamodeling related, not to mention being an allaround good guy to bounce ideas allaround with; and of course Dr. Doug
Meyniel’s conjecture on the cop number: a survey
 JOURNAL OF COMBINATORICS
, 2012
"... ..."
(Show Context)
Detection and characterization of novel sequence insertions using pairedend nextgeneration sequencing
 Bioinformatics
, 2010
"... Motivation: In the past few years, human genome structural variation discovery has enjoyed increased attention from the genomics research community. Many studies were published to characterize short insertions, deletions, duplications, and inversions, and associate copy number variants (CNVs) with d ..."
Abstract

Cited by 14 (4 self)
 Add to MetaCart
(Show Context)
Motivation: In the past few years, human genome structural variation discovery has enjoyed increased attention from the genomics research community. Many studies were published to characterize short insertions, deletions, duplications, and inversions, and associate copy number variants (CNVs) with disease. Detection of new sequence insertions requires sequence data, however, the “detectable ” sequence length with readpair analysis is limited by the insert size. Thus longer sequence insertions that contribute to our genetic makeup are not extensively researched. Results: We present NovelSeq: a computational framework to discover the content and location of long novel sequence insertions using pairedend sequencing data generated by the nextgeneration sequencing platforms. Our framework can be built as part of a general sequence analysis pipeline to discover multiple types of genetic variation (SNPs, structural variation, etc.), thus it requires significantly less computational resources than de novo sequence assembly. We apply our methods to detect novel sequence insertions in the genome of an anonymous donor and validate our results by comparing with the insertions discovered in the same genome using various sources of sequence data. Availability: The implementation of the NovelSeq pipeline is available at