Dinesh P. Mehta

Bio: Dinesh P. Mehta is an academic researcher from Colorado School of Mines. The author has contributed to research in topics: Floorplan & Data structure. The author has an hindex of 13, co-authored 58 publications receiving 867 citations. Previous affiliations of Dinesh P. Mehta include University of North Alabama & University of Tennessee Space Institute.

Handbook of Data Structures and Applications

Abstract: Fundamentals Analysis of Algorithms Sartaj Sahni University of Florida, Gainesville, USA Basic Structures Dinesh P. Mehta Colorado School of Mines, Golden, Colorado, USA Trees Dinesh P. Mehta Graphs Narsingh Deo University of Central Florida, Orlando, USA Priority Queues Leftist Trees Sartaj Sahni Skew Heaps C. Pandu Rangan Indian Institute of Technology, Madras, Chennai Binomial, Fibonacci, and Pairing Heaps Michael L. Fredman Rutgers University, New Brunswick, New Jersey, USA Double-Ended Priority Queues Sartaj Sahni Dictionary Structures Hash Tables Pat Morin Carleton University, Ottawa, Ontario, Canada Balanced Binary Search Trees Arne Andersson, Uppsala University, Sweden Rolf Fagerberg and Kim S. Larsen, University of Southern Denmark, Odense Finger Search Trees Gerth Stolting Brodal University of Aarhus, Denmark Splay Trees Sanjeev Saxena Indian Institute of Technology, Kanpur Randomized Dictionary Structures C. Pandu Rangan Trees with Minimum Weighted Path Length Wojciech Rytter New Jersey Instituteof Technology, Newark, USA B. Trees Donghui Zhang Northeastern University, Boston, Massachusetts, USA Multidimensional and Spatial Structures Multidimensional Spatial Data Structures Hanan Samet University of Maryland, College Park, USA Planar Straight Line Graphs Siu-Wing Cheng The Hong Kong University of Science and Technology, Kowloon Interval, Segment, Range, and Priority Search Trees D. T. Lee Academia Sinica, Taipei, Taiwan Quadtrees and Octrees Srinivas Aluru Iowa State University, Ames, USA Binary Space Partitioning Trees Bruce F. Naylor University of Texas, Austin, USA R-Trees Scott Leutenegger and Mario A. Lopez University of Denver, Colorado, USA Managing Spatio-Temporal Data Sumeet Dua Louisiana Tech University, Ruston, USA S. S. Iyengar Louisiana State University, Baton Rouge, USA Kinetic Data Structures Leonidas Guibas Stanford University Palo Alto, California, USA Online Dictionary Structures Teofilo F. Gonzalez University of California, Santa Barbara, USA Cuttings Bernard Chazelle Princeton University, Princeton, New Jersey, USA Approximate Geometric Query Structures Christian A. Duncan University of Miami, Florida, USA Michael T. Goodrich University of California, Irvine, USA Geometric and Spatial Data Structures in External Memory Jeffrey Scott Vitter Purdue University West Lafayette, Indiana, USA Miscellaneous Data Structures Tries Sartaj Sahni Suffix Trees and Suffix Arrays Srinivas Aluru String Searching Andrzej Ehrenfeuch University of Colorado, Boulder, USA Ross M. McConnell Colorado State University, Fort Collins, USA Persistent Data Structures Haim Kaplan Tel Aviv University, Israel PC Trees Wen-Lian Hsu Academia Sinica, Taipei, Taiwan Ross M. McConnell Data Structures for Sets Rajeev Raman University of Leicester, UK Cache-Oblivious Data Structures Lars Arge Duke University, Durham, North Carolina, USA, Gerth Stolting Brodal University of Aarhus, Denmark Rolf Fagerberg Dynamic Trees Camil Demetrescu, Irene Finocchi, and Giuseppe F. Italiano Universita di Roma, Italy Dynamic Graphs Camil Demetrescu, Irene Finocchi, and Giuseppe F. Italiano Succinct Representation of Data Structures J. Ian Munro and S. Srinivasa Rao University of Waterloo, Ontario, Canada Randomized Graph Data-Structures for Approximate Shortest Paths Surender Baswana and Sandeep Sen Indian Institute of Technology, Delhi, India Searching and Priority Queues in o(log n) Time Arne Andersson Data Structures in Languages and Libraries Functional Data Structures Chris Okasaki United States Military Academy, West Point, New York LEDA, a Platform for Combinatorial and Geometric Computing Stefan Naeher University of Trier, Germany Data Structures in C++ Mark Allen Weiss Florida International University, Miami, USA Data Structures in JDSL Michael T. Goodrich Roberto Tamassia, and Luca Vismara Brown University, Providence, Rhode Island, USA Data Structure Visualization John Stasko Georgia Institute of Technology, Atlanta, USA Drawing Trees Sebastian Leipert Center of Advanced European Studies and Research, Bonn, Germany Drawing Graphs Peter Eades and Seok-Hee Hong University of Sydney and NICTA, Australia Concurrent Data Structures Mark Moir and Nir Shavit Sun Microsystems Laboratories, Burlington, Massachusetts, USA Applications IP Router Tables Sartaj Sahni Kun Suk Kim and Haibin Lu University of Florida, Gainesville, USA Multi-Dimensional Packet Classification Pankaj Gupta Cypress Semiconductor, San Jose, California, USA Data Structures in Web Information Retrieval Monika Henzinger Google, Inc., Mountain View, California, USA The Web as a Dynamic Graph S.N.Maheshwari Indian Institute of Technology, Madras, Chennai Layout Data Structures Dinesh P. Mehta Floorplan Representation in VLSI Zhou Fen Fudan University, Shanghai, China Bo Yao, and Chung-Kuan Cheng University of California, San Diego Computer Graphics Dale McMullin and Alyn Rockwood Colorado School of Mines, Golden, USA Geographic Information Systems Bernhard Seeger University of Marburg, Germany Peter Widmayer ETH, Zurich, Switzerland Collision Detection Ming C. Lin and Dinesh Manocha University of North Carolina, Chapel Hill, USA Image Data Structures S. Sitharama Iyengar V. K. Vaishnavi Georgia State University, Atlanta, USA S. Gunasekaran Louisiana State University, Baton Rouge, USA Computational Biology Stefan Kurtz University of Hamburg, Germany Stefano Lonardi University of California, Riverside, USA Elimination Structures in Scientific Computing Alex Pothen Old Dominion University, Norfolk, Virginia, USA Sivan Toledo Tel Aviv University, Israel Data Structures for Databases Joachim Hammer and Markus Schneider University of Florida, Gainesville, USA Data Mining Vipin Kumar and Michael Steinbach University of Minnesota, Minneapolis, USA Pang-Ning Tan Michigan State University, East Lansing, USA Computational Geometry: Fundamental Structures Mark de Berg and Bettina Speckmann Technical University, Eindhoven, The Netherlands Computational Geometry: Proximity and Location Sunil Arya The Hong Kong University of Scienceand Technology, Kowloon David M. Mount University of Maryland, College Park, USA Computational Geometry: Generalized Intersection Searching Prosenjit Gupta International Institute of Information Technology, Hyderabad, India Ravi Janardan University of Minnesota, Minneapolis, USA Michiel Smid Carleton University, Ottawa, Ontario, Canada

Handbook of Algorithms for Physical Design Automation

Abstract: The physical design flow of any project depends upon the size of the design, the technology, the number of designers, the clock frequency, and the time to do the design. As technology advances and design-styles change, physical design flows are constantly reinvented as traditional phases are removed and new ones are added to accommodate changes in technology. Includes a personal perspective from Ralph Otten as he looks back on the major technical milestones in the history of physical design automation. Explore State-of-the-Art Techniques and TrendsHandbook of Algorithms for Physical Design Automation provides a detailed overview of VLSI physical design automation, emphasizing state-of-the-art techniques, trends and improvements that have emerged during the previous decade. After a brief introduction to the modern physical design problem, basic algorithmic techniques, and partitioning, the book discusses significant advances in floorplanning representations and describes recent formulations of the floorplanning problem. The text also addresses issues of placement, net layout and optimization, routing multiple signal nets, manufacturability, physical synthesis, special nets, and designing for specialized technologies. Highly-Focused Information for Next Generation Design Problems Although several books on this topic are currently available, most are either too broad or out of date. Alternatively, proceedings and journal articles are valuable resources for researchers in this area, but the material is widely dispersed in the literature. This handbook pulls together a broad variety of perspectives on the most challenging problems in the field, and focuses on emerging problems and research results.

Optimal coverage paths in ad-hoc sensor networks

Abstract: This paper discusses the computation of optimal coverage paths in an ad-hoc network consisting of n sensors. Improved algorithms, with a preprocessing time of O(n log n), to compute a maximum breach/support path P in optimal (|P|) time or the maximum breach/support value in O(1) time are presented. Algorithms for computing a shortest path that has maximum breach/support are also provided. Experimental results for breach paths show that the shortest path length is on the average 30% less and is not much worse that the ideal straight line path. For applications that require redundancy (i.e., detection by multiple sensors), a generalization of Voronoi diagrams allows us to compute maximum breach paths where breach is defined as the distance to the kth nearest sensor in the field. Extensive experimental results are provided.

The quarter-state-sequence floorplan representation

Abstract: A floorplan of a bounding box is its dissection into rectangles (rooms) by horizontal and vertical segments. This paper proposes a string data structure called the Quarter-state sequence (or Q sequence) to represent the floorplan. The Q sequence is a concatenation of the states of rooms along the Abe order and is related to the VH graph, which is the union of the vertical-constraint and horizontal-constraint graphs. It is proved that any floorplan of n rooms is uniquely encoded by a Q sequence and any Q sequence is uniquely decoded to a floorplan, both in O(n) time. An exact formula for counting distinct floorplans is given and compared with existing bounds. A linear time transformation of one Q sequence to another is defined. An n-room packing algorithm based on simulated annealing was implemented and found to compare favorably with existing packing algorithms.

Predictive models to rebroadcast in mobile ad hoc networks

Abstract: Network wide broadcast is a fundamental operation in mobile ad hoc networks (MANETs). Several broadcast protocols have been proposed in the literature that improves on simple flooding by reducing the probability that a receiving node retransmits a packet. We propose analytical models to estimate these probabilities for three broadcast protocols. Our simulations show that these analytical models, which were derived under some simplifying assumptions, predict retransmission probabilities for static and mobile networks quite accurately when only the network layer is considered.

Triangulating a simple polygon in linear time

Abstract: We give a deterministic algorithm for triangulating a simple polygon in linear time. The basic strategy is to build a coarse approximation of a triangulation in a bottom-up phase and then use the information computed along the way to refine the triangulation in a top-down phase. The main tools used are the polygon-cutting theorem, which provides us with a balancing scheme, and the planar separator theorem, whose role is essential in the discovery of new diagonals. Only elementary data structures are required by the algorithm. In particular, no dynamic search trees, of our algorithm.

Ministry of Statistics and Programme Implementation

Abstract: Meeting: International Seminar on Information and Communication Technology Statistics, Seoul, Republic of Korea, 19-21 July 2010

Coverage problems in sensor networks: A survey

Abstract: Sensor networks, which consist of sensor nodes each capable of sensing environment and transmitting data, have lots of applications in battlefield surveillance, environmental monitoring, industrial diagnostics, etc. Coverage which is one of the most important performance metrics for sensor networks reflects how well a sensor field is monitored. Individual sensor coverage models are dependent on the sensing functions of different types of sensors, while network-wide sensing coverage is a collective performance measure for geographically distributed sensor nodes. This article surveys research progress made to address various coverage problems in sensor networks. We first provide discussions on sensor coverage models and design issues. The coverage problems in sensor networks can be classified into three categories according to the subject to be covered. We state the basic coverage problems in each category, and review representative solution approaches in the literature. We also provide comments and discussions on some extensions and variants of these basic coverage problems.

Fixed-outline floorplanning: enabling hierarchical design

Abstract: Classical floorplanning minimizes a linear combination of area and wirelength. When simulated annealing is used, e.g., with the sequence pair representation, the typical choice of moves is fairly straightforward. In this paper, we study the fixed-outline floorplan formulation that is more relevant to hierarchical design style and is justified for very large ASICs and SoCs. We empirically show that instances of the fixed-outline floorplan problem are significantly harder than related instances of classical floorplan problems. We suggest new objective functions to drive simulated annealing and new types of moves that better guide local search in the new context. Wirelength improvements and optimization of aspect ratios of soft blocks are explicitly addressed by these techniques. Our proposed moves are based on the notion of floorplan slack. The proposed slack computation can be implemented with all existing algorithms to evaluate sequence pairs, of which we use the simplest, yet semantically indistinguishable from the fastest reported . A similar slack computation is possible with many other floorplan representations. In all cases the computation time approximately doubles. Our empirical evaluation is based on a new floorplanner implementation Parquet-1 that can operate in both outline-free and fixed-outline modes. We use Parquet-1 to floorplan a design, with approximately 32000 cells, in 37 min using a top-down, hierarchical paradigm.