Data stored on disks and tapes or transferred over communications links in commercial computer systems generally contains significant redundancy. A mechanism or procedure which recodes the data to lessen the redundancy could possibly double or triple the effective data densitites in stored or communicated data. Moreover, if compression is automatic, it can also aid in the rise of software development costs. A transparent compression mechanism could permit the use of "sloppy" data structures, in that empty space or sparse encoding of data would not greatly expand the use of storage space or transfer time; however , that requires a good compression procedure. Several problems encountered when common compression methods are integrated into computer systems have prevented the widespread use of automatic data compression. For example (1) poor runtime execution speeds interfere in the attainment of very high data rates; (2) most compression techniques are not flexible enough to process different types of redundancy; (3) blocks of compressed data that have unpredictable lengths present storage space management problems. Each compression ' This article was written while Welch was employed at Sperry Research Center; he is now employed with Digital Equipment Corporation. 8 m, 2 /R4/OflAb l strategy poses a different set of these problems and, consequently , the use of each strategy is restricted to applications where its inherent weaknesses present no critical problems. This article introduces a new compression algorithm that is based on principles not found in existing commercial methods. This algorithm avoids many of the problems associated with older methods in that it dynamically adapts to the redundancy characteristics of the data being compressed. An investigation into possible application of this algorithm yields insight into the compressibility of various types of data and serves to illustrate system problems inherent in using any compression scheme. For readers interested in simple but subtle procedures, some details of this algorithm and its implementations are also described. The focus throughout this article will be on transparent compression in which the computer programmer is not aware of the existence of compression except in system performance. This form of compression is "noiseless," the decompressed data is an exact replica of the input data, and the compression apparatus is given no special program information, such as data type or usage statistics. Transparency is perceived to be important because putting an extra burden on the application programmer would cause

A Technique for High-Performance Data Compression

B-trees have become, de facto, a standard for file organization. File indexes of users, dedicated database systems, and general-purpose access methods have all been proposed and nnplemented using B-trees This paper reviews B-trees and shows why they have been so successful It discusses the major variations of the B-tree, especially the B+-tree, contrasting the relatwe merits and costs of each implementatmn. It illustrates a general purpose access method whmh uses a B-tree.

http://people.cs.aau.dk/~simas/aalg06/UbiquitBtree.pdf

Ubiquitous B-Tree

From the Publisher:
This work covers all aspects of physical design. The book is a core reference for graduate students and CAD professionals. For students, concept and algorithms are presented in an intuitive manner. For CAD professionals, the material presents a balance of theory and practice. An extensive bibliography is provided which is useful for finding advanced material on a topic. At the end of each chapter, exercises are provided, which range in complexity from simple to research level.

Algorithms for VLSI Physical Design Automation

A general model for data compression which includes most data compression systems in the fiterature as special cases is presented. Macro schemes are based on the principle of finding redundant strings or patterns and replacing them by pointers to a common copy. Different varieties of macro schemes may be defmed by specifying the meaning of a pointer; that is, a pointer may indicate a substring of the compressed string, a substring of the original string, or a substring of some other string such as an external dictionary. Other varieties of macro schemes may be defined by restricting the type of overlapping or recursion that may be used. Trade-offs between different varieties of macro schemes, exact lower bounds on the amount of compression obtainable, and the complexity of encoding and decoding are discussed, as well as how the work of other authors relates to this model.

Data compression via textual substitution

This paper surveys a variety of data compression methods spanning almost 40 years of research, from the work of Shannon, Fano, and Huffman in the late 1940s to a technique developed in 1986. The aim of data compression is to reduce redundancy in stored or communicated data, thus increasing effective data density. Data compression has important application in the areas of file storage and distributed systems. Concepts from information theory as they relate to the goals and evaluation of data compression methods are discussed briefly. A framework for evaluation and comparison of methods is constructed and applied to the algorithms presented. Comparisons of both theoretical and empirical natures are reported, and possibilities for future research are suggested.

Data compression

The Lee path connection algorithm is probably the most widely used method for finding wire paths on printed circuit boards. It is shown that the original claim of generality for the path cost function is incorrect, and a restriction, called the pathconsistency property, is introduced. The Lee algorithm holds for those path cost functions having this property. Codings for the cells of the grid are proposed which will allow the correct operation of the algorithm under the most general path cost function, using the minimum number of states possible, six states per cell. Then methods for reducing the number of calculations by increasing the number of states are presented.

/pdf/the-lee-path-connection-algorithm-15pjefdgul.pdf

The Lee Path Connection Algorithm

A system for the compression of data files, viewed as strings of characters, is presented. The method is general, and applies equally well to English, to PL/I, or to digital data. The system consists of an encoder, an analysis program, and a decoder. Two algorithms for encoding a string differ slightly from earlier proposals. The analysis program attempts to find an optimal set of codes for representing substrings of the file. Four new algorithms for this operation are described and compared. Various parameters in the algorithms are optimized to obtain a high degree of compression for sample texts.

Experiments in text file compression

A search procedure is given which will determine whether Hamilton paths or circuits exist in a given graph, and will find one or all of them. A combined procedure is given for both directed and undirected graphs. The search consists of creating partial paths and making deductions which determine whether each partial path is a section of any Hamilton path whatever, and which direct the extension of the partial paths.

A Search Procedure for Hamilton Paths and Circuits

Wires are routed allowing crossings in the initial layout. By spreading the wires and increasing the crossover penalties, fewer crossings occur on each iteration until a crossing free layout is achieved.

An iterative technique for printed wire routing

Hopcroft and Tarjan [2] have recently proposed an algorithm that runs in linear time for testing the planarity of a graph. The technique finds a representation of the graph as a sequence of paths and then iteratively imbeds these paths to find a mesh structure, rearranging the meshes as needed to accommodate each new path. Demoucron et al. [1] have shown that this rearrangement process is unnecessary if the paths are considered in the proper order. The present implementation is found to run in linear time for most ordinary cases, about twice as fast as Tarjan's Algol implementation. A graph of 3000 vertices and 8994 edges required about 18 s.

Frank Rubin

Papers

The Lee Path Connection Algorithm

Experiments in text file compression

A Search Procedure for Hamilton Paths and Circuits

An iterative technique for printed wire routing

An Improved Algorithm for Testing the Planarity of a Graph