Encyclopedia of Computer Science and Technology

134 data compressionlocal network, or connect to the Internet through DSL,an enhanced phone line. Traveling home, the user mightuse a personal digital assistant (PDA) with a wireless linkto make a restaurant reservation (see wireless computing).The user wants all these services to be seamless andessentially interchangeable, but today data communicationsis more like roads in the early days of the automobile—afew fast paved roads here and there, but manybumpy dirt paths.Further ReadingForouszan Behrouz. Data Communications and Networking. NewYork: McGraw Hill, 2006.Stallings, William. Data and Computer Communications. 8th ed.Upper Saddle River, N.J.: Prentice Hall, 2006.Strangio, Christopher E. “Data Communications Basics.” Availableonline. URL: http://www.camiresearch.com/Data_Com_Basics/data_com_tutorial.html. Accessed July 8, 2007.White, Curt. Data Communications and Computer Networks: A BusinessUser’s Approach. 4th ed. Boston: Course Technology,2006.data compressionThe process of removing redundant information from dataso that it takes up less space is called data compression.Besides saving disk space, compressing data such as e-mailattachments can make data communications faster.Compression methods generally begin with the realizationthat not all characters are found in equal numbers intext. For example, in English, letters such as e and s arefound much more frequently than letters such as j or x.By assigning the shortest bit codes to the most commoncharacters and the longer codes to the least common characters,the number of bits needed to encode the text can beminimized.Huffman coding, first developed in 1952, is an algorithmthat uses a tree in which the pairs of the least probable (thatis, least common) characters are linked, the next least probablelinked, and so on until the tree is complete.Another coding method, arithmetic coding, matchescharacters’ probabilities to bits in such a way that the samebit can represent parts of more than one encoded character.This is even more efficient than Huffman coding, but thenecessary calculations make the method somewhat slowerto use.Another approach to compression is to look for words(or more generally, character strings) that match thosefound in a dictionary file. The matching strings are replacedby numbers. Since a number is much shorter than a wholeword or phrase, this compression method can greatlyreduce the size of most text files. (It would not be suitablefor files that contain numerical rather than text data, sincesuch data, when interpreted as characters, would look like arandom jumble.)The Lempel-Ziv (LZ) compression method does notuse an external dictionary. Instead, it scans the file itselffor text strings. Whenever it finds a string that occurredearlier in the text, it replaces the later occurrences withan offset, or count of the number of bytes separating theA basic approach to data compression is to look for recurring patternsand store them in a “dictionary.” Each occurrence of thepattern can then be replaced by a brief reference to the dictionaryentry. The resulting file may then be considerably smaller than theoriginal.occurrences. This means that not only common words butcommon prefixes and suffixes can be replaced by numbers.A variant of this scheme does not use offsets to thefile itself, but compiles repeated strings into a dictionaryand replaces them in the text with an index to their positionin the dictionary.Graphics files can often be greatly compressed by replacinglarge areas that represent the same color (such as a bluesky) with a number indicating the count of pixels with thatvalue. However, some graphics file formats such as GIF arealready compressed, so further compression will not shrinkthem much.More exotic compression schemes for graphics can usefractals or other iterative mathematical functions to encodepatterns in the data. Most such schemes are “lossy” in thatsome of the information (and thus image texture) is lost,but the loss may be acceptable for a given application. Lossycompression schemes are not used for binary (numeric dataor program code) files because errors introduced in a programfile are likely to affect the program’s performance (ifnot “break” it completely). Though they may have less seriousconsequences, errors in text are also generally consideredunacceptable.TrendsThere are a variety of compression programs used onunix systems, but variants of the Zip program are nowthe overwhelming favorite on Windows-based systems. Zipcombines compression and archiving. Archiving, or thebundling together of many files into a single file, contributesa further reduction in file size. This is because files inmost file systems must use a whole number of disk sectors,even if that means wasting most of a sector. Combining filesinto one file means that at most a bit less than one sectorwill be wasted.