Encyclopedia of Computer Science and Technology

480 trends and emerging technologiesFor efficiency it’s important to keep all branches of a treeapproximately the same length. A B-tree (balanced tree) isdesigned to automatically optimize itself in this way.Trees lend themselves to game programs where a seriesof moves and their possible replies must be explored tovarying levels. A chess program will typically create a treefrom the current position, but use various criteria to determinewhich moves should be explored beyond just a fewlevels, thus “pruning” the game tree.Further ReadingBrookshear, J. Glenn. Computer Science: An Overview. 9th ed. Boston:Addison-Wesley, 2006.Lafore, Robert. Data Structures & Algorithms in Java. 2nd ed. Indianapolis:Sams, 2002.Parlante, Nick. “Binary Trees.” Available online. URL: http://cslibrary.stanford.edu/110/BinaryTrees.html. Accessed August23, 2007.trends and emerging technologiesBecause of the complexity of computer systems, software,and business models, it is easy to “fail to see the forest forthe trees.” Stepping back once in a while to see what ischanging (or likely to change) is recommended. Such a perspectiveis particularly useful for professionals who need toperiodically evaluate their skills against the market, investors,venture capitalists, journalists, and educators.It is nearly a commonplace to say that the future is comingat an accelerating rate (for the ultimate speculation, seesingularity, technological). What adds to the challengeis the way each new technology (and social adaptation)has multiple consequences, whether it is social networking,“viral marketing,” or individually targeted, location-awareadvertising. At the same time, attempting to distinguishshort-term hype from genuine trends is always difficult—anyone in the computing field can compile a glossary ofnow-obsolete buzzwords. Thus reading a variety of perspectivesfrom advocates to pundits to critics is essential.Overall TrendsThat said, the following table suggests some activities thatare in transition from a traditional model to one that reflectsemerging technological and social trends.Fromtodesktop PCmobile and pervasive computingwired networkswireless and mobile computingseparate handling of media integrated media serversbroadcastinguser-driven, customizable channelsof mediauser as consumer user as contributor and sharerindividual consumers social networkingsoftware as product software as serviceproprietary codeopen sourceinterface-driven tasks search-driven interfacesarbitrarily organized data semantically retrievableinformation.e-commerceintegration of online and traditionalchannelsFor more information about emerging trends, see thefollowing entries: digital convergence, open-sourcemovement, service-oriented architecture, smartbuildings and homes, social networking, ubiquitouscomputing, user-created content, Web 2.0 andbeyond, Web services.Further ReadingHaskin, David. “Don’t Believe the Hype: The 21 Biggest TechnologyFlops.” Computerworld, April 4, 2007. Available online.URL: http://www.computerworld.com/action/article.do?articleId=9012345&comm and=viewArticleBasic. AccessedNovember 29, 2007.Piquepaille, Roland. “Emerging Technology Trends” [blog]. ZDNet.Available online. URL: http://blogs.zdnet.com/emergingtech/.Accessed November 29, 2007.Plunkett Research. “Plunkett’s E-Commerce & Internet Industry.”Available online. URL: http://www.plunkettresearch.com/Industries/ECommerceInternet/tabid/151/Default.aspx.Accessed November 29, 2007.———. “Plunkett’s InfoTech, Computers & Software Industry.”Available online. URL: http://www.plunkettresearch.com/Industries/InfoTechComputersSoftware/tabid/152/Default.aspx. Accessed November 29, 2007.Seidensticker, Bob. Future Hype: The Myths of Technology Change.San Francisco: Berrett-Koehler, 2006.trust and reputation systemsTrust and reputation are inherently connected. Participantsin any transaction (such as respondents to classified ads orparticipants in an online auction) want assurance that theywill receive the promised value in exchange for what theyare giving up. The default anonymity of online transactions(see anonymity and the Internet) presents a challenge:How does one obtain information about someone’s reputation(how he or she has behaved previously) and thus beassured of his or her reliability?One solution is to collect and characterize the experiencesof participants in previous transactions with thatperson or entity. For an auction (see auctions, online andeBay), the system can solicit and tabulate ratings (“feedback”)by participants in each transaction. However, thiskind of simple system must guard against being subvertedby people who create false identities (fronts) and transactionsand use them to inflate the feedback score.A more sophisticated reputation system can be used forranking Web pages, contributions (such as blogs or productreviews), or other works. Instead of giving each participantthe same single “vote,” the feedback is weighted accordingto the responder’s own reputation. Thus if a numberof people whose own product reviews have been highlyrecommended also recommend another review, that reviewwill be much more highly rated. Examples of this sort ofsystem include the PageRank algorithm used by Google,the consumer review site Epinions.com, and the “techie”favorite Slashdot.Developing a trust and reputation system that is effectivebut unobtrusive is particularly important for the collaborativecreation of content such as for search enginesand wikis (see user-created content and wikis andWikipedia).