Describe the paradigm shift in distributed computing?
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In the old days computers were big and expensive. Many people would want to use them, eventually there were terminals attatched to the big computers so different people could use them at what seemed to be the same time. But then this guy bought a pc that was small and started using it at his desk. He figured out that he could connect his pc to the big computers in the same way big computers connect to each other. And then more and more people bought there own little, affordable, off-the-shelf computer and started connecting them. Now they are free to look for ring tones.
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yes, it was used heavily in the late 1990s and Early 2000s when I was in corporate America- I'm not sure if its still popular or used extensively.\n\nA paradigm shift is when you change your perspective or have it changed for you.  Dr. Steven Covey (7 habits of highly effective people) describes a scene on a bus with a man and his ill behaved children.  they were running around making a bunch of noise and pretty much disrupting everyone that wanted to just ride in peace and quiet to their destination.  Everyone was getting really upset.  One passenger asked the man to get control of his children.  the man replied that the family had just come from the hospital where their mother had passed away just minutes ago.  Everyone on the bus went from being upset to feeling sympathy and understanding.  This was a paradigm shift.
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Doesn't the whole concept of 3-tier computing need it to exist?\nApplication layer = business rules - highly important
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CENTURIES OF PROGRAMMING
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Pervasive Computing is a catalyst for advancing research and practice in mobile and ubiquitous computing.
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Software Processes is an evolving field which takes a small library to explain; the term refers to the design of processes for Software Engineering.  (That is, design and production of a substantial piece of software beyond use-cases.\n\nHaving studied XM and Grady Booch's corpus, you might decide which Layered Technologies paradigm has been mentioned to you (e.g. by searching with 'GSA' or 'DOD' or 'GM' in your terms), of the several model architectures available; primitive layered technologies suggests that you're going to pick a series of technologies and model the competencies of it with respect to each other tech it can be expected to talk with, perhaps choosing the layering to look like the OSI networking model or some Model-View-Controller stack or the Seattle skyline.\n\nI think the original process of this sort was a Cambrian C stack where your program execution stack looked like your architecture; you call up or down one technology at a time, and its model will have to act or defer in the same direction and then return.  It's like writing excellent exceptions code but within a spinlock.
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Here's a good tutorial:\n\nhttp://schools.sbe.saskatoon.sk.ca/Mario/Academic/GrassrootsProject/ComputerScience/hextutorial.htm
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It's kind of a phased approach where one item follows another. It's general to software methodologies and not really specific to BI. There's a good diagram and some discussion in the link below.
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Well, in my opinion, we had/have platform independence with Java as well as many older and newer technologies designed for the Internet and Intranet environments.  While platform independence is a boon to the networked world and not a bad thing elsewhere, it is not a gut wrenching requirement for many applications on many platforms.  I think that part of the trouble lies simply with the IT community's unwillingness to concede that it is nice where you can get it, but won't stop computers in other non-networked environments (embedded platforms, stand alone workstations, point of sale terminals and high end mainframes or super computers, etc.) from running applications made with less portable languages and compilers.  In other words, people tend to use what they want in certain platforms and as long as it works it stays that way.  So, I'd say it has done as much as it has been called to do and will do more when it is called to do that.
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IBM Introduces 'World Community Grid'\n\nPublic invited to donate idle computer time for global humanitarian effort\n\nARMONK, N.Y., November 16, 2004— IBM, along with representatives of the world's leading science, education and philanthropic organizations, today launched World Community Grid, a global humanitarian effort that applies the unused computing power of individual and business computers to help address the world's most difficult health and societal problems.\n\nWorld Community Grid will harness the vast and unused computational power of the world's computers and direct it at research designed to help unlock genetic codes that underlie diseases like AIDS and HIV, Alzheimer's and cancer, improve forecasting of natural disasters and support studies that can protect the world's food and water supply. Anyone can volunteer to donate the idle and unused time on a computer by downloading World Community Grid's free software and registering at www.worldcommunitygrid.org.
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COMMUNICATIONS OF THE ACM August 1998/Vol. 41, No. 8 63\nNearly a decade of Workshops on Information Systems and Economics\n(WISE) have examined a wide range of research topics.\nThese include a number of what could be termed “demand-side” topics, which focus on the\neffective use of information technology, such as IT-induced changes to markets, and “supplyside”\ntopics, which focus on the efficient provision of IT resources. Software engineering economics\n(SEE) spans both groups, but it has generally been the most dominant topic within the supply\narea. While the economics of hardware have been relatively ignored in the management\nresearch literature, given industry’s ability to continually provide\nfaster, smaller hardware at ever-decreasing prices, software has been an\nentirely different matter. Software costs continue to be significant, and\nindustry’s understanding of how to reduce them has improved only very\nslowly in contrast to hardware. This dilemma has merited a significant\namount of research attention, and the consequent research findings tend to\nhave important practical applications.\nChris F. Kemerer\nProgress, Obstacles, and\nOpportunities in\nSoftware Engineering\nEconomics\nPressing demands from industry suggest more attention\nshould be focused on this critical area.\nA d v a n c e s i n S o f t w a r e E n g i n e e r i n g E c o n o m i c s\nAlso in contrast to some of the demand-related\ntopics, SEE research commonly has a significant\ntechnological component to it, since much of the\nresearch is focused on evaluating promising new\ntechnologies or approaches to software development.\nThis diverges with much demand-side work, which\ntends to be closer to traditional economics research.\nTherefore it requires some skills and knowledge of\nboth the software engineering and economics disciplines.\nAccordingly, it has also attracted some\nresearchers from the software engineering area\nwithin computer science, whose work will also be\nreflected in this review, and in the suggestions for\nfuture work. This combination of skill requirements\nalso tends to make research in this area comparatively\ndifficult, and suggests one reason why we\ndon’t see more research in this important area.\nPractitioners are most concerned about understanding\nwhat aspects of software engineering innovations\nhave worked best and whether they are\napplicable to their particular situation. This motivation\nalso lies at the heart of most SEE research. In\naddition, with the huge growth in the packaged\nsoftware industry, more attention has been focused\non software as an economic good.\nObstacles to Progress\nA number of factors militate against observing\nprogress in software engineering in general, and software\nengineering economics in particular. Software\nengineering focuses on the production of software,\nwhich is by its very nature a relatively intangible\ngood. Objectifying and measuring its many dimensions\nare often challenging to researchers. Even in\nsituations where we have relatively good softwarerelated\nartifacts to examine, there may be little evidence\nto examine concerning the process by which\nthey were constructed.\nEven if there were good access to project data,\nthere is another significant confounding factor. The\nnumber and complexity of applications for software\nhave grown very rapidly, fueled, in large measure, by\nthe dramatic improvements in hardware technology.\nAs hardware decreases in size and increases in performance\nper dollar, more applications can be justified.\nThis then creates demand for software. While\nthis tremendous demand for software has fueled the\nfortunes of many software developers and their organizations,\nit provides significant challenges to\nresearchers as we attempt to assess progress in the\ndelivery of software. Since the applications have\nchanged as well as the tools, it becomes very difficult\nto assess the impacts of these new tools. It may well\nbe the c
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Just looked at their website.This is an 'all-in-one ' package which may suit a greenfield development but if you are having to integrate with other middleware? Tomcat/JBOSS/Websphere/Microsoft MTS/.NET?.It's all very well using grids,parallelism and clustering , but you still have the page-lock or contention problem , i.e. what if 2 processes are after the same part of the DB? They have a Caching Edition , but this only postpones the problem . If you have less than 100 TPS then your usually OK with a single instance of MySQL. Any more than that and you start haibg to think a bit. ( take a look at the Oracle performance tuning sites , lots theree about disk / cache / processor configuring).
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Thats a pretty broad question!  What part of the world of computers?  PC's  faster, cheaper, but not better.\nFor servers, the trend is towards virtualization, and IBM\nis currently the leader in my opinion.
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The ACE ORB (TAO) is a freely available, open-source, and standards-compliant real-time C++ implementation of CORBA based upon the Adaptive Communication Environment (ACE). It attempts to provide efficient, predictable, and scalable quality of service (QoS) end-to-end. Unlike conventional implementations of CORBA, which are inefficient, unpredictable, non-scalable, and often non-portable, TAO applies the best software practices and patterns to automate the delivery of high-performance and real-time QoS to distributed applications. TAO is for developers of distributed and embedded applications who have stringent performance demands.
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This thesis is centered around the topic database replication. The work has been motivated by the advances in the development of cluster databases and their specific demands in terms of high throughput, low response times, flexible load-balancing, data consistency and fault-tolerance. Eager, update-everywhere replication seems a promising mechanism to achieve these goals. By replicating data across the cluster, transaction have fast access to local copies and the available system can take over the work of failed sites. Using eager replica control the updates on the different copies are coordinated before the transaction commits providing data consistency and fault-tolerance in a straightforward way. Update-everywhere is a prerequisite for load balancing since only then a transaction can be submitted at any site without any restrictions. However, existing eager, update-everywhere solutions have severe performance limitations and are barely used in practice.\nWhat is needed is a solution that bridges the gap between theory and and practice, and implements efficient, eager, update-everywhere replication. The thesis provides several contributions to this goal.\nWe start with a detailed analysis of existing solutions depicting those assumptions and techniques that make current solutions inefficient and impracticable. In an attempt to eliminate these limitations the thesis presents a couple of basic techniques that we believe are necessary to provide efficiency: keeping the number of messages small, using the powerful multicast primitives of group communication systems to support replica control and fault-tolerance, simplifying the coordination between the database systems, avoiding deadlocks and a 2-phase commit protocol, and providing different levels of transaction isolation and fault-tolerance in order to adapt to various hardware and workload configurations.\nBased on these techniques the thesis develops a replication tool in three steps. First, we develop a theoretical framework including a family of replica control protocols. These protocols delay communication until the end of the transactions where all updates are multicast in a single message to all sites. By using a total order multicast as provided by group communication systems all messages arrive in the same order at all sites. By guaranteeing that all sites serialize conflicting transactions according to this order transactions are globally ordered without further coordination among the sites. In order to reduce resource consumption remote sites do not need to reexecute the operations but only apply the physical changes. The proposed replica control protocols provide different levels of isolation allowing for various degrees of concurrency. Furthermore, they offer two levels of fault-tolerance which vary in the degree of data consistency on failed nodes. All protocols provide data consistency on available sites and correctness criteria that are well understood and widely used in practice.\nIn a second step we evaluate our approach in two ways. First, we have built a simulation system that provides a performance comparison of all proposed protocols and a comparison with traditional solutions. This study shows that our approach provides superior performance compared to traditional solutions, is more stable and applicable for a much wider range of configurations and workloads. By providing a whole family of protocols the approach is able to adjust to the environment since the protocol can be chosen that is best suited to alleviate the specifics of a given configuration. In particular, the protocols are able to address high network costs and high conflict rates. Second, we have proven the feasibility of the approach in a real cluster environment by integrating it into the database system PostgreSQL. Most of the functionality has been added in separate modules and only few changes to the existing PostgreSQL system were necessary. With this, we are confident that the approa
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define "largest server"... most space? fastest?  once you get up to "really friggin big", they start to specialize with what the server does- and they dont just use one, they have arrays of servers that they string together to make supercomputers... refining your question would help
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Try http://compnetworking.about.com/cs/networkfuture/