Distributed Computing: What Is It and Can It Be Useful
A Brief Introduction
You can define distributed computing many different ways. Various vendors have created and marketed distributed computing systems for years, and have developed numerous initiatives and architectures to permit distributed processing of data and objects across a network of connected systems. They have developed a virtual environment where you can harness idle CPU cycles and storage space of tens, hundreds, or thousands of networked systems to work together on a particularly processing-intensive problem. The growth of such processing models has been limited, however, due to a lack of compelling applications and by bandwidth bottlenecks, combined with significant security, management, and standardization challenges. A number of new vendors have appeared to take advantage of the promising market; including Intel, Microsoft, Sun, and Compaq that have validated the importance of the concept.1 Also, an innovative worldwide distributed computing project whose goal is to find intelligent life in the universe--SETI@Home--has captured the imaginations, and desktop processing cycles of millions of users and desktops.
How It Works
The most powerful computer in the world, according to a recent ranking, is a machine called Janus, which has 9,216 Pentium Pro processors2. That's a lot of Pentiums, but it's a pretty small number in comparison with the 20 million or more processors attached to the global Internet. If you have a big problem to solve, recruiting a few percent of the CPUs on the Net would gain you more raw power than any supercomputer on earth. The rise of cooperative-computing projects on the Internet is both a technical and a social phenomenon. On the technical side, the key requirement is to slice a problem into thousands of tiny pieces that can be solved independently, and then to reassemble the answers. The social or logistical challenge is to find all those widely dispersed computers and persuade their owners to make them available.
In most cases today, a distributed computing architecture consists of very lightweight software agents installed on a number of client systems, and one or more dedicated distributed computing management servers. There may also be requesting clients with software that allows them to submit jobs along with lists of their required resources. An agent running on a processing client detects when the system is idle, notifies the management server that the system is available for processing, and usually requests an application package.
The internet works on the basis that some computers act as ‘servers’. These computers offer services for other computers that are accessing or requesting information, these are known as ‘clients’. The term “server” may refer to both the hardware and software (the entire computer system) or just the software that performs the service. For example, Web server may refer to the Web server software in a computer that also runs other applications or it may refer to the computer system dedicated only to the Web server applicant. For example, a large Web site could have several dedicated Web servers or one very large Web server.
Computers were in development from as early as the 1950’s, but the general public wouldn’t hear of the World Wide Web until the 1980’s. By the year 2000, the internet was accessible to the general public from their home computers. It was used mainly for e-mailing, online shopping and research, but with its growing popularity, the World Wide Web was quick to expand its content. We can now, in the present day, access the internet on a number of platforms such as mobile phones, laptops and PCs, and even Smart Televisions, which makes a vast difference to the platforms people used 30 years ago.
A distributed system is a collection of independent computers (nodes) that appears to its users as a single coherent
The new payroll system will utilize client/server based architecture with the use of thin clients running from a central terminal server located at the Data Center. The terminal server will communicate with the application server where the new payroll application will reside and the application server will communicate with the payroll database server.
Deploy clusters with MapReduce,HDFS, Hive,Hive server and , Pig.Fully customizable configuration profile.This includes dedicated machines or share with other work load, DHCP network or Static IP and local storage and shared one.
What we know today as the Internet began as a Defense Advanced Research Projects Agency (DARPA) project in 1969, which was designed to connect several research databases across the country. However, until the end of 1991, the advances were almost completely technical, as the goals set by those responsible in its growth were beyond what the hardware was capable of providing. In 1988, the Internet began to receive attention in the popular press, when the first documented computer virus was released at Cornell University. 1991 marked the beginning of the transition of the Internet as we know it today, with the National Science Foundation’s reinterpretation of its Acceptable Use Policy to allow for commercial traffic across its network, the development of the first graphic interfaces, the formation of the Internet Society, and the formation of ECHO (East Coast Hang Out), one of the first publicly available online communities.
Why NetBatch? At my workplace, we have way more computing needs for the number of machines we own. Hence, it would be economically infeasible to buy enough machines to satisfy our peak consumption, which is growing constantly. NetBatch is a tool, which allows our organization to maximize utilization of the available computing resources. This paper discusses about NetBatch and NBS, a package around NetBatch that handles job management, which use principles of queuing, job scheduling, sequencing to achieve its goals.
The concept of multi agent system comes to the technical world through several factors which initiated the concept of multi agent system. After the invention of computers, human expectations are reaching upon the peak. At the contrary, efficiency and capability of machines were degrading unless it was overcome. Another concept then comes into the picture to use enlarged processing power and devices to speed it up. But this enhancement allows taking the complexity and sophistication of usability and maintainability along it. Gathering more knowledge to handle it is must required. Distributed approach has grabbed the computer generation where systems are not remained alone and connected to a common channel. The most challenging example is internet without which the human life becomes damaged. This interaction is viewed by many scientists and many approaches have been discussed. To deal with the ...
“The most profound technologies are those that disappear. They weave themselves into the fabric of everyday life until they are indistinguishable from it ” – Mark Weiser.
It simplifies the storage and processing of large amounts of data, eases the deployment and operation of large-scale global products and services, and automates much of the administration of large-scale clusters of computers.
Grid computing is defining the combination of computer resources from many numbers of administrative domains to reach the existing goal. The grids have heterogeneity and geographic disreputability in its resources. Grids can solve grand challenge applications using the Computer Modeling, Simulation and Analysis. Grids can be available in the form of distributed computing and differs from the other architectures like as a cluster. Grid computing can overcome the limitations such as the conventional shared computing mood and to become a principal trend in the distributed computing system. Grid core service is the Centre of grid computing which can take the charge of entire grid system in order to give definite grid system with its work effectiveness. The grid core service is an important part in the grid computing and the task scheduling strategy is the part of grid core service. The grid resources are required more number of tasks and the system can optimizes the resource through scheduling the tasks reasonably.
Abstract—High Performance Computing (HPC) provides support to run advanced application programs efficiently. Java adaptation in HPC has become an apparent choice for new endeavors, because of its significant characteristics. These include object-oriented, platform independent, portable, secure, built-in networking, multithreading, and an extensive set of Application Programming Interfaces (APIs). Consequently multi-core systems and multi-core programming tools are becoming popular. However, today the leading HPC programming model is Message Passing Interface (MPI). In present day computing, while writing a parallel program for multi-core systems in distributed environment may deploy an approach where both shared and distributed memory models are used. Moreover an interoperable, asynchronous, and reliable working environment is required for programmers and researchers to build the HPC applications. This paper reviews the existing MPI implementations in Java. Several assessment parameters are identified to analyze the Java based MPI models; including their strengths and weaknesses.
Parallel computer are those system that emphasis parallel processing. The basic architectural features of parallel computers are introduced below. We divide parallel computer into three architectural configuration :
Since the time when man first learned to express how they felt in written form, by drawing or writing, we have tried to communicate with other people. First, it was the prehistoric man with their conceptual cave drawings showing what animals to hunt, how to hunt them, and how to cook them. Soon that form took to hieroglyphics, in which the Egyptians would tell stories about battles they had won and about new pharaohs that had been born. This picture form soon turned in to words in which the Romans would communicate with one another. So it went, each generation progressed more and more, until it was the 20th century.
Throughout my undergraduate studies, I was exposed to various aspects of computer science and engineering. And this exposure helped me to develop as a computer engineer with a broader knowledge. But without an in-depth study on specific fields especially in parallel computing and distributed systems which I’m highly interested of, left me with an urge to study and explore th...