Java Abs Grid Information Retrival System
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The document describes a Grid Information Retrieval (IR) system that combines information retrieval techniques with grid computing to facilitate efficient data processing across distributed resources. The initiative aims to match user information needs with relevant documents using a Java-based architecture supported by MS Access for indexing. The project focuses on maximizing unused computing resources while implementing an autonomous, distributed model of IR services comprising collection management, indexing/searching, and query processing.
Java Abs Grid Information Retrival System
- 1. GRID INFORMATION RETRIVAL SYSTEM USING JAVA INTRODUCTION GRID IR is Information Retrieval on the grid! It is a new initiative to bring together information retrieval techniques with grid computing. IR or information retrieval is a field of research concerned with searching unstructured (or quasi-structured) data such as text documents and the retrieval of results pertinent to a user’s query. Modern web search engines are the most widely known implementations of IR system. Grid computing is the accomplishment of computational tasks on a set of computers connected by a network. This is similar to distributed computing, except with a more finely grained implementation for task assignment and coordination among the grid elements. Grid computing provides clustering of remotely distributed computing. The principal focus of grid computing to date has been on maximizing the use of available processor resources for compute-intensive applications. Grid computing along with storage virtualization and server virtualization enables a Utility Computing. Applying the resources of many computers in a network to a single problem at the same time – usually a scientific or technical problem that requires a great number of computer processing cycles or access to large amounts of data. Grid computing uses software to divide and farm out pieces of a program to as many as several thousand computers. A number of corporations, professional groups and university consortia have developed frameworks and software for managing grid computing projects. Grid computing is a model for allowing companies to use a large number of computing resources on demand, no matter where they are located. Grid IR applies the tools of grid computing to IR to provide a common infrastructure for distributed IR. It also brings the capabilities of IR to grid computing. GRID IR is a newly proposed initiative to implement a specific architecture for realizing IR on the open grid service architecture (OGSA) grid-computing platform. Traditional IR models are broken into constituent pieces and described as OGSA grid services. A model for interaction among these services describes the GRID IR system.
- 2. AIM/OBJECTIVE OF THE SYSTEM The main aim of grid IR is to allow users information needs to be matched to documents by document collections, indexes and query engines which all exist as grid services. The project is implemented using JAVA. MS-ACCESS database is used for indexing the keywords of the document. PROPOSED SYSTEM SOFTWARE REQUIREMENTS Operating system : Windows XP/2000 Software : JDK 1.3 or higher Database : MS-ACCESS PROPOSED SYSTEM HARDWARE REQUIREMENTS Processor : Intel Pentium PIII or higher RAM : 128 MB or higher HDD : 80 GB HDD FDD : 1.44 MB or higher Monitor / Keyboard / CD drive PROPOSED SYSTEM DESCRIPTION Grid Computing is an advanced technology of distributed computing. A Grid is a collection of computers, storage and other devices, which are joined together by any means of communication like Internet and which can be used to manage information and solve their problems among themselves. Grid Computing allows usage of the unutilized resources of other systems. This is achieved by distributing the workload of the system to the other systems in order to use their unused resources such as their memory, processor, etc which results in balancing the workload, decreasing the network traffic, bandwidth, etc. This concept is used in our project to render a large image in a very short time by distributing the image to many systems for using their resources. As the workload is evenly distributed among the grid network, even the large work can be done in a short time itself. The main scope is that using the unused resources to complete the work efficiently. This project helps to use the resources efficiently and cost effective.
- 3. Grid Computing is about making large amounts of computing power available for applications and users. Collaborative development of Java Grid Engine technology provides the proper development framework to ensure that Grid Engine technology meets the requirements of the largest number of users. Grid computing is a form of networking. Unlike conventional networks that focus on communication among devices, grid computing harnesses unused processing cycles of all computers in a network for solving problems too intensive for any stand-alone machine. A common example of a well-known grid computing project is the SETI (Search for Extraterrestrial Intelligence) @Home project, in which PC users worldwide donate unused processor cycles to help the search for signs of extraterrestrial life by analyzing signals coming from outer space. The proposed project relies on individual users to volunteer to allow the project to harness the unused processing power of the user's computer. This method saves the project both money and resources. This project in Java based Grid computing does require special imaging software that is unique to the computing project for which the grid is being used. The basic idea of grid IR is to define an IR system in terms of three functional components, implemented as grid services: the collection manager service (CM), the indexing/searching service (IS), and the Query processing service (QP). These services are autonomous, and being grid services, they are distributed. Since they can be used to create new IR systems or link existing ones together in an interoperable network of IR services. Information retrieval(IR) is the science and practice of identifying documents or sub-documents that needs information needs. Usually, IR deals with textual documents in semi-structured (e.g., HTML, XML) or unstructured (plain text) format. In order to boost processing power, institutions aggregated computing resources across the entire institution. The same idea of sharing resources has paved the way for grid computing but with a far wider scale and scope. Grid computing, in effect, provides a global reach to distributed computing. It promises lower total computing costs along with on-demand, reliable, and inexpensive access to the vast, available computing resources that would other wise go unused.
- 4. GRID COMPUTING FEATURES The requirements for grid-computing infrastructure can be described by the following attributed: • Pooling of resources to increase utilization • Provisioning of work based on policies and dynamic requirements • Virtualization at every layer of the computing stack • Self-adaptive software that largely tunes and fixes itself • Unified management and provisioning. PROPOSED SYSTEM MODULES Java Grid project is divided into three modules server, client and worker 1. SERVER MODULE User interface Job Scheduler Workload Management Resource Management Data Management 2. WORKER MODULE Job Requests Receiver Job Processing Manager Job Requests Sender 3. CLIENT MODULE Job Fragmenter Job Requests Sender Job Results Receiver Job Results Aggregator
- 5. GRID - MODULE DESCRIPTION 1. SERVER MODULE Server module, which maintains the number of clients and worker connected to the grid engine, amount of work load given to the worker, add grid node, remove grid node, data available in the clients. 2. CLIENT MODULE The given job is divided into job fragments and given to the grid server to process, client aggregate the resultant job fragments form the grid server. The purpose of the client is to divide and aggregate the job. 3. WORKER MODULE Worker process the job given by the grid server and then result is send to the grid server. Worker module runs server automatically identifies and connect the worker to the grid engine. In this project worker process the job such as rendering of images using pov ray software. GRID – CLIENT GRID - WORKER G Job Fragmenter R I Job Requests D Job Requests Receiver Job Requests Sender S E R Job Processing Manager V E Job Results Receiver R Job Results Sender Job Results Aggregator