ABSTRACT

Today we are in the Internet world and everyone prefers to enjoy fast access to the Internet. But due to multiple downloading, there is a chance that the system hangs up or slows down the performance that leads to the restarting of the entire process from the beginning. This is one of the serious problems that need the attention of the researchers.

So we have taken this problem for our research and in this paper we are providing a layout for implementing our proposed Grid Model that can access the Internet very fast. By using our Grid we can easily download any number of files very fast depending on the number of systems employed in the Grid. We have used the concept of Grid Computing for this purpose.

The Grid formulated by us uses the standard Globus Architecture, which is the only Grid Architecture currently used world wide for developing the Grid. And we have proposed an algorithm for laying our Grid Model that we consider as a blueprint for further implementation. When practically implemented, our Grid provides the user to experience the streak of lightening over the Internet while downloading multiple files.

CONTENTS

v Introduction – Grid Computing

v Grid’s Conceptual Vision

v Why Grid and Why Now

v Grid’s & Types

v Grid Model Proposed

v Problem due to Multiple Down Loading

v EMPLOYING THE GLOBUS ARCHITECTURE IN OUR GRID

v ACCESSING THE INTRANET GRID

v PROPOSED ALGORITHM FOR INTRANET PROPOSED GRID

v BENEFITS OF GRID COMPUTING

v CONCLUSION

Introduction – Grid Computing

Grid Computing is a technique in which the idle systems in the Network and their “ wasted “ CPU cycles can be efficiently used by uniting pools of servers, storage systems and networks into a single large virtual system for resource sharing dynamically at runtime. These systems can be distributed across the globe; they're heterogeneous (some PCs, some servers, maybe mainframes and supercomputers); somewhat autonomous (a Grid can potentially access resources in different organizations).

STRUCTURE OF A GRID – AN EXAMPLE

The term “GRID” was given in the mid 1990’s to denote a proposed distributed computing infrastructure for Advanced Science and Engineering. It can be defined as, “Resource sharing & coordinating problem solving in dynamic, multi-institutional virtual organizations”.

Grid’s Conceptual Vision

Grid computing is emerging as a viable technology that businesses can use to wring more profits and productivity out of IT resources -- and it's going to be up to you developers and administrators to understand Grid computing and put it to work.

It's really more about bringing a problem to the computer (or Grid) and getting a solution to that problem. Grid computing is flexible, secure, coordinated resource sharing among dynamic collections of individuals, institutions, and resources. Grid computing enables the virtualization of distributed computing resources such as processing, network bandwidth, and storage capacity to create a single system image, granting users and applications seamless access to vast IT capabilities. Just as an Internet user views a unified instance of content via the World Wide Web, a Grid user essentially sees a single, large, virtual computer.

Grid computing will give worldwide access to a network of distributed resources - CPU cycles, storage capacity, devices for input and output, services, whole applications, and more abstract elements like licenses and certificates.

For example, to solve a compute-intensive problem, the problem is split into multiple tasks that are distributed over local and remote systems, and the individual results are consolidated at the end. Viewed from another perspective, these systems are connected to one big computing Grid. The individual nodes can have different architectures, operating systems, and software versions. Some of the target systems can be clusters of nodes themselves or high performance servers.

Why Grid and Why Now

· Civil engineers collaborate to design, execute, & analyze shake table experiments

· Climate scientists visualize, annotate, & analyze terabyte simulation datasets

· An emergency response team couples real time data, weather model, population data

· A multidisciplinary analysis in aerospace couples code and data in four companies

· Scientists working for a multinational soap company design a new product

The following are the reasons why now we are concentrating on Grids:

· Moore’s law improvements in computing produce highly functional end systems.

· The Internet and burgeoning wired and wireless provide universal connectivity.

· Changing modes of working and problem solving emphasize teamwork, computation

· Network exponentials produce dramatic changes in geometry and geography.

Grid’s & Types

The three primary types of grids and are summarized below:

1. Computational grid

A computational grid is focused on setting aside resources specifically for computing power. In this type of grid, most of the machines are high-performance servers.

2. Scavenging grid

A scavenging grid is most commonly used with large numbers of desktop machines. Machines are scavenged for available CPU cycles and other resources. Owners of the desktop machines are usually given control over when their resources are available to participate in the grid.

3. Data grid

A data grid is responsible for housing and providing access to data across multiple organizations. Users are not concerned with where this data is located as long as they have access to the data.

Grid Model Proposed

We are using the Scavenging Grid for our implementation as large numbers of desktop machines are used in our Grid and later planning to extend it by using both Scavenging and data Grid. Figure2 gives an idea about the Grid that we have proposed.

Fig:Layout of our Intranet Grid

PROBLEMS DUE TO MULTIPLE DOWNLOADING

While accessing Internet most of us might have faced the burden of multiple downloading and in particular with downloading huge files i.e., there can be a total abrupt system failure while a heavy task is assigned to the system. The system may hang up and may be rebooted while some percentage of downloading might have been completed. This rebooting of the system leads to download of the file once again from the beginning, which is one of the major problems everyone is facing today.

Let us consider N numbers of files of different sizes (in order of several MBs) are being downloaded on a single system (a PC). This will take approximately some minutes or even some hours to download it by using an Internet connection of normal speed with a single CPU. This is one of the tedious tasks for the user to download multiple files at the same time. Our Grid plays a major role here.

EMPLOYING THE GLOBUS ARCHITECTURE IN PROPOSED GRID

While planning to implement a Grid project, we must address issues like security, managing and brokering the workload, and managing data and resources information. Most Grid applications contain a tight integration of all these components.

The Globus Project provides open source software tools that make it easier to build computational Grids and Grid-based applications. These tools are collectively called the Globus Toolkit. Globus Toolkit is the open source Grid technology for computing and data Grids. On the server side, Globus Toolkit 2.2 provides interfaces in C. On the client side, it provides interfaces in C, Java language, and other languages. On the client side, the Java interfaces are provided by the Java Commodity Grid (CoG) Kit. Globus runs on Linux, AIX, HP-UX, Solaris, and also on windows operating systems.

The Globus architecture represents a multiple-layer model. The local services layer contains the operating system services and network services like TCP/IP. In addition, there are the services provided by cluster scheduling software (like IBM Load Leveler) -- job-submission, query of queues, and so forth. The cluster scheduling software allows a better use of the existing cluster resources. The higher layers of the Globus model enable the integration of multiple or heterogeneous clusters.

ACCESSING THE INTRANET GRID

When any user wants to access our proposed Intranet Grid in order to download multiple files over the Internet, then he should follow certain procedures that we consider necessary for the security of our Grid. The main Requirements for Processing in Grid Environment are:

· Security: Single sign-on, authentication, authorization, and secure data transfer.

· Resource Management: Remote job submission and management.

· Data Management: Secure and robust data movement.

· Information Services: Directory services of available resources and their status.

· Fault Detection: Checking the intranet.

· Portability: C bindings (header files) needed to build and compile programs.

PROPOSED ALGORITHM FOR INTRANET PROPOSED GRID

Steps to perform multiple downloading in the Grid, The host details are got from the server of the LAN in order to identify the various hosts.

The host information is got whenever needed on the priority queue basis.

//module for downloading files

[1]. Start lookup // look for file size and resource information

[2]. Declare nres, nfile // no of resources available and no of files

[3]. Input nres, nfiles

[4]. Input size // the file size

[5]. Initialize P1 à res info // store the resource information in priority queue P1 with highest system configuration as priority

[6]. Initialize P2 à file size // store the file information in the priority queue P2 with maximum file size as priority

[7]. If condition (nfiles == nres) // check whether the no of resources is equal to no of files

[8]. Initialize counter

[9]. For (counter =1; counter <= nres; counter++) // initialize the loop to assign the files.

[10]. Assign the 1^st file of P2 to the 1^st node in P1. // first node will be node with highest configuration and first file will be the file with maximum size.

[11]. Start processing // files directed to the appropriate system for accessing their wasted CPU cycles.

[12]. Loop

[13]. Else:

[14]. Start timer

[15]. Delay à 1 min

[16]. Collect incoming files // the files that the user clicked to download in this duration.

[17]. Assign the files à P2

[18]. Goto step 8

[19]. Goto step 1

[20]. End // when the user exits from proposed Grid.

BENEFITS OF GRID COMPUTING

• Grid computing enables organizations to aggregate resources within an entire IT infrastructure no matter where in the world they are located. It eliminates situations where one site is running on maximum capacity, while others have cycles to spare.
• Grid computing enables companies to access and share remote databases. This is especially beneficial to the life sciences and research communities, where enormous volumes of data are generated and analysed during any given day.
• Grid computing enables widely dispersed organizations to easily collaborate on projects by creating the ability to share everything from software applications and data, to engineering blueprints.
• Grid computing can create a more robust and resilient IT infrastructure better able to respond to minor or major disasters.
• A grid can harness the idle processing cycles that are available in desktop PCs located in various locations across multiple time zones. For example, PCs that would typically remain idle overnight at a company's Tokyo manufacturing plant could be utilized during the day by its North American operations.

CONCLUSION

Grid computing was once said to be fading out but due to the technological convergence it is blooming once again and the Intranet Grid we have proposed adds a milestone for the Globalization of Grid Architecture, which, leads to the hasty computing that is going to conquer the world in the nearest future. By implementing our proposed Intranet Grid it is very easy to download multiple files very fast and no need to worry about the security as we are authenticating each and every step taking place in our Grid and in particular user to access the database. Further implementations could be carried out in the nearest future.

BIBILIOGRAPHY

Ø The Globus Alliance, The Globus Toolkit 3.0.

Ø Foster, I. and Kesselman, C., The GRID: Blueprint for a New Computing Infrastructure. Morgan-Kaufmann, 1999.

Ø Foster, I, Kesselman, C, Nick, J.M., and Tuecke, S. The Physiology of the Grid: An Open Grid Services Architecture for Distributed Systems Integration.

WEB REFERENCES

• www.Globus.org
• www.GridForum.org
• www.gridcomputingplanet.com
• www.globus.org/ogsa.2002