02-04-2011, 04:21 PM
Presented by:
E.Himaja
Y.N.Sowjanya
[attachment=11603]
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.
Key words:
Grid Security Interface (GSI), Global Access to Secondary Storage (GASS), Monitoring and Discovery Service (MDS), Globus Resource Allocation Manager (GRAM).
INTRODUCTION :
What's 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).
Although Grid computing is firmly ensconced in the realm of academic and research activities, more and more companies are starting to turn to it for solving hard-nosed, real-world problems.
IMPORTANCE OF GRID COMPUTING:
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.
TYPES OF GRID:
The three primary types of grids and are summarized below:
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.
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.
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.
OUR PROPOSED GRID MODEL:
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. Figure1 gives an idea about the Grid that we have proposed.
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.
CONCEPT OF OUR PROPOSED GRID:
In order to avoid this problem we have formulated our own Grid for such an access to the Internet via an Intranet (LAN). By using our Grid these large numbers of files are distributed evenly to all the systems in the Network by using our Grid. For example we have taken into account of a small LAN that consists of around 20 systems out of which 10 systems are idle and 5 systems are using less amount of CPU(for our consideration) and their CPU cycles are wasted. And our work begins here, as we are going to efficiently utilize those “wasted CPU cycles” into “working cycles”.
E.Himaja
Y.N.Sowjanya
[attachment=11603]
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.
Key words:
Grid Security Interface (GSI), Global Access to Secondary Storage (GASS), Monitoring and Discovery Service (MDS), Globus Resource Allocation Manager (GRAM).
INTRODUCTION :
What's 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).
Although Grid computing is firmly ensconced in the realm of academic and research activities, more and more companies are starting to turn to it for solving hard-nosed, real-world problems.
IMPORTANCE OF GRID COMPUTING:
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.
TYPES OF GRID:
The three primary types of grids and are summarized below:
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.
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.
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.
OUR PROPOSED GRID MODEL:
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. Figure1 gives an idea about the Grid that we have proposed.
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.
CONCEPT OF OUR PROPOSED GRID:
In order to avoid this problem we have formulated our own Grid for such an access to the Internet via an Intranet (LAN). By using our Grid these large numbers of files are distributed evenly to all the systems in the Network by using our Grid. For example we have taken into account of a small LAN that consists of around 20 systems out of which 10 systems are idle and 5 systems are using less amount of CPU(for our consideration) and their CPU cycles are wasted. And our work begins here, as we are going to efficiently utilize those “wasted CPU cycles” into “working cycles”.
