Abstract: Job Scheduling plays an important role for efficient
utilization of grid resources available across different domains and
geographical zones. Scheduling of jobs is challenging and NPcomplete.
Evolutionary / Swarm Intelligence algorithms have been
extensively used to address the NP problem in grid scheduling.
Artificial Bee Colony (ABC) has been proposed for optimization
problems based on foraging behaviour of bees. This work proposes a
modified ABC algorithm, Cluster Heterogeneous Earliest First Min-
Min Artificial Bee Colony (CHMM-ABC), to optimally schedule
jobs for the available resources. The proposed model utilizes a novel
Heterogeneous Earliest Finish Time (HEFT) Heuristic Algorithm
along with Min-Min algorithm to identify the initial food source.
Simulation results show the performance improvement of the
proposed algorithm over other swarm intelligence techniques.
Abstract: This paper describes a logical method to enhance
security on the grid computing to restrict the misuse of the grid
resources. This method is an economic and efficient one to avoid the
usage of the special devices. The security issues, techniques and
solutions needed to provide a secure grid computing environment are
described. A well defined process for security management among
the resource accesses and key holding algorithm is also proposed. In
this method, the identity management, access control and
authorization and authentication are effectively handled.
Abstract: Cloud computing is a style of computing which is formed from the aggregation and development of technologies such as grid computing distributed computing, parallel computing and service-oriented architecture. And its aim is to provide computing, communication and storage resources in a safe environment based on service, as fast as possible, which is virtually provided via Internet platform. Considering that the provided Services in e-government are available via the Internet, thus cloud computing can be used in the implementation of e-government architecture and provide better service with the lowest economic cost using its benefits. In this paper, the Methods of using cloud computing in e-government has been studied and it's been attempted to identify the challenges and benefits of the cloud to get used in the e-government and proposals have been offered to overcome its shortcomings, encourage and partnership of governments and people to use this economical and new technology.
Abstract: Certain sciences such as physics, chemistry or biology,
have a strong computational aspect and use computing infrastructures
to advance their scientific goals. Often, high performance and/or high
throughput computing infrastructures such as clusters and computational
Grids are applied to satisfy computational needs. In addition,
these sciences are sometimes characterised by scientific collaborations
requiring resource sharing which is typically provided by Grid
approaches. In this article, I discuss Grid computing approaches in
High Energy Physics as well as in bioinformatics and highlight some
of my experience in both scientific domains.
Abstract: A computer cluster is a group of tightly coupled
computers that work together closely so that in many respects they
can be viewed as though they are a single computer. The components
of a cluster are commonly, but not always, connected to each other
through fast local area networks. Clusters are usually deployed to
improve performance and/or availability over that provided by a
single computer, while typically being much more cost-effective than
single computers of comparable speed or availability. This paper
proposed the way to implement the Beowulf Cluster in order to
achieve high performance as well as high availability.
Abstract: Within the last years, several technologies have been developed to help building e-learning portals. Most of them follow approaches that deliver a vast amount of functionalities, suitable for class-like learning. The SuGI project, as part of the D-Grid (funded by the BMBF), targets on delivering a highly scalable and sustainable learning solution to provide materials (e.g. learning modules, training systems, webcasts, tutorials, etc.) containing knowledge about Grid computing to the D-Grid community. In this article, the process of the development of an e-learning portal focused on the requirements of this special user group is described. Furthermore, it deals with the conceptual and technical design of an e-learning portal, addressing the special needs of heterogeneous target groups. The main focus lies on the quality management of the software development process, Web templates for uploading new contents, the rich search and filter functionalities which will be described from a conceptual as well as a technical point of view. Specifically, it points out best practices as well as concepts to provide a sustainable solution to a relatively unknown and highly heterogeneous community.
Abstract: This paper describes the authorization system
architecture for Pervasive Grid environment. It discusses the
characteristics of classical authorization system and requirements of
the authorization system in pervasive grid environment as well.
Based on our analysis of current systems and taking into account the
main requirements of such pervasive environment, we propose new
authorization system architecture as an extension of the existing grid
authorization mechanisms. This architecture not only supports user
attributes but also context attributes which act as a key concept for
context-awareness thought. The architecture allows authorization of
users dynamically when there are changes in the pervasive grid
environment. For this, we opt for hybrid authorization method that
integrates push and pull mechanisms to combine the existing grid
authorization attributes with dynamic context assertions. We will
investigate the proposed architecture using a real testing environment
that includes heterogeneous pervasive grid infrastructures mapped
over multiple virtual organizations. Various scenarios are described
in the last section of the article to strengthen the proposed mechanism
with different facilities for the authorization procedure.
Abstract: Grid computing provides a virtual framework for
controlled sharing of resources across institutional boundaries.
Recently, trust has been recognised as an important factor for
selection of optimal resources in a grid. We introduce a new method
that provides a quantitative trust value, based on the past interactions
and present environment characteristics. This quantitative trust value
is used to select a suitable resource for a job and eliminates run time
failures arising from incompatible user-resource pairs. The proposed
work will act as a tool to calculate the trust values of the various
components of the grid and there by improves the success rate of the
jobs submitted to the resource on the grid. The access to a resource
not only depend on the identity and behaviour of the resource but
also upon its context of transaction, time of transaction, connectivity
bandwidth, availability of the resource and load on the resource. The
quality of the recommender is also evaluated based on the accuracy
of the feedback provided about a resource. The jobs are submitted for
execution to the selected resource after finding the overall trust value
of the resource. The overall trust value is computed with respect to
the subjective and objective parameters.
Abstract: In Virtual organization, Knowledge Discovery (KD)
service contains distributed data resources and computing grid nodes.
Computational grid is integrated with data grid to form Knowledge
Grid, which implements Apriori algorithm for mining association
rule on grid network. This paper describes development of parallel
and distributed version of Apriori algorithm on Globus Toolkit using
Message Passing Interface extended with Grid Services (MPICHG2).
The creation of Knowledge Grid on top of data and
computational grid is to support decision making in real time
applications. In this paper, the case study describes design and
implementation of local and global mining of frequent item sets. The
experiments were conducted on different configurations of grid
network and computation time was recorded for each operation. We
analyzed our result with various grid configurations and it shows
speedup of computation time is almost superlinear.
Abstract: Resource Discovery in Grids is critical for efficient
resource allocation and management. Heterogeneous nature and
dynamic availability of resources make resource discovery a
challenging task. As numbers of nodes are increasing from tens to
thousands, scalability is essentially desired. Peer-to-Peer (P2P)
techniques, on the other hand, provide effective implementation of
scalable services and applications. In this paper we propose a model
for resource discovery in Condor Middleware by using the four axis
framework defined in P2P approach. The proposed model enhances
Condor to incorporate functionality of a P2P system, thus aim to
make Condor more scalable, flexible, reliable and robust.
Abstract: Recently, grid computing has been widely focused on
the science, industry, and business fields, which are required a vast
amount of computing. Grid computing is to provide the environment
that many nodes (i.e., many computers) are connected with each
other through a local/global network and it is available for many
users. In the environment, to achieve data processing among nodes
for any applications, each node executes mutual authentication by
using certificates which published from the Certificate Authority
(for short, CA). However, if a failure or fault has occurred in the
CA, any new certificates cannot be published from the CA. As
a result, a new node cannot participate in the gird environment.
In this paper, an off-the-shelf scheme for dependable grid systems
using virtualization techniques is proposed and its implementation is
verified. The proposed approach using the virtualization techniques
is to restart an application, e.g., the CA, if it has failed. The system
can tolerate a failure or fault if it has occurred in the CA. Since
the proposed scheme is implemented at the application level easily,
the cost of its implementation by the system builder hardly takes
compared it with other methods. Simulation results show that the
CA in the system can recover from its failure or fault.
Abstract: Cloud Computing is a new technology that helps us to
use the Cloud for compliance our computation needs. Cloud refers to a scalable network of computers that work together like Internet. An
important element in Cloud Computing is that we shift processing, managing, storing and implementing our data from, locality into the
Cloud; So it helps us to improve the efficiency. Because of it is new
technology, it has both advantages and disadvantages that are
scrutinized in this article. Then some vanguards of this technology
are studied. Afterwards we find out that Cloud Computing will have
important roles in our tomorrow life!
Abstract: According to development of communications and
web-based technologies in recent years, e-Learning has became very
important for everyone and is seen as one of most dynamic teaching
methods.
Grid computing is a pattern for increasing of computing power
and storage capacity of a system and is based on hardware and
software resources in a network with common purpose. In this article
we study grid architecture and describe its different layers. In this
way, we will analyze grid layered architecture. Then we will
introduce a new suitable architecture for e-Learning which is based
on grid network, and for this reason we call it Grid Learning
Architecture. Various sections and layers of suggested architecture
will be analyzed; especially grid middleware layer that has key role.
This layer is heart of grid learning architecture and, in fact,
regardless of this layer, e-Learning based on grid architecture will
not be feasible.
Abstract: In today-s new technology era, cluster has become a
necessity for the modern computing and data applications since many
applications take more time (even days or months) for computation.
Although after parallelization, computation speeds up, still time
required for much application can be more. Thus, reliability of the
cluster becomes very important issue and implementation of fault
tolerant mechanism becomes essential. The difficulty in designing a
fault tolerant cluster system increases with the difficulties of various
failures. The most imperative obsession is that the algorithm, which
avoids a simple failure in a system, must tolerate the more severe
failures. In this paper, we implemented the theory of watchdog timer
in a parallel environment, to take care of failures. Implementation of
simple algorithm in our project helps us to take care of different
types of failures; consequently, we found that the reliability of this
cluster improves.
Abstract: In Grid computing, a data transfer protocol called
GridFTP has been widely used for efficiently transferring a large volume
of data. Currently, two versions of GridFTP protocols, GridFTP
version 1 (GridFTP v1) and GridFTP version 2 (GridFTP v2), have
been proposed in the GGF. GridFTP v2 supports several advanced
features such as data streaming, dynamic resource allocation, and
checksum transfer, by defining a transfer mode called X-block mode.
However, in the literature, effectiveness of GridFTP v2 has not been
fully investigated. In this paper, we therefore quantitatively evaluate
performance of GridFTP v1 and GridFTP v2 using mathematical
analysis and simulation experiments. We reveal the performance
limitation of GridFTP v1, and quantitatively show effectiveness of
GridFTP v2. Through several numerical examples, we show that by
utilizing the data streaming feature, the average file transfer time of
GridFTP v2 is significantly smaller than that of GridFTP v1.
Abstract: Grid computing provides an effective infrastructure for massive computation among flexible and dynamic collection of individual system for resource discovery. The major challenge for grid computing is to prevent breaches and secure the data from trespassers. To overcome such conflicts a semantic approach can be designed which will filter the access requests of peers by checking the resource description specifying the data and the metadata as factual statements. Between every node in the grid a semantic firewall as a middleware will be present The intruder will be required to present an application specifying there needs to the firewall and hence accordingly the system will grant or deny the application request.
Abstract: Long term rainfall analysis and prediction is a
challenging task especially in the modern world where the impact of
global warming is creating complications in environmental issues.
These factors which are data intensive require high performance
computational modeling for accurate prediction. This research paper
describes a prototype which is designed and developed on grid
environment using a number of coupled software infrastructural
building blocks. This grid enabled system provides the demanding
computational power, efficiency, resources, user-friendly interface,
secured job submission and high throughput. The results obtained
using sequential execution and grid enabled execution shows that
computational performance has enhanced among 36% to 75%, for
decade of climate parameters. Large variation in performance can be
attributed to varying degree of computational resources available for
job execution.
Grid Computing enables the dynamic runtime selection, sharing
and aggregation of distributed and autonomous resources which plays
an important role not only in business, but also in scientific
implications and social surroundings. This research paper attempts to
explore the grid enabled computing capabilities on weather indices
from HOAPS data for climate impact modeling and change
detection.
Abstract: Grid computing is a group of clusters connected over
high-speed networks that involves coordinating and sharing
computational power, data storage and network resources operating
across dynamic and geographically dispersed locations. Resource
management and job scheduling are critical tasks in grid computing.
Resource selection becomes challenging due to heterogeneity and
dynamic availability of resources. Job scheduling is a NP-complete
problem and different heuristics may be used to reach an optimal or
near optimal solution. This paper proposes a model for resource and
job scheduling in dynamic grid environment. The main focus is to
maximize the resource utilization and minimize processing time of
jobs. Grid resource selection strategy is based on Max Heap Tree
(MHT) that best suits for large scale application and root node of
MHT is selected for job submission. Job grouping concept is used to
maximize resource utilization for scheduling of jobs in grid
computing. Proposed resource selection model and job grouping
concept are used to enhance scalability, robustness, efficiency and
load balancing ability of the grid.
Abstract: We discuss the application of matching in the area of resource discovery and resource allocation in grid computing. We present a formal definition of matchmaking, overview algorithms to evaluate different matchmaking expressions, and develop a matchmaking service for an intelligent grid environment.
Abstract: Grid computing is a form of distributed computing
that involves coordinating and sharing computational power, data
storage and network resources across dynamic and geographically
dispersed organizations. Scheduling onto the Grid is NP-complete,
so there is no best scheduling algorithm for all grid computing
systems. An alternative is to select an appropriate scheduling
algorithm to use in a given grid environment because of the
characteristics of the tasks, machines and network connectivity. Job
and resource scheduling is one of the key research area in grid
computing. The goal of scheduling is to achieve highest possible
system throughput and to match the application need with the
available computing resources. Motivation of the survey is to
encourage the amateur researcher in the field of grid computing, so
that they can understand easily the concept of scheduling and can
contribute in developing more efficient scheduling algorithm. This
will benefit interested researchers to carry out further work in this
thrust area of research.