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To tackle complex and massive number of jobs sent by end users, a powerful and dedicated computational resources are required. Grid computing provides such environment in which applications may run for a quite long time. Therefore, efficient scheduling policy is indispensable. In our previous work, a mechanism named Swift Gap followed by developed completion time rule is introduced. This paper deeply...
Due to the rapid technological advancements, the Grid computing has emerged as a new field, distinguished from conventional distributed computing. The load balancing is considered to be very important in Grid systems. In this paper, we propose a new dynamic and distributed load balancing method called "Enhanced GridSim with Load Balancing based on Cost Estimation" (EGCE) for computational...
To generate large-scale resource management, grid based computing play a crucial role. It represents various geographically dispersed computational resources, i.e. workstations, PCs, cluster, storage devices, and database as fused integrated system, which can play dual roles of synchronized resource donator and consumer in such distributed computation environment. Now a day, in ubiquitous environment...
Cloud computing is an innovative technology that mainly relies on sharing of computing resources, data as well as information over the internet. Cloud computing has been evolved from technological growth in Grid systems, Virtualization and Web2.0. Efficient Load Balancing (LB) and scheduling techniques are required for optimal utilization of computing resources and to reduce turnaround time. Load...
Grid computing is a collection of computer resources from multiple locations to reach a common goal. Grid computing distinguishes from conventional high performance computing systems that are heterogeneous and geographically dispersed than cluster computer. One of the major issues in grid computing is load balancing. Classification of load balancing is: Static - Dynamic, Centralized - Decentralized,...
Grid-based Massive dataset search systems integrate many processes to search for a large number of shared datasets distributed over several locations. The implementation of the search mechanism to deal with these distributed dataset greatly affected the system performance. However, the execution of the search over the grid requires someone with grid knowledge and expertise. Consequently, this issue...
Computing intensive applications are an important family of applications in distributed computing domain. They have been object of study using different distributed computing paradigms and infrastructures. Such applications distinguish for their demanding needs for CPU computing, independently of the amount of data associated with the problem instance. Among computing intensive applications, there...
In the last few years there has been tremendous increase in the storage and processing of data, with significant speed and storage space requirements. Medical image storage and retrieval is one such application which requires huge storage space and not easily solved by computers. The researchers who work in the area of medical image processing deal with a high degree of storage and retrieval of medical...
The numerical size of academic publications that are being published in recent years had grown rapidly. Accessing and searching massive academic publications that are distributed over several locations need large amount of computing resources to increase the system performance. Therefore, many grid-based search techniques were proposed to provide flexible methods for searching the distributed extensive...
In this paper, a hierarchical load balancing technique has been presented, which is based on variable threshold value. Through this paper, an attempt has been made to solve the problem of load balancing while maintaining the resource utilization and response time with the help of sender initiative policy. The proposed technique is suitable for dynamic and decentralized Grid environments. The load...
To improve the global throughput of grid environments, workloads have to be evenly balanced among the available resources. However for computational grid we must address main new issues. Like heterogeneous autonomy, dynamicity and so forth. A framework consisting of distributed dynamic load balancing algorithm in perspective to minimize the average response time of tasks. The main goal is to prevent,...
Databases are normally designed to support a specific application domain, and the globalization process brings new issues to integrate data from more than one database. This paper proposes an architecture to integrating databases, by demonstrating a method for integrating semantically heterogeneous databases with a single tool and grid computing technology, which enables access to different databases...
Increasing data volume in the database of organizations especially those that are multicluster and geographically extensive cause a lot of problems in data storage, retrieve and transmition. In addition, data integration related to database existed in different geographical positions is too risky with the respect of security and velocity of transaction executing and generally posses some disadvantages...
Resource co-allocation is a crucial but challenging problem for Grid Computing. With the emergence of WS-Resource Framework and Open Grid Services Architecture, resource co-allocation is commonly associated with a service level agreement (SLA) to determine the achieved QoS level. In this paper, we present an approach for resource co-allocation in Multi-cluster Grid that maximizes the user satisfaction...
The Grid computing vision promises to provide the required platform for users to run a new and more demanding range of high performance computing (HPC) applications. However, the performance i.e. the response times achievable from the grid systems, is reported as not very satisfactory. End users may be forced to purchase, maintain and upgrade their own dedicated HPC systems for the execution of their...
Traditional grid networks employ general purpose processors (GPPs) as their main processing elements. Incorporating reconfigurable processing elements in such networks can be a promising technology to increase their performance and flexibility. Many grid networks, such as Tera Grid, are already utilizing reconfigurable hardware resource as a processing element. In this paper, we propose queuing models...
Grid computing aims at offering standardized access to heterogeneous and distributed resources for scientific communities. However, in order to support emerging next generation Grid applications with specific Quality of Service requirements, the interconnecting networks have also been considered as first-class allocable Grid resources and have been also taken into account for the co-scheduling process...
In the past decade, many enterprise information systems (EIS) have been developed with enormous resources, such as a dedicated server per application (http, email, DNS, File, SMS, backup, etc). Thus, the overall utilization of EIS is low in compared with its resources, especially the servers. In this paper, we present a practical way to increase the utilization of EIS by consolidating many of the...
Data grid provides scalable infrastructure for storage resource and data files management, which supports several scientific applications. Replication is a technique used in data grid to improve the applications'response time and to reduce the bandwidth consumption. An important problem to be addressed is when replication should be trigged. In this paper, we propose a model for a dynamic period that...
Grid has been proved to be a promising technology for integrating heterogeneous resources. However, with the emerging of various Grid middle wares, the heterogeneous problem also occurs for Grid middleware themselves, as well as for the Grid services developed on those middle wares, which is an obstacle for the interoperation. SOA(Service Oriented Architecture) has been introduced into the development...
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