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Peer-to-peer model is one of the commonly used model for distributed computing. Some of the peers are having demand for certain resources some others may be having additional capacity of resources. Peers may have limitations on the number of concurrent connections (degree). In the present work allocation problem of peers having demand, capacity and degree is considered. The problem is to find an allocation...
Data Grids provide services and infrastructure for distributed data-intensive applications accessing massive geographically distributed datasets. An important technique to speed access in Data Grids is replication, which provides nearby data access. Much of the work on the replica placement problem has focused on average system performance and ignored quality assurance issues. In a data grid environment,...
Data grids support distributed data-intensive applications that need to access massive datasets stored around the world. Ensuring efficient access to such datasets is hindered by the high latencies of wide-area networks. To speed up access, files can be replicated so a user can access a nearby replica. Replication also provides improved availability, decreased bandwidth use, increased fault tolerance,...
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 geographically distributed storage resources for large-scale data-intensive applications that generate large data sets. Because data is the important resource in data grids, an efficient management is needed to minimize the response time of applications. Replication is typically used in data grids to improve access time and to reduce the bandwidth consumption. In this paper, we...
Load balancing is one of the critical issues that must be considered in managing a grid computing environment. It is complicated due to the distributed and heterogeneous nature of the resources. An enhanced ant algorithm for load balancing in grid computing is proposed in this paper. The proposed algorithm will determine the best resource to be allocated to the jobs based on job characteristics and...
Formerly computer application development just develops in one computer with one application, if one user wants to use some application in other computer (e.g. a computer or device) then the computer or device must be deployed or reinstalled the application in another computer. As a result, due to improve this problem, many application developer start redesign or translate elder application as Web...
In this paper, we study the impact of tasks reallocation onto a multi-cluster environment where clusters are heterogeneous and use different resources management policies. In this context, we propose a reallocation mechanism that migrates waiting jobs from one cluster to another. We performed simulations using real traces to study benefits of reallocations. We compared two algorithms providing the...
In grid computing, load balancing is a technique to distribute workload evenly across two or more computing nodes, in order to get optimal resource utilization, maximize throughput, minimize response time, and avoid overload. This paper takes advantages of genetic algorithm, brings forward a novel heuristic genetic load balancing algorithm and applied to solve grid computing load balancing problem...
Grid technology is the next evolutionary level in the field of distributed systems. This technology issued to create the illusion of a super computer by connecting a number of heterogeneous systems to share various kinds of resources and to solve large scale problems. Grid technology, with SOA architecture has lead to the virtualization of almost every real life activity. Data Grid is one such, which...
Data are special kinds of resource in grid, and their flow, management and uniform view play an important role in the grid system. This paper presents a dynamic adaptive data transfer model based on multiple replicas in the grid environment, compared with the traditional data transfer method based on single replica, the experimental results show that this model has a better transfer performance.
In dynamic grid environment, distribute a large number of different types of services and resources. F fast and accurate resource and service discovery, this article proposes a new structured Gossip messages spread algorithm, called S-Gossip, this algorithm has good redundancy and completeness. We describes in detail the implementation of the algorithm and protocol, and on this basis, the establishment...
Scheduling jobs to resources in grid computing is complicated due to the distributed and heterogeneous nature of the resources. Stagnation in grid computing system may occur when all jobs require or are assigned to the same resources. This will lead to resources having high workload and stagnation may occur if computational times of the processed jobs are high. This paper proposed an enhanced ant...
In this paper, we study the importance of languages for the specification of algorithms in high performance Grid computing. We present one such language, the Algorithm Definition Language (ADL), designed and implemented for the use in conjunction with SmartGridSolve. We demonstrate that the use of this type of language can significantly improve the performance of Grid applications. We discuss how...
Grid computing has a significant impact on the next generation information infrastructure where job schedules plan an important role. High performance grid schedule must select the appropriate resources which meet the requirement of the clients and ensure the jobs can be finished within deadline. However, current time-based grid schedule only consider part of the time factors to estimate the job execution...
There are many research make use of grid computing to solve large-scale problems and produced at a tremendous velocity and volume from scientific experiments in the fields of high energy physics, molecular docking, computer micro-tomography and many others. Distribute fairly available resources is one of the problem in grid computing and economy model is a way to solve those problems about distribute...
The size of grid systems has increased substantially in the last decades. Resource discovery in grid systems is a fundamental task which provides searching and locating necessary resources for a given process. Various different approaches are proposed in literature for this problem. Grid resource discovery using Web services is an important approach which has resulted in many tools to become de facto...
In this paper, we study the impact of task reallocations/migrations on a grid platform, composed of parallel resources, each supervised by a batch scheduler. Results of simulations using real life traces show that gains of 40% can be attained on the average waiting time of jobs even if tasks are initially mapped by a meta-scheduler on the cluster giving the best completion time.
The large sized data sets are replicated in more than one site for the better availability to the nodes in a grid. Downloading the dataset from these replicated locations have practical difficulties, due to network traffic, congestion, frequent change-in performance of the servers, etc. In order to speed up the download, complex server selection techniques, network and server loads are used. However,...
In a file system, critical sections are represented by means of read or write operations on useful data (i.e files) as well as metadata of the system. The processes must be synchronized to reach these shared resources, thanks to mutual exclusion algorithms which guarantee data consistency. In a grid environment, processes are compared to grid nodes and their synchronization is ensured by the sending...
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