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دسترسی آزاد مقاله
1 - Reliability and Availability Improvement in Economic Data Grid Environment Based On Clustering Approach
Ali Abbasi Amir Masoud Rahmani Esmaeil Zeinali KhasraghiAbstract - One of the important problems in grid environments is data replication in grid sites. Reliability and availability of data replication in some cases is considered low. To separate sites with high reliability and high availability of sites with low availabilit چکیده کاملAbstract - One of the important problems in grid environments is data replication in grid sites. Reliability and availability of data replication in some cases is considered low. To separate sites with high reliability and high availability of sites with low availability and low reliability, clustering can be used. In this study, the data grid dynamically evaluate and predict the condition of the sites. The reliability and availability of sites were calculated and it was used to make decisions to replicate data. With these calculations, we have information on the locations of users in grid with reliability and availability or cost commensurate with the value of the work they did. This information can be downloaded from users who are willing to send them data with suitable reliability and availability. Simulation results show that the addition of the two parameters, reliability and availability, assessment criteria have been improved in certain access patterns. پرونده مقاله -
دسترسی آزاد مقاله
2 - E2DR: Energy Efficient Data Replication in Data Grid
Kobra Bagheri Mehran MohsenzadehAbstract— Data grids are an important branch of gird computing which provide mechanisms for the management of large volumes of distributed data. Energy efficiency has recently emerged as a hot topic in large distributed systems. The development of computing system چکیده کاملAbstract— Data grids are an important branch of gird computing which provide mechanisms for the management of large volumes of distributed data. Energy efficiency has recently emerged as a hot topic in large distributed systems. The development of computing systems is traditionally focused on performance improvements driven by the demand of client's applications in scientific and business domains. High energy consumption in computer systems leads to their limited performance because of the increased consumption of carbon dioxide and amount of electricity bills. Thus, the goal of design of computer systems has been shifted to power and energy efficiency. Data grids can solve large scale applications that require a large amount of data. Data replication is a common solution to improve availability and file access time in such environments. This solution replicates the data file in many different sites. In this paper, a new data replication method is proposed that is not only data aware, but also is energy efficient. Simulation results with CLOUDSIM show that the proposed method gives better energy consumption, average response time, and network usage than other algorithms and prevents the unnecessary creation of replica, which leads to efficient storage usage. پرونده مقاله -
دسترسی آزاد مقاله
3 - Dynamic Replication based on Firefly Algorithm in Data Grid
mehdi SadeghzadehIn data grid, using reservation is accepted to provide scheduling and service quality. Users need to have an access to the stored data in geographical environment, which can be solved by using replication, and an action taken to reach certainty. As a result, users are d چکیده کاملIn data grid, using reservation is accepted to provide scheduling and service quality. Users need to have an access to the stored data in geographical environment, which can be solved by using replication, and an action taken to reach certainty. As a result, users are directed toward the nearest version to access information. The most important point is to know in which sites and distributed system the produced versions are located. By selecting a suitable place for versions, the versions having performance, efficiency and lower access time are used. In this study, an efficient method is presented to select the best place for those versions created in data grid by using the users’ firefly algorithm which is compared with cooling algorithm. Results show that firefly algorithm has better performance than others.This means firefly algorithm is better and more accurate than genetic algorithm and particle swarm optimization in data replication task. پرونده مقاله -
دسترسی آزاد مقاله
4 - Data Replication-Based Scheduling in Cloud Computing Environment
Bahareh Rahmati Amir Masoud Rahmani Ali RezaeiAbstract— High-performance computing and vast storage are two key factors required for executing data-intensive applications. In comparison with traditional distributed systems like data grid, cloud computing provides these factors in a more affordable, scalable a چکیده کاملAbstract— High-performance computing and vast storage are two key factors required for executing data-intensive applications. In comparison with traditional distributed systems like data grid, cloud computing provides these factors in a more affordable, scalable and elastic platform. Furthermore, accessing data files is critical for performing such applications. Sometimes accessing data becomes a bottleneck for the whole cloud workflow system and decreases the performance of the system dramatically. Job scheduling and data replication are two important techniques which can enhance the performance of data-intensive applications. It is wise to integrate these techniques into one framework for achieving a single objective. In this paper, we integrate data replication and job scheduling with the aim of reducing response time by reduction of data access time in cloud computing environment. This is called data replication-based scheduling (DRBS). Simulation results show the effectiveness of our algorithm in comparison with well-known algorithms such as random and round-robin. پرونده مقاله -
دسترسی آزاد مقاله
5 - Minimizing job execution time in Data Grid by A fuzzy dynamic replication algorithm
مهسا بیگرضایی سید لیلی میر طاهری mirtaheriThe nature of Data Grids is dynamic. In these systems, data access patterns of users and network latency may change. The system needs to meet data availability reliability. Data replication is a well-known method for improving performance parameters such as data access چکیده کاملThe nature of Data Grids is dynamic. In these systems, data access patterns of users and network latency may change. The system needs to meet data availability reliability. Data replication is a well-known method for improving performance parameters such as data access time, availability, load balancing, and reliability. Here, a novel dynamic algorithm is proposed that uses fuzzy inference systems to manage replication for increasing performance. The proposed algorithm uses a new comprehensive set of decision parameters and fuzzy logic in each phase to reduce the inefficiency caused by wrong decisions in different phases in a practical Grid. The algorithm uses two fuzzy interfere systems to select an appropriate place for new replication and a less valuable file for deleting when storage space is full. It places the new replica in a suitable site where the file could possibly be needed soon with high probability. It also prevents deleting valuable files using a fuzzy valuation function. The algorithm was simulated by the OptorSim simulator. The results demonstrated that the algorithm is more effective than other replication methods in terms of the number of created replications, the percentage of storage used, and the job execution time. پرونده مقاله -
دسترسی آزاد مقاله
6 - Increasing performance in Data grid by a new replica replacement algorithm
Mahsa Beigrezaei Abolfazl Toroghi Haghighat Seyedeh Leili Mirtaheri Narges Hajizadeh BastaniData Grid provides sharing services for very large data around the world. Data replication is one of the most effective approaches to reduce access latency and response time. In addition to the benefits, replication has costs such as storage and bandwidth consumption, e چکیده کاملData Grid provides sharing services for very large data around the world. Data replication is one of the most effective approaches to reduce access latency and response time. In addition to the benefits, replication has costs such as storage and bandwidth consumption, especially when storage space is low and limited. Therefore, the data replacement should be done wisely. In this paper, we proposed a replacement method called FRA. The algorithm defines a weight for each replica that represents its value. This algorithm uses this weight to prevent the removal of valuable replicas. The results demonstrated that FRA algorithm has better performance than other replication methods in terms of the number of replications, the percentage of storage used, and the job execution time. پرونده مقاله -
دسترسی آزاد مقاله
7 - A Utility-Based Data Replication Algorithm in Large Scale Data Grids
Najme MansouriData grids support access to widely distributed storage for large numbers of users accessing potentially many files. To enhance access time, replication at nearby sites may be used. Data replication, a technique much investigated bydata grid researchers in past years cr چکیده کاملData grids support access to widely distributed storage for large numbers of users accessing potentially many files. To enhance access time, replication at nearby sites may be used. Data replication, a technique much investigated bydata grid researchers in past years creates multiple replicas offile and places them in conventional locations to shorten fileaccess times. One of the problems in data replication iscreation of replicas, replica placement and replica selection. Dynamic creation of replicas in an appropriate site by datareplication strategy can increase the systems performance.In this paper, we propose a data replication algorithm, called the Utility-base Data Replication (UDR) algorithm that improves file access time. Each grid site has its own capabilities and characteristics; therefore, choosing one specific site from many sites that have the needed data is a key and significant decision. The replica selection problem has been studied by many researchers who only considered response time as a criterion for the selection process. Therefore, in this study, we addressed the problem of how to select the best replica for the users' jobs. Our approach is simulated using a data grid simulator, OptorSim, developed by European Data Grid projects. Comparing to the previous work the experimentation shows the improvement in the overall performance. پرونده مقاله -
دسترسی آزاد مقاله
8 - A New Replica Consistency Maintenance Method Based on Dynamic Update Rate Calculation in the Data Grid
Rasmieh Parvaneh Mahsa BeigrezaeiData Grid provides convenient services for data management and uniform access to distributed high volume data sources. Data replication is a service to facilitate and accelerate data accessing in Data Grid. But in the large-scale grid environment, the need to maintain r چکیده کاملData Grid provides convenient services for data management and uniform access to distributed high volume data sources. Data replication is a service to facilitate and accelerate data accessing in Data Grid. But in the large-scale grid environment, the need to maintain replica consistently and ensure identical content of the various replica of a file are inevitable. This paper presents an effective consistency method that maintains replicated data consistent. In this method, the node which contains replica is responsible for managing consistency. In each node, the replica update rate is calculated based on the rate of change in the original data file and the rate of the access request to the existing replica version. The proposed model reduces access delays. The model was simulated using OptorSim developed by European Data Grid projects. The experimental results show that our proposed model has better performance in comparison with optimistic and pessimistic approaches in terms of job execution time, effective network usage, and the total number of updates. پرونده مقاله
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