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12th International Conference on Distributed Computing and Internet Technology (ICDCIT)

作者： Jayalakshmi, D. S. Ranjana, T. P. Rashmi Ramaswamy, Srinivasan MS Ramaiah Inst Technol Bengaluru India SRM Univ Kattankulathur Kancheepuram India

ISBN: (纸本)9783319280349;9783319280332

Cloud computing is being used for data-intensive computing for enterprise and scientific applications that process large data sets originating from globally distributed data centers. In this work, we propose a system model for multiple data centers cooperating to serve a client's request for data and to identify data centers which can provide the fastest response time to a client. Further, dynamic data replication strategy across geo-distributed data centers based on popularity is detailed. Simulation results are presented and the performance evaluation shows that our method consistently maintains the replica count to an optimal value.

关键词： data center selection dynamic data replication Geo-distributed data centers data intensive applications

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dynamic data replication Strategy in Cloud Environments 5

Dynamic Data Replication Strategy in Cloud Environments

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Fifth International Conference on Advances in Computing and Communications (ICACC)

作者： Jayalakshmi, D. S. Ranjana, Rashmi T. P. Srinivasan, R. MS Ramaiah Inst Technol Dept CSE Bangalore Karnataka India SRM Univ Res Directorate Kattankulathur Tamil Nadu India

ISBN: (纸本)9781467369947

replication of a popular file and storing its replica in the locations closer to the clients who are making requests is the best choice to reduce the execution time. Although replication helps in increasing availability, the question of how to decide an optimal replication number and correct locations to place the replicas are open challenges. In this paper, a brief survey on various data center selection and replication strategies used are described. Further, a system model with two phases, data center selection and dynamic data replication, is proposed with an aim to effectively increase the data availability and also reduce user waiting time by very small number of replicas is presented in this paper.

关键词： dynamic data replication Cloud data Service data Center Replica Managers & Replica Catalogs

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PDDRA: A new pre-fetching based dynamic data replication algorithm in data grids

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2012年第4期28卷 666-681页

作者： Saadat, Nazanin Rahmani, Amir Masoud Islamic Azad Univ Dept Comp Engn Sci & Res Branch Tehran Iran Islamic Azad Univ Dept Comp & Mechatron Engn Sci & Res Branch Tehran Iran

In recent years, grid technology has had such a fast growth that it has been used in many scientific experiments and research centers. A large number of storage elements and computational resources are combined to generate a grid which gives us shared access to extra computing power. In particular, data grid deals with data intensive applications and provides intensive resources across widely distributed communities. data replication is an efficient way for distributing replicas among the data grids, making it possible to access similar data in different locations of the data grid. replication reduces data access time and improves the performance of the system. In this paper, we propose a new dynamic data replication algorithm named PDDRA that optimizes the traditional algorithms. Our proposed algorithm is based on an assumption: members in a VO (Virtual Organization) have similar interests in files. Based on this assumption and also file access history, PDDRA predicts future needs of grid sites and pre-fetches a sequence of files to the requester grid site, so the next time that this site needs a file, it will be locally available. This will considerably reduce access latency, response time and bandwidth consumption. PDDRA consists of three phases: storing file access patterns, requesting a file and performing replication and pre-fetching and replacement. The algorithm was tested using a grid simulator, OptorSim developed by European data Grid projects. The simulation results show that our proposed algorithm has better performance in comparison with other algorithms in terms ofjob execution time, effective network usage, total number of replications, hit ratio and percentage of storage filled. (C) 2011 Elsevier By. All rights reserved.

关键词： data grid dynamic data replication File access pattern data pre-fetching

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A novel dynamic data replication strategy to improve access efficiency of cloud storage

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INFORMATION SYSTEMS AND E-BUSINESS MANAGEMENT 2020年第3期18卷 405-426页

作者： Nannai John, Sujaudeen Mirnalinee, T. T. SSN Coll Engn DCSE Chennai Tamil Nadu India

Cloud computing provides on demand services to cloud users, and one among them is storage. Currently, large amount of data gets generated and demand an enormous storage. Users can avail the privilege to store their data remotely and can access them through Internet. Of course, the adoption of cloud lends the kind of storage that the user wants. Since data gets accumulated, the time it takes to store and retrieve the data is very long and difficult. Also, unfortunately the existing method of storage is to be optimized for better performance. The factors that affect the performance of cloud storage are response time, data availability and migration cost. Hence to improve these factors the data can be replicated to multiple locations. The decision on which data to be replicated, number of replicas to be created, where the replica has to be placed, management of the replicated data and the provision of optimal replica to the user are the major challenges involved in dynamic replication. We intend to propose, a novel dynamic data replication strategy with intelligent water drop (IWD) algorithm to address the challenges of replication and for the management of cloud storage. The popularity and size of the data are considered for replication. A swarm intelligence based optimization algorithm named IWD algorithm is used to optimize the process of replication and management of storage in cloud. We have compared our D2R-IWD algorithm with popular optimization techniques such as PSO, GA and found out that our methodology gives better result in terms of access efficiency for several test cases thereby improve the performance of cloud.

关键词： Cloud storage dynamic data replication Intelligent water drop algorithm Replica management Performance

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dynamic data replication and placement strategy in geographically distributed data centers

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CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2023年第14期35卷

作者： Bouhouch, Laila Zbakh, Mostapha Tadonki, Claude Mohammed V Univ Rabat Natl Sch Comp Sci & Syst Anal Rabat Morocco MINES ParisTech PSL CRI Paris France

With the evolution of geographically distributed data centers in the Cloud Computing landscape along with the amount of data being processed in these data centers, which is growing at an exponential rate, processing massive data applications become an important topic. Since a given task may require many datasets for its execution and the datasets are spread over several different data centers, finding an efficient way to manage the datasets storage across nodes of a Cloud system is a difficult problem. In fact, the execution time of a task might be influenced by the cost of data transfers, which mainly depends on two criterias. The first one is the initial placement of the input datasets during the build-time phase, while the second is the replication of the datasets during the runtime phase. The replication is explicitly considered when datasets are being migrated over the data centers in order to make them locally available wherever needed. data placement and data replication are important challenges in Cloud Computing. Nevertheless, many studies focus on data placement or data replication exclusively. In this paper, a combination of a data placement strategy followed by a dynamic data replication management strategy is proposed, with the purpose of reducing the associated cost of all data transfers between the (distant) data centers. Our proposed data placement approach considers the main characteristics of a data center such as storage capacity and read/write speeds to efficiently store the datasets, while our dynamic data replication management approach considers three parameters: the number of replicas in the system, the dependency between datasets and tasks and the storage capacity of data centers. The decision of when and whether to keep or to delete replicas is determined by the fulfillment of those three parameters. Our approach estimates the total execution time of the tasks as well as the monetary cost, considering the data transfers activity. Our experi

关键词： big data cloud computing Cloudsim data placement dynamic data replication

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On dynamic replication strategies in data service grids

On dynamic replication strategies in data service grids

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11th IEEE Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing

作者： Dong, Xiaohua Li, Ji Wu, Zhongfu Zhang, Dacheng Xu, Jie Chongqing Univ Chongqing Peoples R China Univ Leeds Leeds LS2 9JT W Yorkshire England

ISBN: (纸本)9780769531328

Service Oriented Architecture (SOA) allows multiple and heterogeneous data resources to be integrated within a single service while hiding the implementation details and formats of data resources from users of the service. However, data sources for a service are often distributed geographically and connected with long-latency networks;time and bandwidth consumption of data transportation may have an impact on the system performance. dynamic data replication is a practical solution to this problem. By replicating data copies to appropriate sites, this approach aims to reduce time and bandwidth consumptions over networks. Existing strategies for dynamic replication are typically based on so-called single-location algorithms for identifying a single site for data replication. In this paper we discuss the issues with single-location strategies in large-scale data integration applications, and examine potential multiple-location schemes. dynamic multiple-location replication is NP-complete in nature. We therefore transform the multiple-location problem into several classical mathematical problems with different parameter settings, for which efficient approximation algorithms exist. Experimental results indicate that unlike single-location strategies our multiple-location schemes are efficient with respect to access latency and bandwidth consumption, especially when the requesters of a data set are distributed over a large scale of locations.

关键词： Approximation algorithms dynamic data replication Multiple-location replication SOA

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The Incremental Load Balance Cloud Algorithm by Using dynamic data Deployment

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JOURNAL OF GRID COMPUTING 2019年第3期17卷 553-575页

作者： Hsieh, Hui-Ching Chiang, Mao-Lun Hsing Wu Univ Dept Informat Commun 101Sec 1Fenliao Rd New Taipei Taiwan Chaoyang Univ Technol Dept Informat & Commun Engn 168 Gifeng E Rd Wufeng Taichung Cty Taiwan

The rapid advancement of network technology has changed the way the world operates and has produced a large number of network application services for users. In order to provide more convenient services, the network service providers need to provide a more stable and high-capacity system. Therefore, cloud computing technology has been developed in the recent decade. The network service providers can reduce the cost related to the cloud computing services by using the virtualizing and data replicating techniques. Besides, an efficient information duplication strategy is necessary to reduce the workload and enhance the ability of the system. Therefore, a three-phase dynamic data replication Algorithms (DDRA) for deploying the resources has been proposed in this paper to improve the efficiency of the information duplication under the cloud storage system. For the first two phases, the proposed algorithm is designed to determine the suitable service nodes to achieve the balance of workload according to the service nodes' workloads. In the third phase, a dynamic duplication deployment scheme has been designed to achieve the higher access performance and better load balancing between service nodes for the overall environment. As a result, the proposed algorithm can enhance the availability, access efficiency and load balancing under the hierarchical cloud computing environment.

关键词： Cloud computing Load balancing dynamic data replication

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A File Group data replication Algorithm for data Grids

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JOURNAL OF GRID COMPUTING 2017年第3期15卷 379-393页

作者： Rahmani, Amir Masoud Azari, Leila Daniel, Helder A. Univ Human Dev Comp Sci Sulaimanyah Iraq Islamic Azad Univ Ahvaz Branch Dept Comp Engn Ahvaz Iran Univ Algarve Fac Sci & Technol Dept Elect & Informat Engn Algarve Portugal

In recent years data grids have been deployed and grown in many scientific experiments and data centers. The deployment of such environments has allowed grid users to gain access to a large number of distributed data. data replication is a key issue in a data grid and should be applied intelligently because it reduces data access time and bandwidth consumption for each grid site. Therefore this area will be very challenging as well as providing much scope for improvement. In this paper, we introduce a new dynamic data replication algorithm named Popular File Group replication, PFGR which is based on three assumptions: first, users in a grid site (Virtual Organization) have similar interests in files and second, they have the temporal locality of file accesses and third, all files are read-only. Based on file access history and first assumption, PFGR builds a connectivity graph for a group of dependent files in each grid site and replicates the most popular group files to the requester grid site. After that, when a user of that grid site needs some files, they are available locally. The simulation results show that our algorithm increases performance by minimizing the mean job execution time and bandwidth consumption and avoids unnecessary replication.

关键词： dynamic data replication data grids Group replication Connectivity graph

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A data replication algorithm for groups of files in data grids

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JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING 2018年 113卷 115-126页

作者： Azari, Leila Rahmani, Amir Masoud Daniel, Helder A. Qader, Nooruldeen Nasih Islamic Azad Univ Khouzestan Sci & Res Branch Dept Comp Ahvaz Iran Islamic Azad Univ Ahvaz Branch Dept Comp Ahvaz Iran Islamic Azad Univ Sci & Res Branch Comp Engn Dept Tehran Iran Univ Human Dev Comp Sci Sulaimanyah Iraq Univ Algarve Fac Sci & Technol Dept Elect & Informat Engn Faro Portugal

data grid is emerging as the main part of the infrastructure for large-scale data intensive applications such as high energy physics and bioinformatics. The deployment of such infrastructures has allowed users of a grid site to gain access to a large amount of distributed data. data replication is a key issue in a data grid and could be applied intelligently because it reduces data access time and bandwidth consumption for each grid site. In this paper, we introduce a new dynamic data replication algorithm named Popular Groups of Files replication (PGFR). Our proposed algorithm is based on an assumption: users in a Virtual Organization have similar interests in groups of files. Based on this assumption, and file access history, PGFR builds a connectivity graph to recognize a group of dependent files in each grid site and replicates the most Popular Groups of Files to each grid site, thus increasing the local availability. We used OptorSim simulator to evaluate the efficiency of PGFR algorithm. The simulation results show that PGFR achieves better performance compared to the existing algorithm;PGFR minimized the mean job execution time, bandwidth consumption, and avoiding unnecessary replication. (C) 2017 Elsevier Inc. All rights reserved.

关键词： dynamic data replication data grids Group replication Connectivity graph

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On fault-tolerant data replication in distributed systems

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MICROPROCESSORS AND MICROSYSTEMS 2002年第7期26卷 301-309页

作者： Tenzekhti, F Day, K Ould-Khaoua, M Sultan Qaboos Univ Dept Comp Sci Muscat 123 Oman Univ Glasgow Dept Comp Sci Glasgow G12 8RZ Lanark Scotland

This paper presents a new fault-tolerant algorithm for dynamic data replication in distributed systems. The algorithm presents remedies to the deficiencies of the existing adaptive data replication (ADR) and the primary missing writes (PMW) algorithms, proposed in [ACM Trans. database Syst. 22 (1997) 255]. The new algorithm extends the idea of PMW to allow the adaptive replication algorithm to be used in the presence of failures, and introduces new mechanisms for maximising object availability. Results from a comparative analysis reveal that our algorithm outperforms the ADR/PMW especially in a read intensive environment like the Internet. (C) 2002 Published by Elsevier Science B.V.

关键词： distributed systems dynamic data replication fault tolerance comparative analysis

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