A novel dynamic network data replication scheme based on historical access record and proactive deletion

Wang, Zhe; Li, Tao; Xiong, Naixue; Pan, Yi

doi:10.1007/s11227-011-0708-z

Cited by 71 publications

(35 citation statements)

References 13 publications

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“…Based on this model, they developed an algorithm to find near-optimal dynamic allocation solutions. Zhe Wang et al [26] have presented a dynamic data replication strategy based on two ideas. The first one employed historical access records which were useful for picking up a file to replicate.…”

Section: Related Work: a Brief Reviewmentioning

confidence: 99%

Dynamic Replication Algorithm for Data Replication to Improve System Availability: A Performance Engineering Approach

Vobugari

Somayajulu

Subaraya

2015

IETE Journal of Research

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Information technology systems deployed by enterprises should not only fulfil their business functionalities but also cater to Quality of Service concerns such as Availability, Scalability, and Performance. To enhance the system performance, the system availability is an important factor and to improve the system availability, one of the strategies is replicating the frequently accessed data to multiple suitable locations which is a practical choice as the users can access the data from a nearby site. This is, however, not the case for replicas which must have a preset number of copies on several locations. How to decide a sensible number and right location for replicas have become an important issue in cloud computing. In this paper, we show a dynamic data replication strategy to enhance the performance of software system. To identify the suitable file to replicate and to decide respective number of replicas, we calculate popularity degree and replica factor. We use the fuzzy logic system to identify the system to place the replicas and we use the round robin method to place the replicas in the identified systems. We compare the performance of our technique with the existing technique.

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Section: Related Work: a Brief Reviewmentioning

confidence: 99%

Dynamic Replication Algorithm for Data Replication to Improve System Availability: A Performance Engineering Approach

Vobugari

Somayajulu

Subaraya

2015

IETE Journal of Research

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“…DCs, within a DC in different nodes or at the client-side [4,4,15], whereas the focus of adaptive geo-replication is to decide what data, where the data is located within the overall system of DCs and how many replicas exist simultaneously, [1,2,10,12,18]. Both of these types maybe be combined to obtain further performance improvements.…”

Section: Classification Of Strategiesmentioning

confidence: 99%

Adaptive strength geo-replication strategy

Signes¹,

Bieniusa

2015

Proceedings of the First Workshop on Principles and Practice of Consistency for Distributed Data

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The amount of data being processed in Data Centres (DCs) keeps growing at an enormous rate so that full replication may start being impractical. The application of replication between DCs is used to increase data availability in the presence of site failures and to reduce latency by accessing the data closely located, if possible. This means that replicating the data only in some of the DCs is becoming more critical in order to reduce the costs of keeping the data (weakly) consistent while maintaining high availability (scalability) and low access costs. When data read and write request patterns change, then deciding which data should be replicated and where needs to be made dynamically. Given that the problem of finding an optimal replication schema in a general network has been shown to be NP-complete for the static case, so it is unlikely that there exists a general algorithm for an optimal solution to the dynamic problem.We present here a new adaptive bio-inspired replication strategy, which is completely decentralised, adaptive, and event-driven, inspired on the Ant Colony algorithm.

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“…Wang et al (2011) proposed an algorithm for dynamic data replication strategy .It employs historical access records which are useful for picking up a file to replicate. Next one is proactive deletion method [12], is applied to control the replica number to reach an optimal balance between the read and the write update overhead. This replication algorithm uses the popularity of the file to make replication decision.…”

Section: Related Workmentioning

confidence: 99%

An improved dynamic data replica selection and placement in cloud

Rajalakshmi¹,

Vijayakumar²,

Srinivasagan³

2014

2014 International Conference on Recent Trends in Information Technology

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Cloud computing platform is getting more and more attentions as a new trend of data management. Data replication has been widely used to speed up data access in cloud. Replica selection and placement are the major issues in replication. In this paper we propose an approach for dynamic data replication in cloud. A replica management system allows users to create, and manage replicas and update the replicas if the original datas are modified. The proposed work concentrates on designing an algorithm for suitable optimal replica selection and placement to increase availability of data in the cloud. The method consists of two main phases file application and replication operation. The first phase contains the replica location and creation by using catalog and index. In second phase is used to find whether there is enough space in the destination to store the requested file or not. Replication aims to increase availability of resources, minimum access cost, shared bandwidth consumption and delay time by replicating data. The proposed systems developed under the Eucalyptus cloud environment. The results of proposed replica selection algorithm achieve better accessibility compared with other methods.

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A novel dynamic network data replication scheme based on historical access record and proactive deletion

Cited by 71 publications

References 13 publications

Dynamic Replication Algorithm for Data Replication to Improve System Availability: A Performance Engineering Approach

Dynamic Replication Algorithm for Data Replication to Improve System Availability: A Performance Engineering Approach

Adaptive strength geo-replication strategy

An improved dynamic data replica selection and placement in cloud

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