Adding Node Absence Dynamics to Data Replication Strategies for Unreliable Wireless Grid Environments

2009 ◽  
pp. 155-160
Author(s):  
Soomi Yang
Keyword(s):  
Data Replication ◽  
Grid Environments ◽  
Wireless Grid

Dynamic QoS-aware data replication in grid environments based on data “importance”

2012 ◽  
Vol 28 (3) ◽  
pp. 544-553 ◽  
Author(s):  
Vassiliki Andronikou ◽  
Konstantinos Mamouras ◽  
Konstantinos Tserpes ◽  
Dimosthenis Kyriazis ◽  
Theodora Varvarigou
Keyword(s):  
Data Replication ◽  
Grid Environments

A Bee Colony based optimization approach for simultaneous job scheduling and data replication in grid environments

2013 ◽  
Vol 40 (6) ◽  
pp. 1564-1578 ◽  
Author(s):  
Javid Taheri ◽  
Young Choon Lee ◽  
Albert Y. Zomaya ◽  
Howard Jay Siegel
Keyword(s):  
Job Scheduling ◽  
Data Replication ◽  
Optimization Approach ◽  
Bee Colony ◽  
Grid Environments

The State of the Art and Open Problems in Data Replication in Grid Environments

2010 ◽  
pp. 486-516 ◽  
Author(s):  
Mohammad Shorfuzzaman ◽  
Rasit Eskicioglu ◽  
Peter Graham
Keyword(s):  
Data Replication ◽  
Data Access ◽  
The State ◽  
Data Availability ◽  
Data Grids ◽  
Open Problems ◽  
Data Intensive ◽  
Grid Environments ◽  
Bandwidth Savings ◽  
And Storage

Data Grids provide services and infrastructure for distributed data-intensive applications that need to access, transfer and modify massive datasets stored at distributed locations around the world. For example, the next-generation of scientific applications such as many in high-energy physics, molecular modeling, and earth sciences will involve large collections of data created from simulations or experiments. The size of these data collections is expected to be of multi-terabyte or even petabyte scale in many applications. Ensuring efficient, reliable, secure and fast access to such large data is hindered by the high latencies of the Internet. The need to manage and access multiple petabytes of data in Grid environments, as well as to ensure data availability and access optimization are challenges that must be addressed. To improve data access efficiency, data can be replicated at multiple locations so that a user can access the data from a site near where it will be processed. In addition to the reduction of data access time, replication in Data Grids also uses network and storage resources more efficiently. In this chapter, the state of current research on data replication and arising challenges for the new generation of data-intensive grid environments are reviewed and open problems are identified. First, fundamental data replication strategies are reviewed which offer high data availability, low bandwidth consumption, increased fault tolerance, and improved scalability of the overall system. Then, specific algorithms for selecting appropriate replicas and maintaining replica consistency are discussed. The impact of data replication on job scheduling performance in Data Grids is also analyzed. A set of appropriate metrics including access latency, bandwidth savings, server load, and storage overhead for use in making critical comparisons of various data replication techniques is also discussed. Overall, this chapter provides a comprehensive study of replication techniques in Data Grids that not only serves as a tool to understanding this evolving research area but also provides a reference to which future e orts may be mapped.

Enhanced Data Security from Single Clouds to Multiclouds

2018 ◽  
Vol 6 (9) ◽  
pp. 66
Author(s):  
Umesh Banodha ◽  
Praveen Kumar Kataria
Keyword(s):  
Data Storage ◽  
Network Connectivity ◽  
Data Replication ◽  
Recovery Process ◽  
Cloud Environment ◽  
Storage Security ◽  
Cloud Data ◽  
Replication Strategy ◽  
Cloud Data Storage ◽  
Data Files

Cloud is an emerging technology that stores the necessary data and electronic form of data is produced in gigantic quantity. It is vital to maintain the efficacy of this data the need of data recovery services is highly essential. Cloud computing is anticipated as the vital foundation for the creation of IT enterprise and it is an impeccable solution to move databases and application software to big data centers where managing data and services is not completely reliable. Our focus will be on the cloud data storage security which is a vital feature when it comes to giving quality service. It should also be noted that cloud environment comprises of extremely dynamic and heterogeneous environment and because of high scale physical data and resources, the failure of data centre nodes is completely normal.Therefore, cloud environment needs effective adaptive management of data replication to handle the indispensable characteristic of the cloud environment. Disaster recovery using cloud resources is an attractive approach and data replication strategy which attentively helps to choose the data files for replication and the strategy proposed tells dynamically about the number of replicas and effective data nodes for replication. Thus, the objective of future algorithm is useful to help users together the information from a remote location where network connectivity is absent and secondly to recover files in case it gets deleted or wrecked because of any reason. Even, time oriented problems are getting resolved so in less time recovery process is executed.

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