Data replication techniques are used in data grid to reduce makespan, storage
consumption, access latency and network bandwidth. Data replication enhances data …

Replication techniques are widely applied in and for cloud to improve scalability and
availability. In such context, the well-understood problem is how to guarantee consistency …

In data grids, data replication on variant nodes can change some problems such as
response time and availability. Also, in data replication, there are some challenges to finding …

Data Grids provide environment for huge, data-intensive applications that produce and
process enormous data. Such environments are thus asked to manage data and schedule …

Data Grid integrates graphically distributed resources for solving data intensive scientific
applications. Effective scheduling in Grid can reduce the amount of data transferred among …

Data grids provide distributed resources for dealing with large scale applications generating
huge volume of data that require to be efficiently managed, shared and analyzed. Data …

This paper proposes a replication cost model and two greedy algorithms, named GS QoS
and GS QoS C1, for replication placements in cloud-based storage systems. The model …

Data grid systems are utilized to share, manage, and process large data sets. On the other
hand, an increasing number of applications with real-time constraints arise in several …

Data replication is a key optimization technique for reducing access latency and managing
large data by storing replica of data in a wisely manner. In this paper, we propose a data …

Grid environments have gain tremendous importance in recent years since application
requirements increased drastically. The heterogeneity and geographic dispersion of grid …