The performance evaluation and analysis of caching in data grid system

Data-intensive applications in the data grid environment usually transfer large amount of data, which can cause high network consumption and degrade the overall performance of the network. Caching is one of the techniques that can reduce network bandwidth usage by storing data likely to be used in the near future in its local storage. This technique is very successful, especially in the Internet. However, the conventional cache used in WWW can not be applied completely into the grid environment because of the differences between Web and Data Grid{7f2019}s behaviors, for example, data size, network consumption. This thesis proposes the block-based data caching model for data grid environment by dividing data file in many data blocks which can achieve better space utilization which leads to better overall performance. The experiment conduct by simulation using grid extended NS-2. The result indicates that data caching, especially block-based data caching, can provide benefits for the data grid environment which can be further developed into real implementation and can fine-tune for different environments.数据密集型应用在数据网格（Data Grid）环境中通常会传输海量数据，由此引发高额网络开销并降低网络整体性能。缓存（Caching）技术作为通过将近期大概率被访问的数据存储至本地存储，以降低网络带宽占用的手段之一，在互联网领域已取得极佳的应用效果。然而，由于万维网（WWW）与数据网格的运行特性存在差异{7f2019}（如数据规模、网络开销等），传统万维网缓存无法直接完全适配网格环境。本论文针对数据网格环境提出了一种基于块的数据缓存模型：将数据文件划分为若干数据块，以此实现更优的空间利用率，进而提升网络整体性能。本研究采用扩展了网格功能的NS-2开展仿真实验，结果表明，数据缓存尤其是基于块的数据缓存，可为数据网格环境带来切实收益；该方案可进一步开发为实际落地应用，并可针对不同运行环境进行微调优化。

搜集汇总

背景与挑战

背景概述

该数据集是一篇2005年由朱拉隆功大学出版的学术论文，主题为数据网格系统中缓存的性能评估与分析。论文提出了一种基于块的数据缓存模型，旨在解决数据网格环境中大数据传输导致的网络性能问题，并通过模拟实验验证了该模型的有效性。