Abstract
In large-scale distributed dataset sharing systems, challenges of dynamicity, heterogeneity, and latency emphasise the importance of infrastructural support in enhancing the system performance. The growth of grid computing gives a reliable environment for the effective usage of this distributed huge dataset. In order to build efficient sharing architecture, varieties of architectures were developed based on grid technology. The goal of such architecture is to solve interoperability and heterogeneous resource issues, and increase the efficiency and effectiveness of sharing techniques by harnessing the grid computing capabilities. This study proposes grid-based sharing architecture for distributed massive datasets. The architecture is considering a mediator between the users and the data providers. The experiments conducted to evaluate the performance of the architecture by measuring the grid overhead, throughput, and scalability of the architecture. The result shows that the architecture has reasonable performance and can be scalable with the growing data and computing nodes.