LAG: Achieving transparent access to legacy data by leveraging grid environment

The world today is experiencing an explosive growth of data generated by information digitization. Due to the unprecedented advance in software and hardware, large amounts of data gradually becomes legacy data and inaccessible. This is building a digital black hole, and it is becoming a big challenge to access, process, and preserve the legacy data. Grid provides flexible, secure, and coordinated resource sharing among dynamic collections of individuals, institutions, and resources. It allows users and applications to access the aggregated resources in a transparent manner. This paper proposes a Legacy Application Grid (LAG) architecture. This architecture deploys diverse legacy applications in a grid environment and provides a transparent access to the remote LAG users who want to access the legacy data. In contrast to the existing methods which attempt to tackle legacy data and legacy applications, we wrap a display protocol into grid services. The service provider, who wants to deploy any legacy applications, just needs to deploy the protocol based grid service, describe and pass the parameters of those legacy applications to the service. Compared with the traditional approaches, the method proposed in this paper is very cost-effective because it avoids converting legacy data from one format to another format or upgrading legacy applications one by one. An implemented prototype validates that the LAG architecture trades acceptable performance degradation for a transparent and remote access to legacy data.

Research highlights
► This paper builds a legacy application grid architecture (LAG) and proposes to wrap a display protocol as a legacy grid service.
► The legacy service enables service providers to deploy any applications on heterogeneous platforms and operating systems.
► Therefore, the LAG users can leverage this legacy service to locate and use those required legacy applications to handle legacy data.
► In contrast to the traditional methods, this approach is very cost-effective because it avoids converting legacy data from one format to another format or upgrading legacy applications one by one.
► Since this is a real implementation, detailed evaluation is also performed to explore the performance behaviour of LAG.
► We believe the method proposed in this paper is a new way to tackle the increasing legacy data besides the traditional approaches discussed in the introduction Section.