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Conventional data grid systems require the application to access remote data through explicit APIs, consequently sacrificing user transparency. Thus, some systems enable the application to transparently access remote data by copying the entire file to a user's local storage before executing the application, even when only a tiny file fragment is required. Such an approach consumes unnecessary transmission time and storage space, with the additional problem of maintaining replica synchronization. Traditionally, replica consistency treats shared files as read-only, consequently sacrificing guaranteed replica consistency. This paper presents a DSM-based fragment-level file sharing framework called "Spigot". Spigot allows the users to design their applications with the POSIX I/O interface. Moreover, Spigot transfers only the necessary file fragments on user demand, thereby reducing transmission time, wasted network bandwidth and required storage space. Data waiting time is further reduced by overlapping data transmission and data analysis. The DSM concept maintains replica synchronization. Real experiments show reduced turnaround times in data-intensive applications.

Efficient information sharing is difficult to achieve in the scenario of emergency and rescue operations because there is no communication infrastructure at the disaster sites. In general, the network condition is relatively reliable in the intra-site environment but relatively unreliable in the inter-site environment. The network partitioning problem may occur between two sites. Although one can exploit the replication technique used in data grid to improve the information availability in emergency and rescue applications, the data consistency problem occurs between replicas. In this paper, the authors propose a middleware called “Seagull” to transparently manage the data availability and consistency issues of emergency and rescue applications. Seagull adopts the optimistic replication scheme to provide the higher data availability in the inter-site environment. It also adopts the pessimistic replication scheme to provide the stronger data consistency guarantee in the intra-site environment. Moreover, it adopts an adaptive consistency granularity strategy that achieves the better performance of the consistency management because this strategy provides the higher parallelism when the false sharing happens. Lastly, Seagull adopts the transparency data consistency management scheme, and thus the users do not need to modify their source codes to run on the Seagull.

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