Scaling replica maintenance in intermittently synchronized mobile databases

Abstract

To avoid the high cost of continuous connectivity, a class of mobile applications employs replicas of shared data that are periodically updated. Updates to these replicas are typically performed on a client-by-client basis-that is, the server individually computes and transmits updates to each clientlimiting scalability. By basing updates on replica groups (instead of clients), however, update generation complexity is no longer bound by client population size. Clients then download updates of pertinent groups. Proper group design reduces redundancies in server processing, disk usage and bandwidth usage, and dimininishes the tie between the complexity of updating replicas and the size of the client population. In this paper, we expand on previous work done on group design, include a detailed I/O cost model for update generation, and propose a heuristic-based greedy algorithm for group computation. Experimental results with an adapted commercial replication system demonstrate a significant increase in overall scalability over the client-centric approach. Figure 1: The update server maintains the primary copy and distributes updates on demand to intermittently connected clients that maintain replicas.

Pruning Update Log Files in Intermittently Connected Databases

“…Organizing updates into the groups shared by clients is proposed in [7]. Built on this work, in [1], the authors propose an update propagation algorithm to make the server workload in update propagation independent of the client population.…”

“…Given the rising popularity of wireless data applications, the issues around the transaction models for ICDB systems are gaining increasing level of attention from database researchers [5], [4], [7], [6], [1]. However, to the best of our knowledge, this is the first research work that investigates the issue of pruning of update logs that need to be transmitted to the mobile clients in such environments.…”

“…In propagating the updates, a client-centric approach-that maintains a customized log file for each client-is very expensive in terms of server processing, as the server load is proportional to the number of clients. In coping with this scalability issue in an ICDB environment, a data-centric approach [1] has been proposed that, based on the client subscriptions, organizes the updates into a limited and controllable number of groups shared by the clients, and allows the server to manage update processing, irrespective of the number of clients, only for those groups. The server maintains a log file only for each of these data-groups, and each of the log files is relevant to a number of clients.…”

Collaborative hypertext editing in mobile environment

“…More importantly, selective propagation of updates (e.g., based on the containment of updates and subscriptions of different groups of clients) was not addressed. Furthermore, our work also shares similar motivations with several other efforts including [1,2,7,13,22,23]. However, all these efforts only considered primitive or less expressive subscription languages.…”

“…In [13], scalability is enhanced by grouping mobile clients according to their interests in sharing data in relational databases. A similar concept was recently applied for efficiently maintaining replica in an intermittently connected environment in [23]. With the exception of [7], the works above did not attempt to reduce costs by automatically merging similar queries.…”