Efficient data management on lightweight computing devices

Lightweight computing devices are becoming ubiquitous and an increasing number of applications are being developed for these devices. Many of these applications deal with significant amounts of data and involve complex joins and aggregate operations, which necessitate a local database management system on the device. This is a challenge as these devices are constrained by limited stable storage and main memory. Hence new storage models that reduce storage costs are needed and a storage scheme should be selected based on data characteristics, nature of queries, and updates. Also, query execution plan should be chosen depending on the amount of available memory and the underlying storage scheme; memory should be optimally allocated among the database operators involved in the query. To achieve these goals, we utilize a novel storage model, ID based storage, which reduces storage costs considerably. We present an exact algorithm for allocating memory among the database operators. Because of its high complexity, we also propose a heuristic solution based on the benefit of an operator per unit memory allocation.