Mobile Computing Environments, Location-related Data Management

With the advances in wireless communication technology, users can access the information they need, anytime, anywhere. Mobile computing is a research hot point currently. In mobile computing environment, users need to access applications and data which related to their geographical position, seeking information about unfamiliar places or local lifestyle data. Location dependent data management has become the new research direction of mobile computing.First, we define location dependent data and location dependent query completely. We give the classification comparison after the analysis of location dependent application in mobile computing environment. We propose a location dependent query languages-LDSQL based on SQL, along with space query languages. LDSQL can availably manage location dependent query. Compared with the past space query languages, LDSQL extend to support location dependent data, provide the moving objects operation and management. LDSQL added the new condition sub-clause, including the region condition sub-clause locObjRegion which restrict the object query scope, the condition sub-clause cQuyRegion, cQuyPeriod which limit the continuous query validity, cQuyMode which set the update mode and threshold of continuous query, etc. Finally, we discussed location dependent query processing, location translation, the location granularities adjusting and the location mismatch problem.Then, we propose an approximate answers model using generalized databases and concept hierarchies based on location for mobile computing query processing. In a mobile computing environment, because of characteristics such as availability, connectivity, low-band width, data quality, usage cost, users may not obtain perfect answers to their queries within an acceptable time. However, within known limits of correctness and precision, an approximate answer may suffice for some mobile users. In this mobile computing model, answer the query using generalized databases, a condensed form of the primitive database. Generalized databases are smaller than the primitive database, and hence can more easily be stored on the mobile units. During disconnection or weak connections, generalized databases can be used to reply to the queries posed by mobile users, which may result in an approximate answer. This can be verified (if needed) by accessing the main database during periods of strong connection. To construct generalized databases, we propose an algorithm of summarizing the database using concept hierarchies. We have also discussed the cost-benefit analysis with respect to storage, communication and query processing cost.Thirdly, We propose a location dependent data management based on Semantic. In location dependent queries, location plays a distinguished role, it actually provides anadditional, if not the only, semantic criteria to access the data. An LDD query workload is more likely to exhibit a semantic locality in terms of the locations, rather than a static spatial locality defined by the fixed database physical organization. That is to say, an LDD data item with a location closer to the current position of the mobile user and in the direction of his movement is more likely to be visited in the near future. In this paper, a semantic caching scheme is used to access location dependent data in mobile computing. We develop a mobility model to represent the moving behaviors of mobile users, investigate query processing and cache management strategies. We propose a semantic cache replacement strategy LPFDR, which utilizes the semantic locality in terms of locations. The cached contents are changed as the mobile unit moves. The Simulation Experiments show that semantic caching is more flexible and effective for use in LDD applications than page caching, also notice that the semantic cache replacement strategy LPFDR, which utilizes the semantic locality in terms of locations, performs robustly under different kinds of workloads.Fourthly, We propose a location dependent queries processing model based on linear const...