Research On Strategies Of Location Dependent Data Services In Mobile Computing Envrionments

The development and combination of computing technologies and wireless communication techinologies have made a new computing mode—mobile computing mode a reality. The computer networks which use mobile computing mode are called mobile computing environments. Location dependent data service is one of the most important data sercices in mobile computing environment. Such data service provides query results that are dependent on the mobile objects/users' location to the network users. The research on location dependent data services in mobile computing environment is still at an initial stage and increasingly becomes a hot spot. The dissertation addresses three research issues: improving the performance of locating mobile users using the caching method in wireless cellular networks; processing event-basesd location dependent data queries and efficiently managing the sernsors' mobility in resource-constrained Wireless Sensor Networks (WSNs); efficiently processing continuous location dependent aggregation queries in mobile WSNs.Location management of the mobile objects/users is one of the key research topics of location dependent data services in wireless cellular network. To improve the performance of locating mobile users, one important approach is caching mobile users' location information. However, existing caching strategies only consider a single user, which is inefficient. We propose a Dynamic Adaptive Caching Location (DACaL) strategy by location database clustering for mass mobile users. DACaL strategy reduces the total cost of location management in mobile computing environment. In LDB-Clustering, location databases are clustered by mining mobile users' moving pattern to determine the caching level and reduce location management cost. In Dynamic-Adaptive-Caching, location databases are reorganized based on clustering result, location information is cached and bypass pointers are created between adjacent clusters to shorten signal traveling path and reduce times of querying location databases.Few existing research work has addressed the location dependent data services in wireless sensor networks. The reason is that it is difficult to manage and locate mobile sensor nodes in dynamic, distributed and resource constrained netoworks to continuously process the query. We propose an Event-based Location Dependent Query (ELDQ) model that continuously aggregates data in specific areas around mobile sensors of interests is presented. In fact, ELDQs generalize several typical data service queries, which are important in many applications. However, existing approaches fail to efficiently answering ELDQs. Therefore it is necessary to research corresponding algorithms and techniques including adaptive proxy selection, in-network query dissemination and propagation, Location-based In-network Aggregation (LIA) and two-level multi-query optimization to process ELDQs while optimizing system performance.Due to sensor mobility, location dependent queries in mobile WSNs require continuous query results. However, existing approaches require fixed infrastructure and do not exploit the relationships between successive snap-shot queries. We propose an infrastructure-free approach for processing location dependent queries in mobile WSNs to optimize the total processing cost of Continuous Location Dependent Query (CLDQ). This approach consists of a Hop-based Dissemination route Update (HDU) algorithm, a Contention-based Distance-aware Message Scheduling (CDMS) algorithm and a performance optimzaition approach for continous query processing based on location predictions.