Query Optimization Using Global GIS Evaluation Strategies

Abstract

With the current scale of mobile GIS users and increase in the applications that are deployed for LBS, the optimization of proximity analysis queries becomes a major issue. The query melting processor (QMP) has been developed for processing multiple dynamic complex queries (MDCQ) based on the Query Melting paradigm which consists of the sharing paradigm and the push-down strategy. However, with the increase in volume of cost sensitive mobile users, the need emerges to develop a time cost optimizer for processing MDCQs. Thus, it is crucial to develop a new Decision Making Mechanism for handling the time cost optimization (TCOP) and prove its cost effectiveness. TCOP is based on the new paradigm “Sharing Global Execution Plans by MDCQs with similar scenarios”. The experimental evaluation results, using a case study based on the map of Paris, proved that significant saving in time can be achieved by employing the newly developed strategies.