Recent advances in wireless communication networks and portable computers have greatly increased the functionality of mobile information services and mobile computing applications. Most of those applications are expected to support location-dependent continuous queries (LDCQs) in the near future. A LDCQ is evaluated continuously in the system for a period of time and the changing results can be transmitted to the requesting client. The result of a LDCQ depends on both the locations of mobile objects on which the query has been issued and the location of the mobile client which has submitted the query. The result of a LDCQ can be provided to the requesting client as a set of tuples <S, begin, end> indicating that object S satisfies the query from time begin to time end. The correctness and timeliness of query results of LDCQs have been studied by employing an adaptive monitoring method (AMM) that manages the locations of moving objects. In this thesis, we propose a Categorized Adaptive Monitoring Method (CAMM) which allows to specify various criticality levels for LDCQs. The aim of CAMM is to provide higher levels of correctness for query results as the criticality of the query increases, without significantly increasing the wireless bandwidth requirements. We provide a simulation model with multiple criticality levels and evaluate the performance of the mobile system and the proposed method with extensive simulation experiments.