## 1 Introduction  
With the technological advances in wireless networks and the wide deployment of mobile devices equipped with location sensing technology (e.g., smart phones and pads), location-based services (LBSs) have attracted much attention as one of the most promising applications in recent years [1; 2; 3; 4; 5; 6; 7; 8; 9; 10; 11; 12; 13; 14; 15; 16; 17; 18; 19; 20]. A _rangemonitoring query_, which is defined as (i) retrieving the moving objects located within a client-specified spatial query range and (ii) keeping the query result up to date during a certain time period, can be used in many LBSs such as mobile advertising and traffic condition monitoring. For example, let us consider the scenario of a mobile advertising service, where an advertiser (_i.e._, client) plans to send advertising messages to the nearby potential customers (_i.e._, moving objects) who have opted into the mobile advertising service. Then, the service provider (_i.e._, server) must be able to keep track of the locations of the customers and report their proximity to the advertiser, whenever needed. In many real-life LBSs, however, advertisers are moving away from bombarding customers with the same advertising messages regardless of whether the messages are relevant to the customers. Instead, they are moving toward sending different advertising messages to different customers by additionally specifying non-spatial target criteria. For example, let us suppose that a restaurant owner (_i.e._, client) wants to send advertising messages to only the nearby vegetarian customers whose ages are between 20 and 40 years. In this case, the service provider should report to the restaurant owner only the nearby vegetarian customers aged between 20 and 40 years (_i.e._, content-matched moving objects). In this paper, we propose a method for evaluation of a _content-matched range monitoring query_ (_CM range monitoring query_) over moving objects. Given a set of moving objects \(O\), a CM range monitoring query \(q\), issued by a client over \(O\), specifies (i) a spatial query range and (ii) a set of non-spatial query values. For a query \(q\), during a certain time period, the server should continually retrieve all moving objects (in \(O\)) (i) whose non-spatial attribute values are matched to the set of non-spatial query values; and (ii) that are currently located within the spatial query range. There is a large body of work on evaluation of traditional spatial range monitoring queries over moving objects, which can be classified into two categories according to the mobility of spatial query ranges: one deals with stationary or quasi-stationary query ranges [1, 2, 6, 12, 17, 19, 20], whereas the other deals with moving query ranges [3, 5, 7, 14, 15, 16]. Our study belongs to the former category. The majority of existing methods for evaluation of the traditional range monitoring queries assume that moving objects periodically send location-updates to the server via wireless connections and the server keeps the results of the issued queries up to date [12, 15, 19, 20]. However, excessive location-updates from moving objects can not only cause significant energy waste of the battery powered handheld devices (carried by the moving objects), but also significantly degrade the overall system performance due to overloading network resources and overwhelming server workload [21]. To support efficient evaluation of range monitoring queries over moving objects, it is crucial to satisfy the following two requirements both of which depend on the amount of location-update stream generated from moving objects: (i) the wireless communication cost should be minimized and (ii) the server workload should be minimized.