Summary To receive location‐based services (LBS), users must disclose their locations and queries to the LBS server, which can expose the user's identity, location, and other information. Recently, techniques for protecting user privacy using dummies have been researched. However, many factors, such as the distance between the obstacles and the dummies, must be considered in order to create dummies. Therefore, this study proposes an efficient dummy creation technique to improve user privacy protection. Experimental results show that the proposed technique improves on other recent techniques.

An increasing amount of active research is being conducted to protect the locations of mobile device users. Users must tune to more data than they would like to in order to hide their location. In particular, if a user requests a query over k NN, the number of objects the user must receive may increase. Several studies have been proposed to solve these problems. However, problems have been identified during the course of query processing, such as errors and increased query processing times. When the tuning time is increased, the amount of data to download and the battery consumption of the client also increase. In this study, we propose the Privacy‐preserving Spatial Index (PSI), an index that allows users to reduce their tuning time while being satisfied with the results of their queries. The querier (q) requests the object in the area protecting his/her location from the server. The server sends the requested data of points of interest (POIs) (DPOIs) in the Privacy‐preserving Region (PR) to q. Finally, q reduces tuning time by selectively tuning to the desired data of POIs (Dw) through PSI. The superiority of PSI over previous techniques is experimentally proven.

A fundamental problem for peer-to-peer (P2P) applications in mobile-pervasive computing environment is to efficiently identify the node that stores particular data items and download them while preserving battery power. In this paper, we propose a P2P Minimum Boundary Rectangle (PMBR, for short) which is a new spatial index specifically designed for mobile P2P environments. A node that contains desirable data item (s) can be easily identified by reading the PMBR index. Then, we propose a selective tuning algorithm, called Distributed exponential Sequence Scheme (DSS, for short), that provides clients with the ability of selective tuning of data items, thus preserving the scarce power resource. The proposed algorithm is simple but efficient in supporting linear transmission of spatial data and processing of location-aware queries. The results from theoretical analysis and experiments show that the proposed algorithm with the PMBR index is scalable and energy efficient in both range queries and nearest neighbor queries.

In this paper, we propose new spatial query processing algorithms to support Mobile Continuous Nearest Neighbor Query (MCNNQ) in wireless broadcast environments. Each client (object) computes individually the function that best captures the locations of the moving objects, while a server is only responsible for delivering information gathered from the clients. Extensive experiments demonstrate that our location-based data dissemination algorithm significantly out-performs index-based solutions.

Indexing provides for selective tuning but suffers from the drawback that, in order to conserve battery power, the client has to wait for and tune to the index segment. In location-aware mobile services (LAMSs), it is important to reduce the query response time since a late query response may contain out-of-date information. In this paper, we present a broadcast-based spatial query processing scheme designed to support nearest neighbor (NN) query processing. With the proposed schemes, broadcast data items are sorted sequentially based on their locations and the clients can selectively tune to the desired data item without the need for an index segment. For the purpose of selective tuning, we present the exponential sequence scheme (ESS) and cluster-based Fibonacci sequence scheme (CFS) schemes. The ESS and CFS schemes attempt to conserve battery power. The performance of our schemes is investigated in relation to various environmental variables such as the distributions of data objects, the average speed of the clients, and the size of the service area. The resulting latency and tuning time are close to the optimum values, as our analysis and simulation results indicate

Wireless data broadcast, which allows simultaneous access by an arbitrary number of clients, is a very efficient and scalable information dissemination method. It is particularly attractive for resource limited mobile clients in asymmetric communications. In Location Dependent Information Services(LDISs), it is important to reduce the query response time, since a late query response may contain outof- date information. In this paper, we present a broadcastbased spatial query processing method designed to support spatial queries via wireless data broadcast. Experiments are conducted to evaluate the performance of the proposed methods. The resulting latency is close to the optimum values, as the simulation results indicate