This paper proposes a fast safe-region generation method for several kinds of vicinity queries including set k nearest neighbor (NN) queries, ordered kNN queries, reverse kNN queries, and distance range queries. When a user is driving a car on a road network, he/she wants to know about objects located in the vicinity of the car. However, the result changes according to the movement of the car, and therefore, the user needs to request up-to-date result to the server. On the other hand, frequent requests for up-to-date results cause heavy loadings on the server. To cope with this problem efficiently, the idea of the safe-region has been proposed, however, it takes long processing time in existing works. This paper proposes a fast generation method of the safe-region applicable to several types of vicinity queries. Through experimental evaluations, we demonstrate that the proposed method outperforms the existing algorithms in the processing time by one or two orders of magnitude.

With the increasing demand of Internet-of-Things applicability in various devices and location-based services (LBSs) with positioning capabilities, we proposed simple and effective post-processing techniques to reduce positioning error and provide more precise navigation to users in a pedestrian environment in this letter. The proposed positioning error reduction techniques (Technique 1-minimum range securement and bounce elimination, Technique 2-direction vector-based error correction) were studied considering low complexity and wide applicability to various types of positioning systems, e.g., global positioning system (GPS). Through the real field tests in urban areas, we have verified that an average positioning error of the proposed techniques is significantly decreased compared to that of a GPS-only environment.

This paper presents a design methodology for positioning sub-platform from the viewpoint of positioning for smartphone-based location-based services (LBS). To achieve this, we analyze a mechanism of positioning error generation including principles of positioning sub-systems and structure of smartphones. Specifically, we carry out the experiments of smartphone positioning performance evaluation by the smartphone basic API (Application Programming Interface) and by the wireless LAN in various environments. Then, we describe the importance of considering three layers as follows: 1) the lower layer that caused by positioning sub-systems, e.g., GPS, wireless LAN, mobile base stations, and so on; 2) the middle layer that caused by functions provided from the platform such as Android and iOS; 3) the upper layer that caused by operation algorithm of applications on the platform.

With the advances in wireless Internet and mobile positioning technology, location-based services (LBSs) have become popular. In LBSs, users must send their exact locations in order to use the services, but they may be subject to several privacy threats. To solve this problem, query processing algorithms based on a cloaking method have been proposed. The algorithms use spatial cloaking methods to blur the user's exact location in a region satisfying the required privacy threshold (k). With the cloaked region, an LBS server can execute a spatial query processing algorithm preserving their privacy. However, the existing algorithms cannot provide good query processing performance. To resolve this problem, we, in this paper, propose a k-NN query processing algorithm based on network Voronoi diagram for spatial networks. Therefore, our algorithm can reduce network expansion overhead and share the information of the expanded road network. In order to demonstrate the efficiency of our algorithms, we have conducted extensive performance evaluations. The results show that our algorithm achieves better performance on retrieval time than the existing algorithms, such as PSNN and kRNN. This is because our k-NN query processing algorithm can greatly reduce a network expansion cost for retrieving k POIs.

Recent Location Based Services (LBS) extend not only information services such as car navigation services, but supporting various applications such as augmented reality and emergency services in ubiquitous computing environments. However location based services in the ubiquitous computing environment bring several security issues such as location privacy and forgery. While the privacy of the location based service is considered as the important security issue, security against location forgery is less considered. In this paper, we propose improved Han et al.'s protocol [1] that provides more lightweight computation. Our proposed model also improves the credibility of LBS by deploying multiple location sensing technologies.

Various types of data from environment are used to provide user-adaptive services. Among them, data of a user's past moving paths are useful to predict a moving user's next location and provide related services. This paper proposes a method to predict a moving user's location through analyzing his/her past moving paths. This method analyzes the user's moving path by using three elements of distance, time and direction of moving paths and Dynamic Time Warping (DTW), and selects the representative path, which is the one most similar to the current moving path in the past paths. The selected path can be used to provide service like space and time estimation.

In this paper, we propose a continuous range query processing method over moving objects. To efficiently process continuous range queries, we design a main-memory-based query index that uses smaller storage and significantly reduces the query processing time. We show through performance evaluation that the proposed method outperforms the existing methods.

Today, pedestrian navigation systems for mobile phones use 2-dimensional maps as a navigation media in general. But 3-dimensional maps or scenery images are easier to understand for users than 2-dimensional maps. To use 3-dimensional maps or scenery guidance, the measuring accuracy of user position is essential to understand guidance images. In this paper, we will present a pedestrian navigation system using real scenery photographs as a navigation media, and based on experiments we will report the evaluation result of influence of positioning accuracy on the understandability of navigation. It is shown that 3 meters or less error of positioning is tolerable for pedestrian navigation systems using scenery images.

We propose the Geographical Location Information (GLI) system that maps a mobile entity on the Internet to a geographical position. Users can look up the latest geographical location information of registered mobile entities (forward-lookup) and can also search for mobile entities within a specified area (reverse-lookup). The GLI system consists of home and area servers. The home server maintains latest geographical location information of the mobile entities and processes forward-lookup requests. The area server maintains the latest geographical location information of the mobile entities in the area that it manages and processes reverse-lookup requests. To provide a highly scalable system, home and area servers are managed in a distributed manner based on a hierarchical server structure and delegation of authority to servers that manage lower layers. To reduce the amount of traffic due to distributed management, the delegation information of authority is cached by the servers. In our performance evaluation of the GLI system, the prototype implementation can handle 4,500-8,000 requests/sec for location lookup and location registration. We found that 52 home servers and 33 area servers are enough to handle all cars in Japan under some assumed parameters through the performance evaluation.