Location Prediction Based on a Sector Snapshot for Location-Based Services

Abstract

In location-based services (LBSs), the service is provided based on the users' locations through location determination and mobility realization. Most of the current location prediction research is focused on generalized location models, where the geographic extent is divided into regular-shaped cells. These models are not suitable for certain LBSs where the objectives are to compute and present on-road services. Such techniques are the new Markov-based mobility prediction (NMMP) and prediction location model (PLM) that deal with inner cell structure and different levels of prediction, respectively. The NMMP and PLM techniques suffer from complex computation, accuracy rate regression, and insufficient accuracy. In this paper, a novel cell splitting algorithm is proposed. Also, a new prediction technique is introduced. The cell splitting is universal so it can be applied to all types of cells. Meanwhile, this algorithm is implemented to the Micro cell in parallel with the new prediction technique. The prediction technique, compared with two classic prediction techniques and the experimental results, show the effectiveness and robustness of the new splitting algorithm and prediction technique.

A new routing area displacement prediction for Location-Based Services based on an enhanced ant colony

“…SDPA [26], [27] has been developed to improve prediction rates and minimise consumption of resources and the overall cost of the location management process compared with PLM. Also, the SDPA reduces the service area and the number of predicted routes during the MU trip by dividing the cell into eight equivalent regions.…”

Modified Fingerprinting Algorithm for Indoor Location

“…Location Based Services (LBS) have been flourished with the rapid developments in network technology and portable mobile sensing devices. LBS have played an important role in dealing with public emergencies, widely applied in school, hospital, library, warehouse, etc., especially the applications for indoor location [1], [2]. Literature [3] proposed a kind of geographical fingerprint by artificial neural network to reduce handoff delay of wireless access in vehicular environments.…”

Recent advances in location prediction methods for cellular communication networks

“…Location based services (LBSs) aim at offering both network and clients with suitable information related to the user's equipment location, reducing network load and information redundancy [1]. Location based services are limited by the mobile environment characteristics and by the user equipment performances.…”