A new splitting-based displacement prediction approach for location-based services

Abstract

(2011). A new splitting-based displacement prediction approach for location-based services. In: IEEE international conference on systems, man, and cybernetics 2011. IEEE Xplore, 392-397. Abstract-In location-based services (LBSs), the service is provided based on the users' locations through location determination and mobility realization. Several location prediction models have been proposed to enhance and increase the relevance of the information retrieved by users of mobile information systems, but none of them studied the relationship between accuracy rate of prediction and the performance of the model in terms of consuming resources and constraints of mobile devices. Most of the current location prediction research is focused on generalized location models, where the geographic extent is divided into regular-shape cells. These models are not suitable for certain LBSs where the objectives are to compute and present on-road services. One such technique is the Prediction Location Model (PLM), which deals with inner cell structure. The PLM technique suffers from memory usage and poor accuracy. The main goal of this paper is to propose a new path prediction technique for Location-Based Services. The new approach is competitive and more efficient compared to PLM regarding measurements such as accuracy rate of location prediction and memory usage. Copyright and re-use policy

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

“…The authors in [26] introduced a new Splitting-based Displacement Prediction Approach for Location-Based Services (SDPA). The model reduced the service area to be less than the cell.…”

“…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.…”

An Enhanced Ant Colony Optimization for Routing Area Mobility Prediction over Cellular Communications Network

“…A new Splitting-based Displacement Prediction Approach for Location-Based Services (SDPA) (Daoud et al, 2011) has been developed to improve prediction rate, minimizes consumption of resources, and the overall cost of the location management process comparing with PLM. Also, the SDPA reduces the service area and the number of predicted routes during the mobile user trip, by dividing the cell into eight equivalent regions.…”

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

“…A new splitting-based displacement prediction approach for location-based services (SDPA) [25] has been developed to improve the prediction rate. On the other hand, SDPA reduced the service area in a static manner that is not applicable for a cellular communication network.…”