Mobile location indexing based on synthetic moving objects
International Journal of Electrical and Computer Engineering (IJECE)2019, International Journal of Electrical and Computer Engineering (IJECE)
https://doi.org/10.11591/ijece.v9i4.pp2556-2563
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Abstract
Today, the number of researches based on the data they move known as mobile objects indexing came out from the traditional static one. There are some indexing approaches to handle the complicated moving positions. One of the suitable ideas is pre-ordering these objects before building index structure. In this paper, a structure, a presorted-nearest index tree algorithm is proposed that allowed maintaining, updating, and range querying mobile objects within the desired period. Besides, it gives the advantage of an index structure to easy data access and fast query along with the retrieving nearest locations from a location point in the index structure. A synthetic mobile position dataset is also proposed for performance evaluation so that it is free from location privacy and confidentiality. The detail experimental results are discussed together with the performance evaluation of KDtree-based index structure. Both approaches are similarly efficient in range searching. However, the proposed approach is especially much more save time for the nearest neighbor search within a range than KD tree-based calculation. 1. INTRODUCTION With advances in location-based services (LBSs), mobile devices and telecommunication systems are the vital support for the positioning and tracking of moving mobile objects [1]. Besides, the increasing numbers of mobile users are already emerged along with the improvement of new technologies. So, using the mobile phone is the main function on a daily requirement with the user's search queries. Most of the required queries or information is usually based on current or anticipated locations. For example, searching nearest restaurants, viewing the route and inquiry required information are the user required queries which are supported by pop technology [2]. This technology normally based on static data or locations. In addition, the services such as receiving weather information, emergency alerts, advertisement getting access to what's known as automatic notifications are aided by push technology [3]. This service is usually based on moving positions or current mobile positions. In such environments, mobile devices regularly send their current locations to a server. The server receives the current locations and processes desired queries such as "which mobiles are currently located within the desired area". To reply such queries appropriately, the application server has to search all of the current mobile locations that are in the desired area. Therefore, an appropriate structure and searching method for the nearest are required. Generally, the nearest searching technique can be divided into two parts: structureless technique and structure-based technique. For example, a well-known technique such as k the nearest neighbor is a structureless technique and it is very easy to implement. The general work of structureless technique is that distance is calculated from all nodes to the service node of a query and the node with the closest distance is regarded as the nearest neighbor [4-5]. These techniques are very simple but the value of k affects the result. To provide the speed of query and memory requirement, a variety of tree-based index structures called structure-based techniques are applied in many areas.
