Location Of Mobile User Research Articles

Novel calibration algorithm for received signal strength based indoor real-time locating systems

Fingerprinting is a popular technology for indoor WLAN based locating systems. Received signal strength information from different access points is used to estimate the location of mobile users. One of the drawbacks of fingerprinting algorithm is the extensive and time-consuming calibration (training) phase, during which the received signal strength measurements from nearby wireless access points are gathered at pre-defined reference spots and stored in a database to build a prior radio signal strength map of the region.In this manuscript, we present a new, precise and time efficient calibration algorithm that combines the reference data collection procedure with the path-loss prediction model. Our algorithm requires only a few samples to be measured in a given region, and thus significantly reduces the calibration time; the rest of the signal strength database is then estimated by using path-loss prediction model. We carefully evaluate the proposed algorithm through a real-world experiment. Field test results show that our new approach reduces the calibration time without harming the location accuracy of the locating system.

Movement-aware and QoS-driven indoor location and mobile service discovery framework

The ever evolving wireless technology and the advances in mobile devices induced a growing interest in indoor location-based services ILBS. In this paper, we propose an ILBS discovery framework that finds the accurate indoor location of mobile users and provides information about services within the users' surrounding area keeping in mind the client's Quality of Service QoS. It also provides support for movement-aware services where the path the mobile user takes is recorded to provide richer awareness of the client's context than pure location. An ontology chain is proposed to support service discovery and to capture context information dynamically from different client's locations, then map it to both single and composite web services. Comprehensive experiments, comparative study with other ILBS approaches, and performance evaluation were conducted. The results demonstrate that our proposed scheme outperforms the state-of-the-art methods presented in the literature and achieves very high localisation and service discovery accuracy.

Services and Applications Based on Mobile User’s Location Detection and Prediction

Many wireless applications are deployed and available to customers via their mobile phones. Variety of these applications and services are based on determination of the current or future location of mobile user. Location based services (LBS) are one of the vital applications which are subdivided into two main categories: economical category and public category. Economic applications include mobile marketing, entertainment and tracking applications. Whereas, emergency cases, safety, traffic management, Muslims’ applications and public information applications are sort of public applications. The first part of the paper presents a new proposed system with developed procedure to recreate public and economic applications with high positioning accuracy and good authentication of users’ data. The developed system is created to enhance both location based services and network allocation resources within mobile network platform using either normal or GPS supported mobile equipment. The second part of the paper introduces future location prediction of mobile user dependent applications. New algorithm is developed depending on utilizing both intra-cell Movement Pattern algorithm (ICMP) [1] and hybrid uplink time Difference of Arrival and Assisted GPS technique (UTDOA_AGPS) [2]. It has been noticed that ICMP algorithm outperforms other future location prediction algorithms with high precision and within suitable time (less than 220) msec. However, UTDOA_AGPS guarantees high precession of mobile user independent of the surrounding environment. The proposed technique is used to enhance reliability and efficiency of location based services using cellular network platform.

Collaborative localization of mobile users with Bluetooth

Location awareness is a key requirement for many pervasive applications. Collaborative localization can improve accuracy and coverage indoors and improve power consumption by duty-cycling GPS outdoors. We use Bluetooth for collaborative localization of mobile personal devices. Specifically, we embed information in Bluetooth device names to improve latency of information exchange between participating nodes. We identify and demonstrate on real hardware two problems in the Bluetooth stack that negatively impact localization accuracy: a) device name caching that introduces significant device-specific delays in transmitting information between nodes, and b) poor accuracy of time synchronization in modern mobile devices. Our solution is to append additional time information to the device name and track time offsets between nodes. We verify experimentally that this helps to both detect outliers and correct for time-synchronization errors and thus mitigate localization errors.

On the Analysis of Random Coverage Time in Mobile LEO Satellite Communications

Deterministic models for coverage time evaluation of Low Earth Orbit (LEO) satellites constituting a mobile satellite network may tend to unreliable results due to arbitrary locations of mobile users within the satellite coverage area. This inevitable phenomenon necessitates a statistical model for coverage time assessment of LEO satellite networks. In this letter, we propose a novel approach for effective analysis of coverage times during LEO satellite visits. The analysis is particularly useful for probabilistic investigation of intersatellite handovers in LEO satellite networks and also in designing mobile satellite systems.

Mobility Prediction in Dynamic Grids

Mobile grids are one of the emerging grid types. They help to pool the resources of several cooperative mobile devices to resolve a computationally intensive task. Mobility management is a key challenge in mobile grids which includes mechanisms to track and maintain the locations of mobile nodes. Mobility prediction is one of the most important components of mobility management, which defined as proactively tracking the future locations of mobile users. In this paper we introduce a straight forward mobility predictor that can predict the future locations of mobile users and the duration for which the users will remain in those locations.

User's Profile Replication Tree and On Demand Replica Update in Wireless Communication

Replication strategy is mostly useful for replicating the called mobile user's profile at selected locations where some caller mobile users have higher calling rate. It plays important role in personal communication services (PCS) in order to reduce call setup cost and call setup time. In prior replication schemes, replicated sites (visitor location registers) have no inter relationship. We have proposed a novel and innovative replication tree which is buildup from replicated VLRs (visitor location registers). VLRs are replicated based on effective replication probability of caller mobile user. Home location register (HLR) keeps update replica at root VLR in the replication tree and root VLR forwards update replica to a VLR in the replication tree on demand. The main objective of the proposed scheme is to reduce call setup time and call setup cost by enabling replication of called mobile user's location profile at certain visitor location registers (VLRs) where caller mobile user roams. We have presented analytical modeling which shows that setting inter-relationship among the replicated sites helps in further reducing the call setup cost.

A profile anonymization model for location-based services

Location-based services LBS aim at delivering point of need information. Personalization and customization of such services, based on the profiles of mobile users, would significantly increase the value of such services. Since profiles may include sensitive information of mobile users and moreover can help identify a person, such customization is allowable only when the security and privacy policies dictated by them are respected. While LBS providers are presumed to be untrusted entities, the location services that capture and maintain mobile users' location to enable communication are considered trusted, and therefore can capture and manage the profile information. The question then is, how to enable the use of location based services while protecting privacy?In this paper, we address the problem of privacy preservation via anonymization. Prior research in this area attempts to ensure k-anonymity by generalizing the location. However, a person may still be identified based on his/her profile if the profiles of all k people in the generalized region are not the same. We extend the notion of k-anonymity by proposing a profile based k-anonymization model that guarantees anonymity even when profiles of mobile users are revealed to untrusted entities. Specifically, our anonymization methods generalize both location and profiles to the extent specified by the user. We propose a novel unified index structure, called the PTPR-tree to enhance the performance during anonymization. PTPR-tree is an extension of the TPR-tree [in: SIGMOD'00: Proceedings of the 2000 ACM SIGMOD International Conference on Management of Data, New York, NY, USA, ACM, 2000, pp. 331--342] which organizes both the locations of mobile users as well as their profiles using a single index, and therefore can efficiently find candidate users for the proposed profile based anonymization models.

MAP BASED INTRA-CELL METHOD FOR LOCATION PREDICTION OVER UMTS NETWORK PLATFORM

Location based services (LBS) and their applications are regarded as the mostgrowing services applied on communication systems. According to the greatenhancement in the mobile network platform and its related database servers,we are not only able to develop LBS applications but also to enhance theperformance of mobile networks. Future location prediction of mobile userresults in great enhancement in LBS applications and mobile networkperformance. Many researches were introduced to predict location of mobileuser. In [7] User Mobility Pattern (UMP) algorithm based on sequentialmining prediction has been developed to deal with future location prediction inmobile networks. The main limitations of this pattern are: map based intra cellprediction cannot be extracted and the timestamps aren't associated with rules.In [8], another method has been introduced using All frequent MovementPattern (ALLMOP) algorithm for extracting all frequent movement patternswithin movement Rule based Location Prediction method (RLP). RLP methodworks on GPS network map based platform without manipulating cell to cellmovement. So, it can't be used to enhance mobile network's resource allocationand mobility management. In this paper we proposed a new method, Intra CellMovement Prediction (ICMP), for mobile user's future location prediction onUniversal Mobile Telecommunication System (UMTS) environments to benefitfrom both intra and inter cell based techniques for both network and servicesenhancement. The proposed method depends on map based intra-cellprediction and utilizes the network database and positioning techniques inextracting user trajectories and movement rules. As a result, the user positioncan be predicted for the next movement step. The performance of the proposedalgorithm is evaluated through computer simulation and compared with that of[7] and [8]. The simulation results indicate that the proposed method is highlyefficient for both network and services' improvements as it is used to enhancelocation based services with satisfactory accuracy, network's resourceutilization, reduce the latency in accessing resources and mobilitymanagement.

The Virtual Overlap Region with Forwarding Pointer (VORFP) Technique for Tracking Mobile Users in Personal Communication Systems

Reducing the volume of location updates and cost of searching for location information are two important issues for tracking mobile users in personal communication systems. Many approaches have been proposed to improve both the location update traffic and searching costs. Some of these approaches can reduce access cost and some other approaches can reduce the location update cost and location update rate. In this paper, we shall propose a new approach for reducing both location update cost and searching cost (for finding mobile users location information). The new scheme called Virtual Overlap Region with Forwarding Pointer (VORFP) uses the forwarding pointer and the virtual overlap region concepts. The virtual overlap region technique is a good method for reducing the location update traffic, especially when a user backs and forths between adjacent cells. Our performance evaluations show that VORFP can significantly reduce searching cost and update cost.

Extreme learning machine for user location prediction in mobile environment

PurposePrediction accuracies are usually affected by the techniques and devices used as well as the algorithms applied. This work aims to attempt to further devise a better positioning accuracy based on location fingerprinting taking advantage of two important mobile fingerprints, namely signal strength (SS) and signal quality (SQ) and subsequently building a model based on extreme learning machine (ELM), a new learning algorithm for single‐hidden‐layer neural networks.Design/methodology/approachPrediction approach to location determination based on historical data has attracted a lot of attention in recent studies, the reason being that it offers the convenience of using previously accumulated location data to subsequently determine locations using predictive algorithms. There have been various approaches to location positioning to further improve mobile user location determination accuracy. This work examines the location determination techniques by attempting to determine the location of mobile users by taking advantage of SS and SQ history data and modeling the locations using the ELM algorithm. The empirical results show that the proposed model based on the ELM algorithm noticeably outperforms k‐Nearest Neighbor approaches.FindingsWiFi's SS contributes more in accuracy to the prediction of user location than WiFi's SQ. Moreover, the new framework based on ELM has been compared with the k‐Nearest Neighbor and the results have shown that the proposed model based on the extreme learning algorithm outperforms the k‐Nearest Neighbor approach.Originality/valueA new computational intelligence modeling scheme, based on the ELM has been investigated, developed and implemented, as an efficient and more accurate predictive solution for determining position of mobile users based on location fingerprint data (SS and SQ).

A New Algorithm to Mitigate NLOS Errors in Cellular Networks

摘要: 非视距传播(NLOS)误差是目前基于蜂窝网络的移动台定位系统提高定位精度必须解决的关键问题,该文提出一种基于概率密度估计和偏差Kalman滤波器的NLOS误差无偏估计算法。仿真结果表明,该算法在性能上优于现有同类算法,并且算法对环境先验知识的需求更少,具有更广泛的适用性。 关键词: 无线定位; 非视距传播误差; 概率密度估计; Kalman滤波

An adaptive distance‐based location management of LEO system using coordinates approach

PurposeThe purpose of this paper is to introduce a simplified method to do the mobility management in the low earth orbit (LEO) system. With experimentations, the method is thereafter evaluated.Design/methodology/approachThe approach is introduced to implement the distance‐based strategy by using the coordinates. The users update their coordinates to the networking and the system computers which satellite and which beam can cover the user being called at real time.FindingsIn managing the location of mobile users in mobile communication systems, the distance‐based strategy has been proven to have better performance than other dynamic strategies, but difficult to implement. The approach introduced in this paper implements the distance‐based strategy by using the coordinates.Originality/valueThis method makes full use of the characters of the LEO system and refutes the apparent weakness that location management area is restricted by the establishment on the ground. The simulation result proves that this method is efficient.

Locating Mobile Users Using Base Stations of Cellular Networks

The location of mobile users served by cellular networks is considered. The chosen approach assumes that location is estimated through angular triangulation with three base stations (BSs). New estimates are proposed, which are described by closed-form expressions, and are alternatives to the maximum likelihood estimate. It is shown that the accuracy of the estimate coinciding with incircle center of the bearing triangle is close to the accuracy of the maximum likelihood estimate.

Anonymization models for directional location based service environments

Location based services (LBS) aim to deliver information based on a mobile user's location. However, knowledge of the location can be used by an adversary to physically locate the person, leading to the risk of physical harm, as well as possible leakage of certain personal information. This has serious consequences on privacy. The concept of location k-anonymity has been proposed to address this. Under this notion of anonymity, the adversary only has the knowledge that the LBS request is originating from a region containing at least k people, and therefore cannot individually distinguish the user. However, the existing anonymity models ignore the movement information of mobile users, assuming that it has no impact on privacy. Thus, existing work cannot ensure complete privacy while serving advanced type of LBS requests that require information about direction as well as speed of motion. We denote such LBS services as directional LBS. The key observation we make in this paper is that, in addition to the user's location, the user's movement direction should also be considered to ensure true anonymization. In this paper, we extend the notion of location k-anonymity by incorporating user's moving direction into the anonymization process while serving directional LBS. Specifically, our anonymization methods generalize both location and direction to the extent specified by the user. Our experimental results demonstrate that such anonymization can be achieved with marginal increase in computational cost when compared to the traditional location k-anonymity, while providing increased anonymity.

Evaluation of position tracking technologies for user localization in indoor construction environments

Evolving technologies such as location-aware computing offer significant potential of improving important decision-making tasks on construction sites by providing support for tedious and time-consuming tasks associated with timely and accurate access to project information. For example, rapid and convenient access to contextual project information, through continuous position tracking of engineers, managers, and inspectors, can lead to significant cost and time savings due to the accuracy and immediacy with which relevant project information can be made available to field personnel. Considering the spatial expanse and dynamic nature of typical construction projects, mobile users need to be constantly tracked both outdoors as well as indoors. The Global Positioning System (GPS) is an attractive option for outdoor environments, but is not suitable for indoor applications because it needs a clear line-of-sight to orbital satellites in order to track position. As a result, alternate means of tracking users' location in indoor environments without relying on GPS is needed. This paper presents research that investigated the effectiveness of three wireless technologies for dynamic indoor user position tracking. In particular, Wireless Local Area Networks (WLAN), Ultra-Wide Band (UWB), and Indoor GPS positioning systems are evaluated and compared. Experimental results demonstrate the ability of Indoor GPS, in particular, to estimate a mobile user's location with relatively low uncertainty (1 to 2 cm).

A method for predicting future location of mobile user for location-based services system

Convergence of location-aware devices, wireless communications, and geographic information system (GIS) functionalities has been enabling the deployment of a new generation of selective information disseminating services and location-based services (LBSs). Current LBSs use information about current locations of users to provide services, such as nearest features of interest, they request. Although the common computing strategy in LBSs benefits the users, there are additional benefits when future locations are predicted. One major advantage of location prediction is that it provides LBSs with extended resources, mainly time, to improve system reliability which in turn increases the users’ confidence and the demand for LBSs. In this study, we propose a movement Rule-based Location Prediction method (RLP), to guess the user’s future location for LBSs. Its performance is assessed with respect to precision and recall. In comparison with the previous technique, the prediction accuracy of ours is higher. With the proposed approach, we give an efficient support to the LBSs provider in monitoring user intelligently and sending information to user in a push-driven fashion. Apart from the support of timely and desired services and enhanced automation, the technique helps overcome some existing issues such as network flooding due to the massive tracking of users, the latencies of the positioning systems in providing and information delivery. Accordingly, the positioning is more reliable, which enables the service provider to effectively and efficiently offer location-based services with high frequency.

A future location‐aware replacement policy for the cache management at the mobile terminal

AbstractWhile the traditional data shipping systems use physical information to organize data, a newer data caching technique maintains both associated answers (data items) of previous queries and their meaning (purpose). This form of information description is called semantic description, and it makes it possible to reason about and derive knowledge from the given description. In a distributed heterogeneous environment, such as the mobile environment, the semantic data caching paradigm is an important technique for improving the performance of wireless data dissemination systems. Data caching performance depends heavily on the replacement policy being used for the cache management. However, future location uncertainty, limited client resources and frequent client disconnections make cache management a challenge.This paper proposes a future location‐aware cache replacement policy to manage a semantic cache. The proposed replacement policy uses the validity of the data fetched from the server and the neighboring locations to decide which of the cache entries is less likely to be needed in the future, and therefore a good victim for eviction when cache space is needed. The replacement policy's preference for cached items to be evicted is modeled as a general function that declines with distance between the mobile user's current location and the candidate for replacement cached item's bound location. For better efficiency, the overall replacement granularity is dynamically achieved along three levels: ring, cell and data item. Simulation study of the proposed approach shows that it outperforms both the least recently used (LRU) and furthest away replacement (FAR) schemes, where only temporal locality is considered. Moreover, the proposed scheme is easier to implement than other research and development proposals. Copyright © 2008 John Wiley & Sons, Ltd.

Location privacy in a ubiquitous computing society

The ability to identify the exact geographical location of a mobile user at any time and to provide users of mobile devices with personalised applications tailored to their current location is at the core of the future ubiquitous computing society. Ubiquitous access to information anywhere and anytime and the ever faster, smaller and omnipresent computing devices will enable the constant collection and transmission of personal data without it being apparent to the user. This implies that maintaining privacy in a future ubiquitous computing society is a complex task involving several levels of activities to take account of the changed context.

A New Data Encryption Algorithm Based on the Location of Mobile Users

The wide spread of WLAN and the popularity of mobile devices increases the frequency of data transmission among mobile users. However, most of the data encryption technology is location-independent. An encrypted data can be decrypted anywhere. The encryption technology cannot restrict the location of data decryption. In order to meet the demand of mobile users in the future, a location-dependent approach, called location-dependent data encryption algorithm (LDEA), is proposed in this paper. A target latitude/longitude coordinate is determined firstly. The coordinate is incorporated with a random key for data encryption. The receiver can only decrypt the ciphertext when the coordinate acquired from GPS receiver is matched with the target coordinate. However, current GPS receiver is inaccuracy and inconsistent. The location of a mobile user is difficult to exactly match with the target coordinate. A toleration distance (TD) is also designed in LDEA to increase its practicality. The security analysis shows that the probability to break LDEA is almost impossible since the length of the random key is adjustable. A prototype is also implemented for experimental study. The results show that the ciphertext can only be decrypted under the restriction of TD. It illustrates that LDEA is effective and practical for data transmission in mobile environment.