scholarly journals On Location-based Services Build on the Close Patial Position of Mobile Devices

2020 ◽  
Vol 14 ◽  
Keyword(s):  
Mobile Devices ◽  
Location Based Services ◽  
Location Information ◽  
Cyber Physical System ◽  
Spatial Network ◽  
Network Nodes ◽  
Classical Architecture ◽  
Service Models ◽  
Network Proximity ◽  
Architectural Models

This article focuses on architectural models of location-based services. The paper discusses the model of spatial network proximity, within which the classical architecture of services using location information, based on the use of geo-coordinates data provided by users, is replaced by some distributed cyber-physical system. Within the network proximity model, geo-computation is replaced by the direct proximity definitions. And this very proximity measurement is based on determining the availability (visibility) of the signals of the wireless network nodes. This article discusses how to build new service models using location information.

Location Information Management in LBS Applications

2011 ◽  
pp. 2450-2455 ◽  
Author(s):  
Anselmo Cardoso de Paiva ◽  
Erich Farias Monteiro ◽  
Jocielma Jerusa Leal Rocha ◽  
Claudio de Souza Baptista ◽  
Aristófanes Corrêa Silva
Keyword(s):  
Mobile Devices ◽  
Positional Information ◽  
Market Potential ◽  
Location Based Services ◽  
Location Information ◽  
Software Applications ◽  
New Applications ◽  
Application Developers ◽  
Services Effectiveness ◽  
Climatic Information

The mobile computing advent brings a set of new applications that benefit from the constant need of information, diminishing communication costs and favoring the popularization of mobile devices, to reach an increasing number of users. The mobility characteristic opens a new area for software applications. Associated to the mobility we have the location identification, which turns into a critical attribute, once it allows the development of a great variety of new services and applications. The systems that benefit from the use of that location information are named locationbased systems (LBS); alternatively, these applications are also known as location-aware, context-aware, or adaptive information systems More precisely, we can define LBS as applications that use the location information to supply services, based on this position context, to their users (Kupper, 2005; Schiller & Voisard, 2004). The user location information makes available completely new and innovative service concepts, offering information to the user based on its own context (e.g., climatic information in the region where the user is located), increasing considerably the utility of these services. We know that location- based applications increase the services effectiveness, as they give a customized access to the data based on the user’s preferences and on its actual position. This enhances the personalization content, giving several benefits to users and to the application developers. In our daily life, several activities may use these services, like the emergency call centers, the car navigation services, and even location-based friend finder. We may verify that, beyond the already cited characteristics and benefits, what also gave the LBS applications a growing perspective were the location techniques modernization and the mobile devices popularization, enabling the offer of more precise, objective, and useful information. In Shiode et al. (Shiode, Li, Batty, Longley, & Maguire, 2002), research shows the trend of LBS market and the market potential reserved to this class of applications that, each year, turns out to be more important to the users, becoming the area that dominates the applications for mobile devices. According to Sayed (2005), the forecast annual revenues for location-based services was estimated in US $3.3 billions for United States in 2006/2007, and in US $11.7 billions on the other countries. In summary, we may say that the positional information has the potential to explore the user’s geographical context as one of the most important variables for content and services personalization for mobile devices users.

scholarly journals Privacy perception in location-based services for mobile devices in the university community of the north coast of Colombia

2019 ◽  
Vol 23 (1) ◽  
Author(s):  
Margarita Gamarra ◽  
Inés Meriño Fuentes ◽  
Juan Calabria Sarmiento ◽  
Omar Gutierrez Acosta ◽  
Mauricio Barrios Barrios ◽  
...  
Keyword(s):  
Mobile Devices ◽  
Private Information ◽  
Location Privacy ◽  
Location Based Services ◽  
North Coast ◽  
Location Information ◽  
Privacy Management ◽  
The North ◽  
The University ◽  
University Community

Introduction: The use of mobile applications has increased in the last years. Most of them require the knowledge of the user location, either for their core service or for marketing purposes. Location-based services (LBS) offer context-based assistance to users based on their location. Although these applications ask the user for permission to use their location and even explain in detail how this information will be used in its terms and conditions, most users are not aware or even interested in the fact that their location information is stored in databases and monetized by selling it to third-party companies. Regarding this situation, we developed a study with the aim to assess perception, concerns and awareness from users about their location information. Methods: This work is based on an exploratory survey applied to the university community, mainly from the North Coast of Colombia, to measure the perception of location privacy of users with mobile devices. The questionnaire was applied using Google Forms. The survey has nineteen questions organized in three sections: personal information, identification of privacy and privacy management. These questions were designed to know the users’ perceptions of privacy concerns in LBS and any actions they take to preserve it. Results: The results show that, in general, the respondents do not have a real concern regarding the privacy of their geolocation data, and the majority is not willing to pay to protect their privacy. Conclusions: This type of surveys can generate awareness among participants about the use of their private information. The results expose in this paper can be used to create government policies and regulations by technology companies about the privacy management.

scholarly journals Offloading Method for Efficient Use of Local Computational Resources in Mobile Location-Based Services Using Clouds

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Yunsik Son ◽  
Yangsun Lee
Keyword(s):  
Mobile Computing ◽  
Mobile Devices ◽  
Communication Networks ◽  
Fog Computing ◽  
Computing System ◽  
Location Based Services ◽  
Computation Offloading ◽  
Smart Devices ◽  
Smart Device ◽  
Location Information

With the development of mobile computing, location-based services (LBSs) have been developed to provide services based on location information through communication networks or the global positioning system. In recent years, LBSs have evolved into smart LBSs, which provide many services using only location information. These include basic services such as traffic, logistic, and entertainment services. However, a smart LBS may require relatively complicated operations, which may not be effectively performed by the mobile computing system. To overcome this problem, a computation offloading technique can be used to perform certain tasks on mobile devices in cloud and fog environments. Furthermore, mobile platforms exist that provide smart LBSs. The smart cross-platform is a solution based on a virtual machine (VM) that enables compatibility of content in various mobile and smart device environments. However, owing to the nature of the VM-based execution method, the execution performance is degraded compared to that of the native execution method. In this paper, we introduce a computation offloading technique that utilizes fog computing to improve the performance of VMs running on mobile devices. We applied the proposed method to smart devices with a smart VM (SVM) and HTML5 SVM to compare their performances.

scholarly journals Privacy vs. Reward in Indoor Location-Based Services

2016 ◽  
Vol 2016 (4) ◽  
pp. 102-122 ◽  
Author(s):  
Kassem Fawaz ◽  
Kyu-Han Kim ◽  
Kang G. Shin
Keyword(s):  
Location Privacy ◽  
Indoor Localization ◽  
Service Providers ◽  
Location Based Services ◽  
Location Information ◽  
Privacy Concerns ◽  
Indoor Location ◽  
Location Data ◽  
Personalized Services ◽  
Privacy Risks

AbstractWith the advance of indoor localization technology, indoor location-based services (ILBS) are gaining popularity. They, however, accompany privacy concerns. ILBS providers track the users’ mobility to learn more about their behavior, and then provide them with improved and personalized services. Our survey of 200 individuals highlighted their concerns about this tracking for potential leakage of their personal/private traits, but also showed their willingness to accept reduced tracking for improved service. In this paper, we propose PR-LBS (Privacy vs. Reward for Location-Based Service), a system that addresses these seemingly conflicting requirements by balancing the users’ privacy concerns and the benefits of sharing location information in indoor location tracking environments. PR-LBS relies on a novel location-privacy criterion to quantify the privacy risks pertaining to sharing indoor location information. It also employs a repeated play model to ensure that the received service is proportionate to the privacy risk. We implement and evaluate PR-LBS extensively with various real-world user mobility traces. Results show that PR-LBS has low overhead, protects the users’ privacy, and makes a good tradeoff between the quality of service for the users and the utility of shared location data for service providers.

ILSSPP: Intelligent location sharing system with privacy preserving features for smart cities

2021 ◽  
pp. 1-12
Author(s):  
Gokay Saldamli ◽  
Richard Chow ◽  
Hongxia Jin
Keyword(s):  
Service Providers ◽  
Smart Cities ◽  
User Interaction ◽  
Privacy Preserving ◽  
Location Based Services ◽  
Third Party ◽  
Location Information ◽  
Fine Grained ◽  
Location Sharing ◽  
Social Network Structure

Social networking services are increasingly accessed through mobile devices. This trend has prompted services such as Facebook and Google+to incorporate location as a de facto feature of user interaction. At the same time, services based on location such as Foursquare and Shopkick are also growing as smartphone market penetration increases. In fact, this growth is happening despite concerns (growing at a similar pace) about security and third-party use of private location information (e.g., for advertising). Nevertheless, service providers have been unwilling to build truly private systems in which they do not have access to location information. In this paper, we describe an architecture and a trial implementation of a privacy-preserving location sharing system called ILSSPP. The system protects location information from the service provider and yet enables fine grained location-sharing. One main feature of the system is to protect an individual’s social network structure. The pattern of location sharing preferences towards contacts can reveal this structure without any knowledge of the locations themselves. ILSSPP protects locations sharing preferences through protocol unification and masking. ILSSPP has been implemented as a standalone solution, but the technology can also be integrated into location-based services to enhance privacy.

Mobile Crowd-sensing Applications: Data Redundancies, Challenges, and Solutions

2022 ◽  
Vol 22 (2) ◽  
pp. 1-15
Author(s):  
Tu N. Nguyen ◽  
Sherali Zeadally
Keyword(s):  
Mobile Devices ◽  
Cyber Physical System ◽  
Redundant Information ◽  
Mobile Crowd Sensing ◽  
Sensing System ◽  
Sensing Systems ◽  
Sensing Applications ◽  
Crowd Sensing ◽  
Mobile Crowd ◽  
Collection Methods

Conventional data collection methods that use Wireless Sensor Networks (WSNs) suffer from disadvantages such as deployment location limitation, geographical distance, as well as high construction and deployment costs of WSNs. Recently, various efforts have been promoting mobile crowd-sensing (such as a community with people using mobile devices) as a way to collect data based on existing resources. A Mobile Crowd-Sensing System can be considered as a Cyber-Physical System (CPS), because it allows people with mobile devices to collect and supply data to CPSs’ centers. In practical mobile crowd-sensing applications, due to limited budgets for the different expenditure categories in the system, it is necessary to minimize the collection of redundant information to save more resources for the investor. We study the problem of selecting participants in Mobile Crowd-Sensing Systems without redundant information such that the number of users is minimized and the number of records (events) reported by users is maximized, also known as the Participant-Report-Incident Redundant Avoidance (PRIRA) problem. We propose a new approximation algorithm, called the Maximum-Participant-Report Algorithm (MPRA) to solve the PRIRA problem. Through rigorous theoretical analysis and experimentation, we demonstrate that our proposed method performs well within reasonable bounds of computational complexity.

scholarly journals Trusted Base Stations-Based Privacy Preserving Technique in Location-Based Services

2015 ◽  
Vol 8 (4) ◽  
pp. 93
Author(s):  
Muhammad Aqib ◽  
Jonathan Cazalas
Keyword(s):  
Optimal Path ◽  
Specific Area ◽  
Daily Basis ◽  
Location Based Services ◽  
Base Stations ◽  
The Internet ◽  
Location Information ◽  
Google Maps ◽  
Privacy Issue ◽  
Internet Technologies

With the advent in mobile and internet technologies, there is a significant increase in the number of users using smartphones and other internet based applications. There are a large number of applications available online that use the internet and provide useful information to the users. These include ones that provide location-based services e.g. google maps etc. These applications provide many facilities to the users who want information regarding a specific area or directions using an optimal path to a destination. Due to these reasons, the number of clients using these applications is increasing on a daily basis. Although these services are very useful and are making it easy for us to get information about our surroundings, some issues are also linked with the use of these applications and their services. One of the more significant issues of using these services is privacy with respect to sending personal location information to location-based services servers. Researchers have provided many solutions to solve these issues. One of the solutions is through caching and use of k-anonymity techniques. In this paper, we have proposed a method to solve the privacy issue that uses caching data approach to reduce the number of queries sent to the location-based services server. We also discuss the use of the concept of k-anonymity when no relevant data is available in cache, and queries are sent to the server.

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