Alicia Rodriguez-Carrion

Performance Evaluation of LZ-Based Location Prediction Algorithms in Cellular Networks

In mobile phones, it is useful to know the most probable next location to make decisions about future actions. In this letter we compare three LZ based prediction algorithms. The originality of our work is that we make it in a cellular network, we separate the algorithms into two independent phases (tree updating and probability calculation), we have included Active LeZi in the study, and we evaluate hit rate and resource consumption, including processing time.

A Bandwidth-Efficient Service for Local Information Dissemination in Sparse to Dense Roadways

Thanks to the research on Vehicular Ad Hoc Networks (VANETs), we will be able to deploy applications on roadways that will contribute to energy efficiency through a better planning of long trips. With this goal in mind, we have designed a gas/charging station advertising system, which takes advantage of the broadcast nature of the network. We have found that reducing the number of total sent packets is important, as it allows for a better use of the available bandwidth. We have designed improvements for a distance-based flooding scheme, so that it can support the advertising application with good results in sparse to dense roadway scenarios.

Impact of location history collection schemes on observed human mobility features

Human mobility knowledge is key for urban planning or mobility models design. Therefore, estimating reliable mobility parameters is crucial to lay an unbiased foundation. However, most works estimating such features rely on datasets made up of the history of mobile network cells where the user is located when she makes active use of the network, known as Call Data Records (CDRs), or every time the her device connects to a new cell, without taking into account cell changes not caused by movement. Could we accurately characterize human mobility with such datasets? In this work we consider three approaches to collect network-based mobility data, propose three filtering techniques to delete cell changes not caused by movement and compare mobility features extracted from the traces collected with each approach. The analysis unveils the need for a filtering step to avoid important biases, and the negative impact that using CDRs may have in estimating mobility parameters.

MOFETA: a network architecture based on MObile FEmtocells to enhance cellular connectivity on trains

Nowadays the quality of the indoor coverage on trains is not enough to offer broadband services, mainly due to two factors: the high penetration losses caused by Faraday cage characteristics of the railcars and the high speeds reached. In this paper we aim to enhance the 3G indoor coverage on trains by setting up femtocells inside the railcars and establishing several wireless interfaces along the roof of the train. We design an architecture to connect the train to the fixed network in a transparent manner, so that the end users do not experience service disruptions during the journey. Finally, we deploy a testbed to evaluate the performance of the mobility management system based on test results.

Entropy-Based Privacy against Profiling of User Mobility

Location-based services (LBSs) flood mobile phones nowadays, but their use poses an evident privacy risk. The locations accompanying the LBS queries can be exploited by the LBS provider to build the user profile of visited locations, which might disclose sensitive data, such as work or home locations. The classic concept of entropy is widely used to evaluate privacy in these scenarios, where the information is represented as a sequence of independent samples of categorized data. However, since the LBS queries might be sent very frequently, location profiles can be improved by adding temporal dependencies, thus becoming mobility profiles, where location samples are not independent anymore and might disclose the user’s mobility patterns. Since the time dimension is factored in, the classic entropy concept falls short of evaluating the real privacy level, which depends also on the time component. Therefore, we propose to extend the entropy-based privacy metric to the use of the entropy rate to evaluate mobility profiles. Then, two perturbative mechanisms are considered to preserve locations and mobility profiles under gradual utility constraints. We further use the proposed privacy metric and compare it to classic ones to evaluate both synthetic and real mobility profiles when the perturbative methods proposed are applied. The results prove the usefulness of the proposed metric for mobility profiles and the need for tailoring the perturbative methods to the features of mobility profiles in order to improve privacy without completely loosing utility.

A 2-D random walk mobility model for WiMAX location update

Mobile Worldwide Interoperability for Microwave Access (WiMAX) network is increasingly popular, and upcoming deployments can be expected with the development of intelligent transport systems (ITS) and the advent of smart cities. However, both applications will demand an efficient management of high mobility. Therefore, optimizing the cost of mobility signaling procedures of the network is key. In this work we study the location update procedure in WiMAX networks. Whilst previous works consider 1-D layouts of base stations (BSs), corresponding to ITS-based scenarios, we focus on extending that scenario to develop an analytical model for 2-D layouts, which fit better for cities. Our model consider the two cases in which the logical entity in charge of handling the location tracking and paging operations, known as anchor paging controller (APC), is assigned for a mobile station (MS) during a location update: when the old APC is reassigned (no relocation), and when a new APC is assigned (relocation). The comparison is made by calculating the cost (as the number of exchanged messages) of the location update procedure in each case. We validate our model through simulations, and discuss the impact on the final cost of several parameters, such as type and frequency of the movements. Finally, we provide some guidelines on how to assign the APC depending on the network parameters.

Adapting a Bandwidth-Efficient Information Dissemination Scheme for Urban VANETs

The recent release of standards for vehicular communications will hasten the development of smart cities in the following years. However, the standards do not define efficient schemes for infotainment dissemination over urban networks. These networks present special features and difficulties that may require special measures. In a previous work, we proposed three different schemes. The preliminary results of the three were satisfying but we still had to explore the values for some parameters that affect significantly their behavior. In this article, we tackle this task. Our findings clear up the strengths and weaknesses of each scheme and open the door to new advances.

A Bandwidth-Efficient Dissemination Scheme of Non-Safety Information in Urban VANETs

The recent release of standards for vehicular communications will hasten the development of smart cities in the following years. Many applications for vehicular networks, such as blocked road warnings or advertising, will require multi-hop dissemination of information to all vehicles in a region of interest. However, these networks present special features and difficulties that may require special measures. The dissemination of information may cause broadcast storms. Urban scenarios are especially sensitive to broadcast storms because of the high density of vehicles in downtown areas. They also present numerous crossroads and signal blocking due to buildings, which make dissemination more difficult than in open, almost straight interurban roadways. In this article, we discuss several options to avoid the broadcast storm problem while trying to achieve the maximum coverage of the region of interest. Specifically, we evaluate through simulations different ways to detect and take advantage of intersections and a strategy based on store-carry-forward to overcome short disconnections between groups of vehicles. Our conclusions are varied, and we propose two different solutions, depending on the requirements of the application.

Analysis of a fast LZ-based entropy estimator for mobility data

Randomness in peoples movements might serve to detect behavior anomalies. The concept of entropy can be used for this purpose, but its estimation is computational intensive, particularly when processing long movement histories. Moreover, disclosing such histories to third parties may violate user privacy. With a goal to keep the mobility data in the mobile device itself yet being able to measure randomness, we propose three fast entropy estimators based on Lempel-Ziv (LZ) prediction algorithms. We evaluated them with 95 movement histories of real users tracked during 9 months using GSM-based mobility data. The results show that the entropy tendencies of the approaches proposed in this work and those in the literature are the same as time evolves. Therefore, our proposed approach could potentially detect variations in the mobility patterns of the user with a lower computational cost. This allows to unveil shifts in the users mobility behavior without disclosing their sensible location data.

An efficient, eco-friendly approach for push-advertising of services in VANETs

Thanks to the research on VANETs, we will be able to deploy applications on highways that will contribute to the energy efficiency through a better planning of long trips. With this goal in mind, we have designed a gas/charging station advertising system, that takes advantage of the broadcast nature of the network. We have found that reducing the number of total sent packets is important, as it allows a better use of the available bandwidth. We have optimized a distance-based flooding scheme so that it can support the advertising application with good results in a highway scenario.