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Follow that Light: Leveraging LEDs for Relative Two-Dimensional Localization
Get PDFVisible light is gaining significant attention as a medium to achieve accurate relative localization. Most of the studies in the area focus on indoor positioning and rely on two important assumptions: (i) lights are static, and (ii) the receiver has line-of-sight with multiple lights.
These requirements limit the application of localization methods in scenarios where nodes have a single light and are mobile, such as motorbikes or swarms of robots. In general, this particular type of scenarios (single lights moving on a plane) leads to under-determined localization systems where no unique solution can be found. We follow a holistic approach that includes theory, simulations, and experiments to overcome some of the limitations present in such type of scenarios. Our theoretical and simulation results show that if nodes are enhanced with sensors providing relative directions (such as compasses), we can derive dependencies in the system to obtain unique solutions. Our proof-of-concept implementation validates our model by showing that single lights can provide relative localization with high accuracy: an average error below 5cm.TRUEpu
Characterising users experience and critical path in mobile applications
No full textUsers Quality of Experience (QoE) analysis is paramount for telcos to drive business, and for users to verify their SLAs with the operators. Over the years both academia and industry put a lot of efforts to define methodologies and create tools to monitor QoE. In particular, web traffic QoE analysis is a well understood and ``standardized'' research area, and a varied set of tools and metrics are available to understand how content is delivered. For instance, it is easy to capture the interaction of a browser with a website (e.g., as HAR objects), to inspect content delivery critical path via the download waterfall (e.g., via Chrome, or tools like WProf), or quantify webpage retrieval performance via page load time (PLT), or Google speed index.
These tools and techniques suit well fixed access networks but cannot be directly applied to analyze mobile user QoE. Indeed, most of mobile traffic is generated by large number of applications and do not resemble to traditional web browsing traffic. Also, mobile architectures are more complex than fixed infrastructures and their main performance bottleneck is latency. In this work, we consider QoE for mobile applications by focusing on network level metrics and taking into account application level information. The main goal is to identify network activities (as DNS lookup, TCP and TLS handshake, content download, etc.) which are bottlenecks for application performance and propose countermeasures. To achieve this objective we combine active and passive on-device measurements.
On the one hand, we developed an app that leverages the Android VPN APIs (i.e., it does not require rooted devices) to monitor network traffic, while collecting also info about user activity with the device. This enable us to analyze mobile apps traffic in different scenarios (e.g., application startup, application in background/foreground without user activity, user interaction) and develop techniques to reconstruct the networking waterfall for each of them, similarly to what is currently possible for generic web browsing traffic. However, we envision a generic mobile device system component capable to inspect all traffic, and possibly tapping into user engagement (e.g., interactivity with the screen). By analysing the waterfall we aim to identify activities constituting the critical path for each scenario and application.
On the other hand, the monitoring app allows to schedule active experiments. This allows us to define a comparison baseline to contrast against other analysis, as well as further diagnose problems when the waterfall analysis suggests there may be a bottleneck.
In the poster, we present the methodology and preliminary results on a small set of applications in a testbed with real devices.TRUEpu
A Data-driven Method for the Detection of Close Submitters in Online Learning Environments
Get PDFOnline learning has become very popular over the last decade. However, there are still many details that remain unknown about the strategies that students follow while studying online. In this study, we focus on the direction of detecting 'invisible' collaboration ties between students in online learning environments. Specifically, the paper presents a method developed to detect student ties based on temporal proximity of their assignment submissions. The paper reports on findings of a study that made use of the proposed method to investigate the presence of close submitters in two different massive open online courses. The results show that most of the students (i.e., student user accounts) were grouped as couples, though some bigger communities were also detected. The study also compared the population detected by the algorithm with the rest of user accounts and found that close submitters needed a statistically significant lower amount of activity with the platform to achieve a certificate of completion in a MOOC. These results confirm that the detected close submitters were performing some collaboration or even engaged in unethical behaviors, which facilitates their way into a certificate. However, more work is required in the future to specify various strategies adopted by close submitters and possible associations between the user accounts.TRUEpu
Intelligent Gaming for Mobile Crowd-Sensing Participants to Acquire Trustworthy Big Data in the Internet of Things
Get PDFIn mobile crowd-sensing systems, the value of crowd-sensed big data can be increased by incentivizing the users appropriately. Since data acquisition is participatory, crowd-sensing systems face the challenge of data trustworthiness and truthfulness assurance in the presence of adversaries whose motivation can be either manipulating sensed data or collaborating unfaithfully with the motivation of maximizing their income. This paper proposes a game theoretic methodology to ensure trustworthiness in user recruitment in mobile crowd-sensing systems. The proposed methodology is a platform-centric framework that consists of
three phases: user recruitment, collaborative decision making on trust scores, and badge rewarding. In the proposed framework, users are incentivized by running sub-game perfect equilibrium and gamification techniques. Through simulations, we show that approximately 50% and a minimum of 15% improvement can be achieved by the proposed methodology in terms of platform and user utility, respectively, when compared with fully distributed and user-centric trustworthy crowd-sensing.pu
Lightweight and Effective Sector Beam Pattern Synthesis with Uniform Linear Antenna Arrays
Get PDFIn this letter, we present a lightweight and effective
method for the synthesis of sector beam patterns using uniform linear arrays. With the objective to approximate a desired array-factor response, we formulate an optimization problem which can be simplified and solved in closed form assuming real instead of complex array weights. As a solution to this problem, we derive a compact expression to compute the optimal array weights as a function only of the desired beamwidth and steering direction. Numerical experiments demonstrate that, compared to classical, state-of-the-art techniques, our solution can better approximate
the target radiation mask, yet requires one order of magnitude lower computational complexity.
Demo: https://joanguitar.github.io/beam-patterns/
https://joanguitar.github.io/beam-patterns/
Repositorio: https://github.com/Joanguitar/beam-patterns
https://github.com/Joanguitar/beam-patternspu
Route or Carry: Motion-driven Packet Forwarding in Micro Aerial Vehicle Networks
Get PDFMicro aerial vehicles (MAVs) provide data such as images
and videos from an aerial perspective, with data typically transferred to the ground. To establish connectivity in larger areas, a fleet of MAVs may set up an ad-hoc wireless network. Packet forwarding in aerial networks is challenged by unstable link quality and intermittent connectivity caused by MAV movement. We show that signal obstruction by the MAV frame can be alleviated by adapting the MAV platform, even for low-priced MAVs, and the aerial link can be properly characterized by its geographical distance. Based on this link characterization and making use of GPS and inertial sensors on-board of MAVs, we design and implement a motion-driven packet forwarding algorithm. The algorithm unites location-aware end-to-end routing and delay-tolerant forwarding, extended by two predictive heuristics. Given the current location, speed, and orientation of the MAVs, future locations are estimated and used to refine packet forwarding decisions. We study the forwarding algorithm in a field measurement campaign with quadcopters connected over Wi-Fi IEEE 802.11n, complemented by simulation. Our analysis confirms that the proposed algorithm masters intermittent connectivity well, but
also discloses inefficiencies of location-aware forwarding. By anticipating motion, such inefficiencies can be counteracted and the forwarding performance can be improved.pu
Energy footprint reduction in 5G reconfigurable hotspots via function partitioning and bandwidth adaptation
Get PDFCloud-based radio access networks (C-RAN) are expected to face important challenges in the forthcoming fifth generation (5G) communication systems. For this reason, more flexible C-RAN architectures have recently been proposed in the literature, where the radio communication stack is partitioned and placed across different RAN nodes to tackle the 5G capacity and latency requirements. In this paper, we show that this functional split also supports energy efficiency, especially when it is combined with bandwidth adaptation. To this aim, we have built a dynamic hotspot prototype, where the hardware-accelerated physical-layer is placed in the remote radio head, and higher software-based layers are placed in a server (either directly connected or remotely accessible). This setup allowed us to experimentally evaluate the power consumption of key hardware modules when adapting the bandwidth and the modulation and coding scheme. The real-time operation of the testbed allows further experimentation with different 5G use cases and the evaluation of other key performance indicators.TRUEpu
The 5G-Crosshaul Packet Forwarding Element pipeline: measurements and analysis
Get PDFThis paper is focused on the 5G-Crosshaul Packet Forwarding Element (XPFE), which is the packet forwarding element of the 5G-Crosshaul network architecture. The XPFE integrates multiple technologies which allow to transport traffic from multiple tenants and of different nature over the same infrastructure. Hence, the paper is focused on the performance of this essential element of our network, providing some end-to-end delay measurements and analyzing the behavior of this delay. Likewise, we have fitted the appropriate probability distribution for these measurements, which allows us to infer some confidence intervals for the prediction of the maximum number of hops supported by delay-sensitive fronthaul traffic before being processed in a 5G-Crosshaul Processing Unit.TRUEpu
Reliable Capacity Provisioning for Distributed Cloud/Edge/Fog Computing Applications
Get PDFThe REliable CApacity Provisioning and enhanced
remediation for distributed cloud applications (RECAP) project aims to advance cloud and edge computing technology, to develop mechanisms for reliable capacity provisioning, and to make application placement, infrastructure management, and capacity provisioning autonomous, predictable and optimized. This paper presents the RECAP vision for an integrated edge-cloud architecture, discusses the scientific foundation of the project, and outlines plans for toolsets for continuous data collection, application performance modeling, application and component auto-scaling and remediation, and deployment optimization. The paper also presents four use cases from complementing fields that will be used to showcase the advancements of RECAP.TRUEpu
Cost Analysis of Smart Lighting Solutions for Smart Cities
Get PDFStreet lighting is an essential community service, but
current implementations are not energy efficient and and require municipalities to spend up to 40% of their allocated budget. In this paper, we propose heuristics and devise a comparison methodology for new smart lighting solutions in next generation smart cities. The proposed smart lighting techniques make use of Internet of Things (IoT) augmented lampposts, which save energy by turning off or dimming the light in the absence of citizens nearby. Assessing costs and benefits in adopting the new smart lighting solutions is a pillar step for municipalities to foster real implementation. For evaluation purposes, we have developed a custom simulator which allows the deployment of lampposts in realistic urban environments. The citizens travel on foot along the streets and trigger activation of the lampposts according to the proposed heuristics. For the city of Luxembourg, the results highlight that replacing all existing lamps with LEDs and dimming light intensity in the absence of users in the vicinity of the lampposts is convenient and provides an economical return already after the first year of deployment.TRUEpu