IMDEA Networks Institute Digital Repository
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Theoretical and Empirical Analysis of Fundamental Bottlenecks in Networking and Distributed Computing
Get PDFThe goal of the thesis is to resolve distributed computing bottlenecks arising from continuously increasing amount of incoming data and from delay requirements that become more and more stringent. In particular, we present a novel formalization of resource allocation problem for serverless computing paradigm that has emerged recently and promises to provide significant cost savings. We designed new resource allocation algorithms based on that formalization and performed their rigorous theoretical analysis.
As the next step towards its goal, this thesis suggests an alternative to the existing approach of computing system design that usually treats the network solely as an interconnect. The new alternative allows to lessen the computational load on traditional cloud computing resources and to reduce the processing delays. The two methods were developed for that purpose: intermediate data aggregation and in-network data processing. The latter method includes several major improvements in packet classification and buffer management algorithms.Computer ScienceNational Research University Higher School of Economicspu
openLEON: An End-to-End Emulation Platform from the Edge Data Center to the Mobile User
Get PDFTo support next generation services, 5G mobile network architectures are increasingly adopting emerging technlogies like software-defined networking (SDN) and network function virtualization (NFV). Core and radio access functionalities are virtualized and executed in edge data centers, in accordance with the Multi-Access Edge Computing (MEC) principle. While testbeds are an essential research tool for experimental evaluation in such environments, the landscape of data center and mobile network testbeds is fragmented. In this work, we aim at filling this gap by presenting openLEON, an open
source muLti-access Edge cOmputiNg end-to-end emulator that operates from the edge data center to the mobile users. openLEON bridges the functionalities of existing emulators for data centers and mobile networks, i.e., Containernet and srsLTE, and makes it possible to evaluate and validate research ideas on all the components of an end-to-end mobile edge architecture.pu
Design and Deployment of an Open Management and Orchestration Platform for Multi-site NFV Experimentation
Get PDFManagement and orchestration of virtual resources and functions, commonly referred to as MANO, are key functionalities of Network Function Virtualization (NFV) environments. This paper describes the design and deployment of the NFV MANO platform of 5TONIC, the open research and innovation laboratory on 5G technologies founded by Telefonica and IMDEA Networks. This NFV MANO platform provides 5TONIC trials and experiments with access to a functional production-like NFV environment, enabling experimentation with novel NFV products and services. As a relevant feature, the platform is capable of incorporating external sites to complement the portfolio of software and hardware resources that can be made available for experimentation activities. The 5TONIC MANO platform has been designed and built using open-source technologies. The research carried out during its design and deployment has resulted in a contribution already made to its upstream projects, regarding the automated configuration of virtualized network functions. Finally, we explored the scalability properties of the 5TONIC MANO platform, and we experimentally validated its functional capacity to orchestrate multi-site experiments.pu
5G-DIVE: eDge Intelligence for Vertical Experimentation
Get PDF5G-DIVE targets end-to-end 5G trials aimed at proving the technical merits and business value proposition of 5G technologies in two vertical pilots, namely (i) Industry 4.0 and(ii) Autonomous Drone Scout. Its design is built around two main pillars, namely (1) end-to-end 5G connectivity including 5G New Radio, Crosshaul transport and 5G Core, and (2) distributed edge and fog computing integrating intelligence located closely to the user to achieve optimized performance, improving significantly the business value proposition of 5G in each targeted vertical application.TRUEpu
An Ad-Driven Measurement Technique for Monitoring the Browser Marketplace
Get PDFIn this paper we present a novel active measurement methodology for monitoring the browser market landscape. It leverages the display ads delivered through online advertising campaigns to collect the browser brand and version of the device receiving the ad. While providing a similar accuracy to traditional techniques based on passive measurements, our methodology offers some advantages: (i) a lower entry barrier for researchers and practitioners interested in measuring the browser marketplace; (ii) it allows targeted measurements, which can be useful to fix biases in the data sample or to analyze specific aspects of the browser market. We analyze the performance, accuracy, and capabilities of our methodology through real experiments that overall produced more than 6M measurements.pu
pDCell: an End-to-End Transport Protocol for Mobile Edge Computing Architectures
Get PDFTo deal with increasingly demanding services and the rapid growth in number of devices and traffic, 5G and beyond mobile networks need to provide extreme capacity and peak data rates at very low latencies. Consequently, applications and services need to move closer to the users into so-called edge data centers. At the same time, there is a trend to virtualize core and radio access network functionalities and bring them to edge data centers as well. However, as is known from conventional data centers, legacy transport protocols such as TCP are vastly suboptimal in such a setting.
In this work, we present pDCell, a transport design for mobile edge computing architectures that extends data center transport approaches to the mobile network domain. Specifically, pDCell ensures that data traffic from application servers arrives at virtual radio functions (i.e., C-RAN Central Units) timely to (i) minimize queuing delays and (ii) to maximize cellular network utilization. We show that pDCell significantly improves flow completion times compared to conventional transport protocols like TCP and data center transport solutions, and is thus an essential component for future mobile networks.TRUEpu
Crowdsensed Data Learning-Driven Prediction of Local Businesses Attractiveness in Smart Cities
Get PDFUrban planning typically relies on experience-based solutions and traditional methodologies to face urbanization issues and investigate the complex dynamics of cities. Recently, novel data-driven approaches in urban computing have emerged for researchers and companies. They aim to address historical urbanization issues by exploiting sensing data gathered by mobile devices under the so-called mobile crowdsensing (MCS)
paradigm. This work shows how to exploit sensing data to improve traditionally experience-based approaches for urban decisions. In particular, we apply widely known Machine Learning (ML) techniques to achieve highly accurate results in predicting categories of local businesses (LBs) (e.g., bars, restaurants), and their attractiveness in terms of classes of temporal demands (e.g., nightlife, business hours). The performance evaluation is conducted in Luxembourg city and the city of Munich with publicly available crowdsensed datasets. The results highlight that our approach does not only achieve high accuracy, but it also
unveils important hidden features of the interaction of citizens and LBs.TRUEpu
Single- and Multiple-Access Point Indoor Localization for Millimeter Wave Networks
Get PDFMillimeter wave (mmWave) location systems not only provide accurate positioning for location-based services, but can also help optimize network operations, for example through location-driven beam steering and access point association. In this paper, we design and evaluate localization schemes that exploit the characteristics of mmWave communication systems. We propose two range-free algorithms belonging to the broad classes of triangulation and angle difference-of-arrival. The schemes work both with multiple anchors and with as few as a single anchor, under the only assumption that the floor plan and the positions of the mmWave access points are known. Moreover, they are designed to be lightweight, so that even computationally-constrained devices can run them. We evaluate our proposed algorithms against two benchmark approaches based on fingerprinting and angles of arrival, respectively. Our results, obtained both by means of simulations and through measurements involving commercial 60-GHz mmWave devices, show that sub-meter accuracy is achieved in most of the cases, even in the presence of only a single access point. The availability of multiple access points substantially improves the localization accuracy, especially for large indoor spaces.pu
Beyond content analysis: Detecting targeted ads via distributed counting
Get PDFBeing able to check whether an online advertisement has been targeted is essential for resolving privacy controversies and implementing in practice data protection regulations like GDPR, CCPA, and COPPA. In this paper we describe the design, implementation, and deployment of an advertisement auditing system called eyeWnder that uses crowdsourcing to reveal in real time whether a display advertisement has been targeted or not. Crowdsourcing simplifies the detection of targeted advertising, but requires reporting to a central repository the impressions seen by different users, thereby jeopardising their privacy. We break this deadlock with a privacy preserving data sharing protocol that allows eyeWnder to compute global statistics required to detect targeting, while keeping the advertisements seen by individual users and their browsing history private. We conduct a simulation study to explore the effect of different parameters and a live validation to demonstrate the accuracy of our approach. Unlike previous solutions, eyeWnder can even detect indirect targeting, ie, marketing campaigns that promote a product or service whose description bears no semantic overlap with its targeted audience.TRUEpu
Enhancing the ns-3 IEEE 802.11ad Model Fidelity: Beam Codebooks, Multi-antenna Beamforming Training, and Quasi-deterministic mmWave Channel
Get PDFNext generation wireless local area networks are envisioned to serve a high number of devices with heterogeneous capabilities and service requirements. Millimeter-wave technology is expected to be able to satisfy these demands and complement the highly congested wireless networks operating in the sub-6 GHz band. However, real world experimentation with millimeter-wave communications is not always feasible due to the significant amount of resources required and its associated costs. For these reasons, researchers resort to high fidelity system-level simulators which provide a high degree of flexibility to test complex network deployments with a reasonable level of abstraction at the physical layer. The ns-3 IEEE 802.11ad model allows researchers to study large-scale wireless networks operating in the 60 GHz band, taking into account all of the essential features supported by the standard. However, the beamforming capabilities in the current implementation still lack both the flexibility and the agility that commercial of-theshelf devices offer. Additionally, the model relies on a simplified channel model that does not accurately reflect the characteristics of a millimeter-wave channel. In this paper, we augment our ns-3 IEEE 802.11ad model with novel features that enhance its fidelity and provide the user with high granularity to control both physical and MAC layer aspects of 802.11ad devices. These features include beam codebooks, multi-antenna beamforming training, beam refinement and beam tracking capabilities, and a quasi-deterministic channel model. Our work paves the way for a future implementation of the next generation wireless gigabit standard, IEEE 802.11ay.TRUEpu