Miracle-dz/UniFAR-FTUs huggingface dataset:
An Attack on Untraceable Linear Network Coding

The privacy of users in wireless mesh networks is threatened by attackers that trace the flow of packets through the network or trace users' movements within the network. Untraceable Linear Network Coding, a scheme to provide flow and movement untraceability, suggests to recode messages based on a specified matrix. However, the advantage an attacker gains by knowing this encoding strategy and the routing mechanism is not discussed. Hence, although claimed otherwise packet flows and movement of users might be traceable when the Untraceable Linear Network Coding Scheme is used. In this paper, we investigate this open point and introduce an attack based on the knowledge of the coding scheme and routing. We show the success of our polynomial time attack in a simulation: For most realistic parameters the attacker can trace flows in the network to the receiver's mesh node with a success rate of 80% or more. Additionally, we discuss countermeasures to reinforce the protection of the network coding scheme.
On the Downlink Performance of UAV Communications in Dense Cellular Networks

Reliable command and control channels to unmanned aerial vehicles (UAVs) are needed to allow beyond visual line of sight (LoS) operations. Cellular networks, with their almost ubiquitous coverage, are an obvious candidate to provide such conditions. However, up to which extent the current networks designed for ground users can support UAV communications is an open question. In this paper, we provide a comprehensive theoretical analysis, using stochastic geometry, of the performance that operators could expect from traditional cellular networks with omnidirectional antennas when supporting UAV downlink command and control channels. Our study employs the latest UAV height-dependent path loss model defined by the 3GPP, with LoS and non-LoS transmissions and a probabilistic model to switch between them. We derive analytical expressions for the coverage probability and area spectral efficiency, while accounting for base stations with idle mode capabilities, a practical finite UAV density, and different UAV heights. Results show that networks based on base stations with omnidirectional coverage can support low-height UAVs but will struggle with high-height ones. Network densification helps to provide a better performance.
Clustering writing components from medieval manuscripts

This article explores a minimally supervised method for extracting components, mostly letters, from historical manuscripts, and clustering them into classes capturing linguistic equivalence. The clustering uses the DBSCAN algorithm and an additional classification step. This pipeline gives us cheap, but partial, manuscript transcription in combination with human annotation. Experiments with different parameter settings suggest that a system like this should be tuned separately for different categories, rather than rely on one-pass application of algorithms partitioning the same components into non-overlapping clusters. The method could also be used to extract features for manuscript classification, e.g. dating and scribe attribution, as well as to extract data for further palaeographic analysis.
11-Gbps Broadband Modem-Agnostic Line-of-Sight MIMO Over the Range of 13 km

A modem-agnostic Line-of-Sight (LoS) MIMO system, which performs MIMO processing in analog domain, can be retrofitted to any kind of single-input-single-output (SISO) digital modems to further increase spectral efficiency and data- rate. We show that two of the enabling technologies for broadband analog MIMO processing over several GHz bandwidth are: (1) precise signal delay compensation using continuously tunable delay line and (2) operating analog MIMO equalization at high RF intermediate frequency. Based on these two principles, we design and implement a 2×2 LoS MIMO system that supports MIMO processing of up to 1.6 Gbaud 64-QAM signal. The channel interference can be reduced lower than −25 dB over the entire signal spectrum after MIMO equalization. We demonstrate an indoor 2×2 LoS MIMO link of 16.7 Gbps with each channel carrying 1.6 Gbaud 64 QAM and an outdoor MIMO link of 11.1 Gbps over the range of 13 km with each channel carrying 1.6 Gbaud 16-QAM signal at millimeter-wave (MMW) frequency of 85 GHz.
Graphical Modeling Of High-Dimensional Time Series

We consider the problem of inferring the conditional independence graph of a high-dimensional stationary multivariate real-valued Gaussian time series. A p-variate Gaussian time series graphical model associated with an undirected graph with p vertices is defined as the family of time series that obey the conditional independence restrictions implied by the edge set of the graph. We present a novel formulation of joint graphical lasso in frequency domain, suitable for dependent time series, generalizing current time-domain approaches to i.i. d. time series. The approach is nonparametric. First a sufficient statistic set in frequency domain is developed, and then a penalized log-likelihood of the sufficient statistic set is optimized. An optimization algorithm based on alternating minimization is presented and illustrated via numerical examples.
Energy-Efficient Core Allocation and Deployment for Container-Based Virtualization

Infrastructure-as-a-Service (IaaS) is a popular form of cloud computing that provides virtualized computing resources. The current trend of IaaS is moving from virtual machine-based into container-based. In this paper, we study the energy-efficient resource allocation problem for container-based virtualization in a data center. Our goal is to minimize the energy consumption by determining 1) the number of cores allocated to a container, 2) the operating frequency of the container, and 3) the deployment of the container to server. Every container has to meet its service level agreement (SLA). We propose dynamic programming algorithms that can be used under different scenarios, depending on the affordable time complexity. The performance of the proposed algorithms is evaluated with energy consumption data collected from experiments.
Design and Implementation of a 5G NR System Based on LDPC in Open Source SDR

Low-density parity-check (LDPC) code has been chosen as the coding scheme for data channels in enhance Mobile Broad Band (eMBB) of the fifth generation (5G) New Radio (NR) technical specifications. However, there has not been a low-cost and flexible platform to evaluate the performance of LDPC over the air interface now. In this paper, the Physical Downlink Shared Channel (PDSCH) encoder and decoder are first realized on the OpenAirInterface (OAI) DLSIM platform to validate the LDPC code. Then, in order to meet the real-time requirements of Software Defined Radio (SDR) system, the extended instruction set and multithreading are used to optimize LDPC encoder and decoder. Based on our proposed system, plenty of experiments are carried out to evaluate the LDPC performances not only by simulations but also through the field trials over the air. The results demonstrate that 5G NR system based on LDPC has excellent performance in terms of the throughput.
Resource Provision for Energy-Efficient Mobile Edge Computing Systems

Mobile Edge Computing (a.k.a Fog computing) is recently proposed to provide computing service for delay-sensitive mobile applications. Despite various benefits, deploying edge servers in cellular networks would increase their energy consumption. In this paper, we investigate the provision of resources, including both communication and computation resources, of Mobile Edge Computing (MEC) systems to improve their energy efficiency (EE). In a MEC system, both the communication subsystem, which allows mobile users to access Internet and offload their computing tasks, and the computation subsystem, which accomplishes the offloaded computing tasks, affect the service latency and consume energy. Modelling the whole system as tandem queues, we study the trade-offs between these two subsystems on energy consumption and service latency. Based on the analysis results, we propose an algorithm to determine the optimal provision of both communication and computation resources to minimize the overall energy consumption without sacrificing the performance on service latency. Numerical results are provided to validate our analytical findings.
Preamble-Less Diversity Combining: Improved Energy-Efficiency in Sensor Networks

Recent advances in the field of sensor networks helped miniaturizing nodes and, thus, enabling novel application domains for, e.g., remote monitoring or more generally the Internet of Things (IoT). One of the most critical issues in this context is the limited energy capacity of a sensor node, and its implication on communication reliability. Recently, we have investigated the use of diversity combining in a distributed sensor network to improve both the communication reliability and the energy footprint of mobile sensors transmitting to stationary receiver nodes. In this work, we go one step further and integrate the idea of preamble-less communication proposed by mSync with diversity combining to gain the added advantage of both. The elimination of preambles allows to further minimize the transmission energy. We implemented the proposed integrated model in GNU Radio and evaluated its performance both in simulations as well as lab experiments. Our results demonstrate that applying diversity combining together with mSync not only reduces the energy required for transmission but also improves the communication performance in terms of Packet Delivery Ratio (PDR), especially at higher Signal-to-Noise Ratio (SNR).
Contribution à la réduction de l'impact environnemental du perméat de lactosérum via sa valorisation intégrale par un procédé d'électro-activation en solution : preuve du concept et analyse de la qualité du produit

v TABLE DES MATIÈRES . vii LISTE DES TABLEAUX . xii LISTE DES FIGURES . xiii LISTE DES ABBRÉVIATIONS . xvi Dédicaces . xvii REMERCIEMENTS . xviii AVANT-PROPOS . xix INTRODUCTION . 1 CHAPITRE 1 : REVUE DE LITTÉRATURE . 4 1.1. Définition du lactosérum . 4 1.2. Composition chimique du lactosérum . 4 1.3. Perméat de lactosérum (PLS) . 5 1.4. Lactose . 5 1.4. 1. Dérivés du lactose . 6 1.4. 1.1. Galacto-oligosaccharides . 7 1.4. 1.1.1. Procédé chimique . 7 1.4. 1.1.2. Procédé enzymatique . 8 1.4. 1.2. Acide lactobionique . 9 1.4. 1.2. 1. Procédé chimique (oxydation catalytique hétérogène) . 9 1.4. 1.2. 2. Procédé enzymatique . 11 1.4. 1.3. Lactitol. 12 1.4. 1.3. 1. Procédé chimique . 13 1.4. 1.4. Lactosucrose. 13 1.4. 1.4. 1. Procédé enzymatique (industriel) . 14 1.4. 1.5. Tagatose . 15 1.4. 1.4. 1. Procédé chimique . 15 1.4. 1.4. 2. Procédé enzymatique . 16 1.4. 1.6. Epilactose . 17 1.4. 1.6. 1. Synthèse chimique . 18 1.4. 1.6. 2. Procédé enzymatique . 18 1.4. 1.7. Lactulose . 20
Identification and quantification of colours in children's drawings

Researchers in social sciences and humanities disciplines are confronted with the need to analyse increasing amounts of visual data, which calls for the development of new computational methods. This paper focuses on the problem of identifying the colours used in children's drawings, notably in the perspective of assessing their diversity. It describes a simple, effective, and flexible algorithm for performing this task. This methodology is applied to a subset of more than 1000 drawings taken from the ``Drawings of gods'' database. The first results show that this approach makes it possible to address meaningful research questions concerning the patterns of colour usage in these data.
Distributed optimization for Generalized Phase Retrieval Over Networks

In this paper, we will solve the generalized phase retrieval (PR) problem over a network, where each agent only has a subset of the measurements. The problem is formulated as minimizing the squared loss between the measurements and linear sensing intensity. To solve the problem in a distributed setting, an algorithm named distributed Wirtinger flow (DWF) is proposed. Theoretical analyses show that the proposed DWF algorithm converges to the (approximate) KKT points of the original problem globally in a sublinear rate. The performance of the DWF algorithm is numerically compared with the state-of-the-art method. Simulation results show that DWF is able to recover a high-quality solution for the original PR problem.
Novel Wake-Up Signaling for Enhanced Energy-Efficiency of 5G and beyond Mobile Devices

Low-power and low-latency communication features are vital to extend 5G mobile devices functionalities beyond those of the current networks, and to introduce innovative services and applications. On the other hand, limitations of state-of-the-art cellular modules prevent designing and facilitating such features based on current power saving mechanisms alone. In this paper, a new wake-up signaling for 5G control plane is introduced, aiming to reduce energy consumption of cellular module in downlink. Performance of the proposed scheme in terms of false alarm and misdetection rates are investigated and evaluated. The obtained numerical results show that such a signaling can reduce power consumption of discontinuous reception (DRX) by up to 30%, at the cost of negligible increase in signaling overhead.
Reliability-Driven Vehicular Crowd-Sensing: A Case Study for Localization in Public Transportation

This paper proposes a new framework for GPS-less identification of location of public transportation vehicles by using machine intelligence algorithms by exploiting the vehicular crowd-sensing concept. Since data trustworthiness is vital when data is crowd- solicited via various non-dedicated sensors, assessment and quantification of the trustworthiness of participating sensors plays a key role in the accuracy of the acquired information. To this end, we propose two trustworthiness-aware recruitment schemes for the non-dedicated sensors in a vehicular crowd-sensing environment: Reliability-driven naive recruitment (RDNR) and Reliability-driven exclusive recruitment (RDER). The former determines to use the data of a mobile device with a probability equal to the reliability of the device whereas the latter excludes the participating devices whose reliability scores are below a certain threshold. The data acquired from the recruited participant pool then undergoes an unsupervised machine learning module that is hosted in the cloud. We evaluate the performance of RDNR and RDER in comparison to each other and a non-restrictive recruitment mechanism which does not consider reliability of participants at all. Through simulations, we show that over 85% and 98% accuracy can be achieved in the worst and best cases, respectively while consuming less energy than GPS-based localization approaches.
On the Secrecy Performance of Mixed RF/UOW Communication System

In this paper, the secrecy performance of a dual-hop mixed radio-frequency/underwater optical wireless communication (RF/UOWC) system is investigated. The considered system consists of one single antenna source node ($S$) communicating with one destination node ($D$), considered as the legitimate receiver, through the help of one amplify-and-forward (AF) relay node $R$ equipped with multiple antennas for reception. Specifically, the relay receives the incoming signal from $S$ via an RF link, applies maximal-ratio combining (MRC) technique, amplifies the output combined signal with a fixed gain, and then forwards it to $D$ via a UOWC link. The transmission protocol is performed under the eavesdroppers' attempt to overhear the RF link (i.e., $S-R$). We derive an exact closed-form expression for the secrecy intercept probability (IP) in terms of the Fox's $H$-function, or in terms of the Meijer's G-function as a particular case. The derived secrecy performance metric is evaluated in terms of various channel and system parameters, and corroborated by Monte-Carlo simulation method. Our derived analytical formulas present an efficient tool to highlight the impact of some system and channel parameters on the secrecy performance.
TIMAO: Time-Sensitive Mobile Advertisement Offloading with Performance Guarantee

Mobile advertising has played an important role with the prevalence of smart mobile devices. Most of the previous studies focus on location-based or content-based mobile advertisement propagation and distribution, which are suffered by the low propagation efficiency, because advertisements could not be available to mobile users within limited time span. Conventional offloading schemes could perfectly distribute advertisements according to user's interest, but have not fully respected the time sensitivity in mobile advertisement distribution. In response to this stalemate, we introduce the advertisement platform's expected income maximization problem (EIMP), and prove its NP-hardness. To our knowledge, ours is even harder than conventional 0–1 mutlidimensional and multiple knapsack problem. But inspiringly we find that it could be transformed into a maximizing monotone submodular set function, being subjected to partition matroid constraints. Then a simple but effective greedy algorithm (TIMAO, time-sensitive mobile advertisement offloading)is proposed to solve the EIMP with approximation ratio of 1/3. Finally, the evaluation results show that TIMAO could double the platform's expected income comparing with the random selection method and reach 99.2% of the near optimal values achieved by CPLEX tool-box. At the same time, it increases the time duty cycle by about average 10% compared with the random selection.
eMPTCP: Towards High Performance Multipath Data Transmission by Leveraging SDN

Motivated by the poor performance of MPTCP when used for bulk transfers in multipathed networks, in this paper we propose an efficient MPTCP protocol variant named eMPTCP aiming to achieve high throughput, low latency and good bottleneck fairness. The novel MPTCP variant eMPTCP can prevent in-network buffer overflow and packet loss using a distributed and reactive approach for bandwidth allocation and adjusting the congestion window of subflows on multiple paths in a coordinated fashion. It employs ECN feedback and latency (in terms of RTT) to modulate the congestion window via a gamma correction function. This novel congestion- and latency-aware window adjustment mechanism behaves very helpful in handling the traffic bursts, easing the buffer pressure on switches, and greatly mitigates the incast issue. Besides, in this solution SDN is leveraged to compute a set of optimal available routes for subflows and actively adjust the number of subflows of each MPTCP flow according to the instantaneous traffic condition. Moreover, this novel MPTCP protocol variant eMPTCP works well with existing switch hardware and is able to coexist with legacy TCP. It ensures that a multipath flow will not take up more capacity on any shared paths than if it was a single path TCP flow using only one of those paths, which guarantees it will not unduly harm other flows. Simulation results show that eMPTCP achieves smaller MPTCP convergence time, higher aggregate throughput and lower flow completion time than existing legacy competitors, and largely improves the application performance and user experience, making the network more robust and faster.
Cooperative NOMA for Wireless Layered Multicast

This paper proposes a novel design of cooperative non-orthogonal multiple access (NOMA) for layered multicast, where the information is encoded into the messages of high-priority (HP) and low-priority (LP). Two types of multicast users coexist in the system: 1) regular users (RUs), which locate far away from the base-station (BS) and demand only the HP message; 2) advanced users (AUs), which locate close to the BS and demand both HP and LP messages. To improve the reliability of layered multicast, an opportunistic cooperative NOMA multicast strategy is proposed, in which one successful AU is selected to forward both HP and LP messages. For the proposed strategy, we derive closed-form exact outage probabilities of AUs and RUs. By further carrying out the asymptotic analysis, the achieved diversity orders are shown to be not less than the number of AUs, i.e., full diversity is achieved. Finally, numerical results verify the theoretical analysis and demonstrate the superiority of the proposed strategy.
Cyber Risk Management with Risk Aware Cyber-Insurance in Blockchain Networks

Benefit from the capabilities of providing decentralized tamper-proof ledgers and platforms for data-driven autonomous organization, open-access blockchains based on proof-of-work protocols have gained tremendous popularity. Yet, the proof-of-work based consensus protocols under threats, e.g., double-spending. In this paper, by adopting the cyber-insurance as an economic tool to neutralize cyber risks, we propose a novel approach of cyber risk management for blockchain-based service. The blockchain service market under our consideration is composed of four entities, i.e., the infrastructure provider, blockchain provider, cyber-insurer, and users. The blockchain provider purchases the computing resources, e.g., a cloud, from the infrastructure provider to maintain the blockchain consensus and then offers blockchain services to the users. The blockchain provider optimize its profit by strategizing its investment in the infrastructure in order to improve the security of the blockchain and the service price charged to the users. In the meantime, to prevent the potential damage incurred by the attacks and then fully secure the cyber-space, the blockchain provider purchases a cyber-insurance from the cyber-insurer. In return, the cyber- insurer adjusts the insurance premium according to the perceived risk level of the blockchain service and will pay the claim to the blockchain provider once attacks happen. Based on the rationality of the market entities, we model the interaction among the blockchain provider, users, and cyber-insurer as a two- stage Stackelberg game. Specifically, the blockchain provider and cyber-insurer lead to set their pricing&#x002F;investment strategies in the upper level subgame, and then the users follow to determine their demand of the blockchain service in the lower level subgame. Specifically, we consider the scenario of double-spending attacks and provide a series of analytical results about the Stackelberg equilibrium in the market game.
System-Level Analysis for Full-Duplex MmWave Cellular Networks

In this paper, we investigate the performance of full-duplex (FD) radio in large-scale heterogeneous millimeter-wave (mmWave) cellular networks. The FD radio can potentially double the spectral efficiency but its performance is compromised by the existence of loop- and multi-user interference compared to half-duplex radio. Using stochastic geometry tools, we derive closed-form expressions for the coverage probability and the sum-rate performance of the considered network. We evaluate the impact of the FD radio on the network performance and quantify the associated gains under different network parameter settings. Our results demonstrate that the combination of FD radio with heterogeneous mmWave cellular networks provides significant gains, since it increases the spectral efficiency but also alleviates the effects of the multi-user interference.