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The pulp and paper industry in Europe produces over 11 million tons of waste per year. Given high landfill operational costs, thermal co-processing with biomass may be a viable management and valorisation option for such wastes. In this work, the analysis of biomass (wood sawdust), mixture of primary and secondary pulp mill sludge and their respective blends (50 wt.%, 60 wt.%, 70 wt.% of sludge) was assessed by thermogravimetric analysis. One of the possibilities to ensure valorisation of paper pulp mill sludge is its combustion in the form of pellets containing a different amount of sludge. Production of pellets samples was realised on laboratory experimental device. The measurements showed that increasing the content of paper sludge in the produced pellets reduced the calorific value and increased the ash content. This research deals also with the effect of paper sludge on the ash melting temperatures. The results indicated that a higher content of paper sludge in the pellets increased the ash melting temperatures. This advantage of paper sludge can be utilized in co-combustion of biomass with a low ash melting temperature.

SUMMARY Digital books have become popular as electronic media has become more common. An evaluation that includes not only a subjective assessment of readability or usability, but also an objective assessment of psychometric health impact is needed. The goal of this study is an objective assessment of the physiological and psychological effects of reading books using electronic or paper media. This paper focuses on hemodynamic parameters. The measurement items include VAS and POMS as a psychological index and hemodynamic parameters as a physiological index. As a result, low levels of vigor and limited readability were recognized as significant (p < 0.05) when reading a book using electronic media as compared to paper media. The cardiovascular system was actively engaged in coping because of sympathetic hyperactivity in the hemodynamic reaction. By contrast, using electronic media was not seen to involve stress coping. We also found that the parasympathetic nervous system activity was enhanced by the illegibility of sentences and fatigue due to using electronic media. Based on all of these results, we identified a difference in how people react physiologically when reading a book using electronic and paper media.

International audience; We study unlimited infinite churn in peer-to-peer overlay networks. Under this churn, arbitrary many peers may concurrently request to join or leave the overlay network; moreover these requests may never stop coming. We prove that unlimited adversarial churn, where processes may just exit the overlay network, is unsolvable. We focus on cooperative churn where exiting processes participate in the churn handling algorithm. We define the problem of unlimited infinite churn in this setting. We distinguish the fair version of the problem, where each request is eventually satisfied, from the unfair version that just guarantees progress. We focus on local solutions to the problem, and prove that a local solution to the Fair Infinite Unlimited Churn is impossible. We then present our algorithm UIUC that solves the Unfair Infinite Unlimited Churn Problem for a linearized peer-to-peer overlay network. We extend this solution to skip lists and skip graphs.

In this paper, an inkjet-printed paper-based capacitive touchpad is proposed. This touchpad detects finger contact by sensing the change in effective capacitance caused by the skin electrical impedance. A low-cost flexible disposable touchpad with nine capacitive buttons is fabricated, using paper as a substrate. The use of home inkjet printing technology with silver nanoparticle ink makes the fabrication process simple, fast, cheap, and environmentally friendly. The performance of the proposed touchpad is measured with a microcontroller, and tests are conducted for both the cases of finger and touch pen operation. The measured capacitance of the non-touched state is 228–236 pF, whereas the measured capacitance of the touched state is 340–564 pF. The differences in the capacitance of each state are sufficiently large to indicate that a finger has made contact with the touchpad. The sensitivity of the proposed sensor is evaluated, and the parameters of the proposed sensor are compared with those of other paper-based touch pads.

Paper checks may have complex background features including fine lines and patterns, which make forgery more difficult. Also, halftoning techniques are used to produce continuous tones and to prevent copies with void pantograph features. When these kinds of checks are scanned, Moire patterns may occur. These patterns make it difficult for customers to examine the scanned check images on ATM (Automated Teller Machine) displays. They also can decrease the classification accuracy of check recognition systems. In this paper, we propose an algorithm to enhance the perceptual quality of scanned check images by reducing the Moire patterns. The proposed algorithm consists of foreground extraction, Moire detection and Moire removal. Subjective image quality assessment was performed to evaluate the degree of improvement. Experimental results show that the proposed algorithm improves perceptual quality while maintaining check recognition accuracy.

With rapid expansion of scientific papers, making a survey from a large collection of papers on a given research issue or domain becomes more and more important for researchers. This paper proposes a template-based framework for automatically generating survey paper. It allows users to compose a template tree as a syllabus for the required survey. Each tree node corresponds to a section to be composed in the survey therefore the whole tree defines the section structure of the survey. The template consists of two types of nodes, dimension node and topic node, which filter contents of papers. A recursive procedure along the survey generation template tree paths is conducted to process documents, rank sentences, and compose sections. We apply the approach to generating the survey of the reference papers of a survey paper and compare the result with the survey paper. Experiments show improvement over several baseline methods.

Trends in processor and system architecture, driven by power and complexity, point super-computing landscape toward very high and heterogeneous core count designs. As the number of cores inevitably increase traditional ways of performing large scale computations will also need to evolve from legacy models like OpenMP & MPI. However, such models are very much wedded to a control-flow vision of parallel programs, making it difficult to express asynchrony in programs. To address these challenges, codelet model was developed which is fine-grained, event-driven asynchronous program execution model. In-spite of its initial design goals, the Codelet model is rife with opportunities for further improvements to provide high-performance for both data and control regular applications. The major inspiration behind this work is to leverage the decades of research done to exploit instruction level parallelism (ILP) for the machine instructions inside codelet while build upon the dataflow software pipelining principals at codelet graph level to further enhance performance. In this paper, we propose hardware assisted extensions to the original codelet program execution model in order to implement efficient dataflow software pipelining and extend capabilities of the codelet model. This hardware-software co-design focuses on efficient implementation of data FIFO buffers leveraging proposed optimizations like - FIFO ring buffers and multiple-head FIFO buffers and single owner FIFO buffers to further exploit advantages of dataflow software pipelining. The wide range of scientific, machine learning and specially streaming applications should be able to take advantage of techniques proposed in this paper. Identifying these kernels and bench-marking them are the next anticipated steps for us.

This paper is a subset of a full-length paper that will be published in a special issue on metamaterials of the transactions at the end of this year. It presents the current authors’ perspective on the emerging field of spacetime metamaterials. Emphasis is placed on the definition, contextualization and fundamentals of the concept. In addition, a few new physical effects are described and a number of applications are enumerated.

This paper presents a compact paper-based rectenna with dual frequency operation. The rectenna is composed of a microstrip antenna designed on paper, in which an air gap is introduced between the patch and the ground plane to overcome the low-thickness and high-loss characteristics of the conventional paper substrate. This allows the microstrip antenna to reach a high radiation efficiency and a large bandwidth. Additionally, a miniaturization technique is utilized to reduce the antenna dimensions imposed by the low permittivity of the air. The absence of matching network between the antenna and the rectifier ensures a very compact size as well as limited insertion losses at the rectifier level and results in a high RF -DC conversion efficiency in the two frequency bands 1.8 and 2.4 GHz. The rectenna prototype shows experimental conversion efficiencies of 25 and 19 % at 1 $\mu \mathrm{W}/\mathrm{cm}^{2}$ and 55 and 44 % at 10 $\mu \mathrm{W}/\mathrm{cm}^{2}$ at 1.8 and 2.45 GHz, respectively, corresponding to output DC voltages of 208, 190 and 933 and 923 mV. Furthermore, output DC voltages of 93 and 550 $\mathrm{mV}$ are maintained over the band 1.75-2.6 GHz at 1 and 10 $\mu \mathrm{W}/\mathrm{cm}^{2}$ respectively. The rectenna prototype features a weight of 1.5 $\mathrm{g}$ and dimensions of 0.21 $\lambda_{o}\mathrm{x}0.21\lambda_{o}\mathrm{x}0.06\lambda_{o}$ .

International audience; A growing fraction of the papers published by CCR and at SIGCOMM-sponsored conferences include artifacts such as software or datasets. Besides CCR, these artifacts were rarely evaluated. During the last months of 2018, we organised two different Artifacts Evaluation Committees to which authors could submit the artifacts of their papers for evaluation. The first one evaluated the papers accepted by Conext’18 shortly after the TPC decision. It assigned ACM reproducibility badges to 12 different papers. The second one evaluated papers accepted by CCR and any SIGCOMM-sponsored conference. 28 papers received ACM reproducibility badges. We report on the results of a short survey among artifacts authors and reviewers and provide some suggestions for future artifacts evaluations.

A reconfigurable microstrip antenna with a dual-polarization beam-scanning feature is proposed in this paper. The proposed antenna is based on microstrip Yagi-Uda antenna comprised of a driven square patch and four parasitic square patches. Two different feed ports are utilized to separately excite two orthogonal modes for dual-polarization operation. The capability of beam-scanning is realized by loading a narrow loop slot and four varactors within each parasitic patch. By tuning the capacitance value of the varactors, the parasitic patch can act as a director or a reflector for the driven patch. Simulation results demonstrate that the beam can be scanned in 2D plane. The simulated cross-polarization discriminations are higher than 20 dB in all seven states presented in this paper. The proposed antenna is in fabrication and experimental results will be provided in the final submission.

An integral component of nearly all Internet of Things (IoT) systems or applications relies on the deployment and utilization of sensors which often yield massive volumes of disparate and distributed heterogeneous data. This sensor data is often transformed into usable information that can provide valuable insights for further facilitating the decision making process or enforcing strategic policies. Managing this raw data generated by IoT sensors while enforcing a certain level of quality is becoming a challenging task particularly for mission critical applications (e.g. homeland security, disaster preparedness, etc.). In this paper, we introduce the Quality of Data for IoT Devices (QoDID) framework that attempts to address key challenges associated with the collection and processing of raw sensor data used in IoT systems or applications. Throughout the paper, we discuss the overall architecture, use cases and implementation details of QoDID. We further use our QoDID framework to provide insights on improving the data acquisition processes involving devices and sensors in IoT systems.

There are many applications scenarios in different disciplines where the critical knowledge of decision making arrives in a sequential manner, so the optimization must be done in an online fashion. An important class of online optimization problems that have been extensively studied in the past is online linear programs. This paper tackles a general class of online linear programs that take into account the online arrival of the constraint entries related to the available budget and demand for different problem settings. This generalization is motivated by many recent applications on revenue management or resource allocation problems with the unknown and time-varying budget. As the main contribution of this paper, we propose a decoupling strategy that can be used to reduce the general problem into a series of subproblems with offline entries for the budget and demand. Using the proposed strategy, one can decouple the general problem, leverage the state-of-the-art algorithms for the online subproblems with fixed constraints, and achieve the same performance for the general problem. As for a case study, we apply the strategy to an extension of the one-way trading problem with the dynamic budget.

International audience; Photographic paper texture characterization constitutes a challenging image processing task and an important stake both for manufacturers and art museums. The present contribution shows how the Hyperbolic Wavelet Transform, thanks to its joint multiscale and anisotropie nature, permits to achieve an accurate photographic paper texture analysis and characterization. A cepstral-type distance, constructed on the coefficients of the Hyperbolic Wavelet Transform, is then used to measure similarity between pairs of paper textures. Spectral clustering followed by Ascendant Hierarchical Clustering applied to the similarity matrix enables an unsupervised classification of photographic paper sheets. This methodology is applied to a test dataset made available in the framework of the Historic Photographic Paper Classification Challenge. The relevance of the proposed texture characterization and classification procedure is assessed by comparisons against the database documentation provided by experts.

Currently, there is a massive demand for Internet of Things (IoT) devices that can interact and cooperate with each other over multiple wireless networks. Therefore, data transmission between IoT devices emerged as an essential process to ensure connectivity and achieve diverse and intelligent services. Typically, most of IoT-devices share the same frequency band at 2.4 GHz (ISM band), which is free and suitable for many devices. While, the continuous growing of IoT devices makes such frequency band suffers from increasing packet collisions and congestion due to accretion of uplink demand request packets. Therefore, the simple solution relies on using multiple antennas for each band. This solution proposes several challenges toward design implementation and the attached antenna's sizes. In this paper, we propose a quite new technique that can be used to tune frequency band over runtime through a single antenna with the same design. This is achieved through the recent technology of inkjet printing onto flexible substrate to expose such paper-based antenna to different mechanical deformation forces. This will enable manipulation of the antenna operating frequency and bandwidth to dynamically introduce/shift/remove the operating frequency bands over runtime. Simulation results show the ability of antenna to enable direct connectivity between IoT devices depending on twisting the antenna with different angles to establish new several frequency bands.

Respiration is a key vital sign indicative of an individual's health. Current approaches of respiration sensing require direct contact with the body. Moreover, they are expensive and need bulky holter monitors for continuous realtime monitoring. In this study, we propose a low-cost capacitive sensor fabricated using screen printing of carbon paste interdigitated electrodes on paper substrate for respiration monitoring. Cellulosic paper provides a microporous network to trap exhaled breath. Respiration causes the dielectric constant of the paper to change, mostly as a function of breath humidity, which in turn changes the capacitance of the sensor. The interdigitated electrodes configuration is shown to provide better response time compared to resistive configuration. A simple phase sensitive detector-based circuit was used to convert the capacitance change into a measurable output voltage. The MSP430 microcontroller was used for data acquisition and voltage measurement. A graphical user interface was designed for real time respiration monitoring. Experimental results validate the performance of this sensor.

The difference between conventional replicator dynamics and pairwise (PW) nonlinear Fermi dynamics can be discerned by studying the evolutionary dynamics of the interactions between the symmetric cyclic structure in the rock–paper–scissors game and inter- and intraspecific competitions. Often, conventional replicator models presume that the payoff difference among species is a linear function (a linear benefit). This study introduces a PW contrast under the properties of the well-known Fermi rule, where species play against one another in pairs. To model a PW nonlinear evolutionary environment (a nonlinear benefit) within this framework, both analytical and numerical approaches are applied. It is determined that the dynamics of the linear and nonlinear benefits can present the same stability conditions at equilibrium. Moreover, it is also demonstrated that, even in an identical equilibrium condition for both dynamics, the numerical result run by a deterministic approach presents a faster stability state for nonlinear benefit dynamics. This study also suggests that introducing mutation as demographic noise can effectively disrupt the phase regions and show the different relationships between linear and nonlinear dynamics. The symmetric bidirectional mutation among all the species reduced to the stable limit cycle by an arbitrary small mutation rate is also explored. Due to the environmental noise, however, linear and nonlinear exhibit the same steady state. Nevertheless, non-linearity illustrates more stable and faster stability situations. Our result suggests that environmental and demographic noise on the evolutionary dynamic framework can serve as a mechanism for supporting PW nonlinear dynamics in multi-species games.

Gossiping is a widely known and successful approach to reliable communications, tolerating packet losses and link crashes. It has been extensively used in several middleware kinds, such as event notification services and application domains, like infrastructures for air traffic management, power grid control, health information exchange, just to cite some of them. Despite achieving a high loss-tolerance and scalability degrees, gossiping is affected by degraded performances and heavy traffic loads on the network. For this reason, it may be not optimal in applications where reliability must be provided jointly with timeliness and/or in congestion-prone networks. The crucial aspect for improving a gossiping scheme is deciding which nodes should receive a gossiping message, and our driving idea is to adopt a distributed strategic learning logic to determine such nodes in an efficient manner. This is able to resolve gossiping's weakness points and to achieve better performance and reduced traffic loads. This paper describes how to introduced strategic learning in a gossip scheme so as to determine the best set of nodes that can be used to send gossip messages and to optimize their utility. Such a solution has been experimentally assessed through a set of simulations demonstrating the effectiveness of the proposal.

Recently, convergence has been presented as one of the technical innovations in many industrial sectors and diffusion has been discussed as providing the main influence on convergence. The present study used the VOSviewer to analyze convergence trends and the current state of joint research, complemented by quantitative analysis using information from scientific papers published in 2015 obtained through the Scopus database. The results of this study illustrate that convergence of research occurring in Korea is evident in a variety of sectors, e.g. chemistry, material science, mechanics and the electrical and electronics sectors. We discovered that a sector performing research characterized by convergence also was actively involved in joint research. We also discovered that institutions conducting many studies were doing so as partners within joint research with other institutions. There are two important applications: The present study identified important information that can be used to monitor convergence and diffusion appears to provide the most influence on convergence.

This study presents the design of a flexible compact rat-race coupler operating at 0.72 GHz on a 1 mm thick paper substrate. The ultra-wide stop-band effect caused due to the combination of the modified stepped impedance stub and the interdigitated resonator slot, offers suppression up to the 14th harmonic. The slow-wave effect caused due to the resonator slot leads to 59.6% size reduction compared with the conventional coupler at the design frequency. The signal transmission through the coupler for different substrate deformation steps has been investigated. Stable responses are reported for the same, making the prototype suitable for flexible electronics applications.

The present comment concerns some doubtful mathematical calculation that produced misleading results which are presented in the above paper.

Addressing delay caused by unstable and dynamic Military Cognitive Radio Ad Hoc Networks (MCRAHNs) is one of the major challenges in routing. In MCRAHNs nodes can be destroyed by an enemy causing the network to be intermittent, resulting in two forms of delay called Spectrum Mobility (SM) and Node Relay (NR) delay. The existing routing algorithms deployed in MCRAHNs incur a lot of SM and NR delay which causes inefficiencies in the transmission of packets. This paper introduces a routing scheme called Spectrum-Aware Transitive Multicast on Demand Distance Vector (SAT-MAODV) optimized to address the effects of SM and RP delay in MCRAHNs.

Development of a testbed for spectrum sharing is a multi-step process requiring systems engineering understanding. The ASCENT project is building a testbed to study licensed spectrum sharing between satellite systems and between satellite and terrestrial systems. The work has been carried out as part of the European Space Agency’s (ESA) Advanced Research in Telecommunications Systems (ARTES) programme. The 5G frequency bands currently under study are the 3.6 GHz band and the 26 GHz band. Validation is needed to check that all the requirements are fulfilled and consequently to understand in detail how the spectrum could be shared in the studied bands and what the benefits of different techniques such as licensed shared access (LSA) and power control could be. This paper describes the validation framework that provides guidance for the actual validation and enables creation of an efficient validation plan for different use cases and frequency bands. We also define the architecture for the LSA testbed.

This paper reviews the results of recent researches aimed to extend the standard-cell based digital design flow to analog building blocks, so that to enhance scalability, reconfigurability and portability across technology nodes and to reduce design effort, time-to-market and costs. In this framework, the application of the proposed fully digital design approach to a wake up oscillator and to a Digital-to-Analog Converter, which are two building blocks widely employed in IoT sensor nodes, is illustrated in detail.

We consider private information retrieval (PIR) for distributed storage systems with noncolluding nodes where data is stored using a non maximum distance separable (MDS) linear code. Recently, it was shown that when data is stored using certain non-MDS codes, the MDS-PIR capacity can be achieved, and is indeed the capacity of the system. In this paper, for storage codes not belonging to this class, we present a heuristic algorithm for their decomposition into punctured subcodes and a PIR protocol based on these punctured subcodes. The code decomposition is guided by the generalized Hamming weights of the storage code. We show that the proposed PIR protocol can achieve a larger PIR rate than that of all existing PIR protocols.

This paper presents the recent progress in studying the algorithmic computability of capacity expressions of secure communication systems. Several communication scenarios are discussed and reviewed including the classical wiretap channel, the wiretap channel with an active jammer, and the problem of secret key generation.

International audience; In this article, we present the design and results of an electronically re-writable chipless RFID tag on paper substrate. This tag consists of two resonators build around a modified shorted dipole, integrated with a non-volatile Metal-Insulator-Metal (MIM) switch, which tunes the electrical length of each resonator to resonate at two different frequencies, depending on state of the switch. One can electronically reconfigure the tag using low power DC pulses to change its RF signature. The integrated MIM switch has a layer architecture of Silver-Nafion-Aluminum, formed exclusively using an in-house process in ambient laboratory conditions, notably without the use of any 'clean room' facilities. Operating mechanism of the tag is validated with the help of developed electrical equivalent model. This study proves the concept of realizing 'electronically reconfigurable' chipless tags on flexible and low cost substrates, with a fabrication process compatible with mass production.

This paper presents a brief review on functionality-improved patch antennas with loading shorting pins that are recently proposed by the authors' group. Firstly, shorting pins can increase (reduce) the feeding current (voltage) of a patch antenna, so the edge-fed impedance can be reduced. Meanwhile, the cross-polarization can be kept in low level when the shorting pins are symmetrically loaded. Secondly, the shunt inductive effect of shorting pins significantly increases the resonant frequency of fundamental mode, resulting in enlarged radiating area, and so enhanced gain can be obtained. Thirdly, by properly adjusting the electrical size of patch through loading of shorting pins, the two orthogonal far-field components will have close beamwidth and beam shape, and then wide axial-ratio beamwidth (ARBW) can be realized.

The problem of communication over binary dirty paper (DP) using nested polar codes is considered. An improved scheme, focusing on low delay, short to moderate blocklength communication is proposed. Successive cancellation list (SCL) decoding with properly defined CRC is used for channel coding, and SCL encoding without CRC is used for source coding. The performance is compared to the best achievable rate of any coding scheme for binary DP using nested codes. A well known problem with nested polar codes for binary DP is the existence of frozen channel code bits that are not frozen in the source code. These bits need to be retransmitted in a second phase of the scheme, thus reducing transmission rate. We observe that the number of these bits is typically either zero or a small number, and provide an improved analysis, compared to that presented in the literature, on the size of this set and on its scaling with respect to the blocklength when the power constraint parameter is sufficiently large or the channel crossover probability sufficiently small., Accepted to ISIT 2019

This paper demonstrates that magnetic tuning can be employed either as coarse tuning or fine tuning or both for mm-Wave fundamental oscillators to achieve ultra-wide frequency tuning range and low phase noise. Firstly, a multimode VCO with a tuning range of 41.1% from 57.5 GHz to 90.1 GHz with phase noise of -111.8 dBc/Hz at 10-MHz offset and FoM T of -192.2 d Bc/Hz is discussed. Secondly, a dual-band varactor-less DB-VCO with 14.3% tuning range from 95.7 GHz to 110.5 GHz and -106.9 dBc/Hz phase noise at 10-MHz offset is presented together with a quad-band varactor-less QB-VCO achieving a tuning range of 32% from 58.8 GHz to 81.2 GHz and phase noise of -115.8 dBc/Hz at 10-MHz offset and FoM T of 192.4 dBc/Hz. Finally, a 95-GHz DCO provides a tuning range of 27% is demonstrated. It achieves a phase noise of -110 dBc/Hz at 10-MHz offset and FoM T of -186.1 dBc/Hz.

Many IoT systems are data intensive, where a large volume of data steadily get generated from a large number of sensors in the system. These data are continuous, thus, how to store and manage them is an important issue. Existing time series databases (TSDBs) offer some good strategies for storing continuous IoT data streams, but they lack a good semantic model for describing the IoT data streams to support effective data discovery. This shortcoming becomes critical when we consider the need for data sharing in many application domains; and it becomes significant when we consider the super huge scale of the IoT-Edge-Fog-Cloud infrastructure and the dynamic data flows in the infrastructure. In this paper, we develop the solutions for IoT data management in the IoT-Edge-Fog-Cloud infrastructure. We focus on the issues of data storage, specification and discovery. First, we build a semantic model for better specification of the IoT data streams (time series data), the DS-ontology. We have applied DS-ontology to TSDBs and developed the SE-TSDB tool suite, which runs on top of existing TSDBs to help establish semantic specifications for data streams and enable semantic-based data retrievals. We have also developed the IoT data discovery techniques based on SE-TSDB to facilitate semantic based data retrieval in the IoT-Edge-Fog-Cloud infrastructure. With our techniques, IoT data streams can be more effectively tracked and flexibly retrieved to help with integrated data analytics and improved knowledge discovery.

Data centers are the infrastructure that underpins modern distributed service-oriented systems. They are complex systems-of-systems, with many interacting elements, that consume vast amounts of power. Demand for such facilities is growing rapidly, leading to significant global environmental impact. The data center industry has conducted much research into efficiency improvements, but this has mostly been at the physical infrastructure level. Research into software-based solutions for improving efficiency is greatly needed. However, most current research does not take a holistic view of the data center that considers virtual and physical infrastructures as well as business process. This is crucial if a solution is to be applied in a realistic setting. This paper describes the complex, system-of-systems nature of data centers, and discusses the service models used in the industry. We describe a holistic scheduling system that replaces the default scheduler in the Kubernetes container system, taking into account both software and hardware models. We discuss the initial results of deploying this scheme in a real data center, where power consumption reductions of 10-20% were observed. We show that by introducing hardware modelling into a software-based solution, an intelligent scheduler can make significant improvements in data center efficiency. We conclude by looking at some of the future work that needs to be performed in this area.

This paper reviews the accelerated design of power amplifiers (PA) using a nonlinear embedding device model. Examples of practical application to the design Class F, continuous Class-J and Chireix PAs are presented together with the use of a graphic interface (GUI) for the automatic design of dual-input Doherty PAs. Preliminary simulation results on the application of nonlinear embedding to the design of PAs operating in class E at the current-source reference planes are also reported. A modified embedding device model is used for this purpose.

Mobile crowdsensing (MCS) is a distributed sensing paradigm that uses a variety of built-in sensors in smart mobile devices to enable ubiquitous acquisition of sensory data from surroundings. However, non-dedicated nature of MCS results in vulnerabilities in the presence of malicious participants to compromise the availability of the MCS components, particularly the servers and participants' devices. In this paper, we focus on Denial of Service attacks in MCS where malicious participants submit illegitimate task requests to the MCS platform to keep MCS servers busy while having sensing devices expend energy needlessly. After reviewing Artificial Intelligence-based security solutions for MCS systems, we focus on a typical location-based and energy-oriented DoS attack, and present a security solution that applies ensemble techniques in machine learning to identify illegitimate tasks and prevent personal devices from pointless energy consumption so as to improve the availability of the whole system. Through simulations, we show that ensemble techniques are capable of identifying illegitimate and legitimate tasks while gradient boosting appears to be a preferable solution with an AUC performance higher than 0.88 in the precision-recall curve. We also investigate the impact of environmental settings on the detection performance so as to provide a clearer understanding of the model. Our performance results show that MCS task legitimacy decisions with high F-scores are possible for both illegitimate and legitimate tasks.

Polar codes natively lack the flexibility that is desired for practical application. Namely, Arikan’s polar code definition can only achieve code lengths that are powers of two. Rate-matching techniques, known as puncturing and shortening, have been applied to polar codes to grant a flexible block length. By considering polarizing kernels of alternate dimensions, Multi-kernel polar codes improve natural block length flexibility. With the recent advent of the 3GPP 5th generation New Radio specification, there now exists an industry standard for length-flexible polar codes. This paper outlines various state-of-the-art flexible polar coding schemes, such as puncturing, shortening, and multi-kernel construction, and evaluates their efficacy with respect to the newly designed 3GPP standard. Simulations and an in-depth analysis are presented.

The rapid mainstream adoption of cloud computing and the corresponding spike in the energy usage of big data systems make the efficient management of cloud computing resources a more pressing issue than ever before. To this end, numerous online algorithms such as Receding Horizon Control and Online Balanced Descent have been designed. However it is difficult for cloud service providers to select the best control algorithm dynamically for resource provisioning when confronted with consumer resource demands that are notoriously unpredictable and volatile. Furthermore, it highly possible that it might not be the case for any one algorithm to consistently perform well over the months-long contract period. In this paper, we first exemplify the need to address non-stationarity in cloud computing by showcasing traces from MS Azure. We then develop a novel meta-algorithm that combines change point detection and online optimization. The new algorithm is shown to outperform existing solutions in real-world trace-driven simulations.

© 2018 IEEE. Recently, it has been standardized by the 3rd Generation Partnership Project (3GPP) [1] that device-to-device (D2D) communications should use uplink resources when coexisting with conventional cellular communications. With uplink resource sharing, both cellular and D2D links cause significant co-channel interference. In this paper, we consider a D2D mode selection criterion based on the maximum received signal strength (MRSS) for each user equipment (UE) to control the D2D-to-cellular interference. Specifically, a UE will operate in a cellular mode, if its received signal strength from the strongest base station (BS) is larger than a threshold β; otherwise, it will operate in a D2D mode. Furthermore, in our study, cellular UEs, D2D transmit UEs and D2D receiver UEs constitute the entire UE set, which is a more practical assumption than dropping more UEs for D2D reception only in existing works. The coverage probability and the area spectral efficiency (ASE) are derived for both the cellular network and the D2D one. Through our theoretical and numerical analyses, we quantify the performance gains brought by D2D communications and provide guidelines for selecting the parameters for network operations.

Domain name classification is an important issue in the field of cyber security. Notice that objectionable-related domain names are one category of domain names that serve services such as gambling, pornography, etc. They are classified and even forbidden in some areas, some of these domain names may defraud visitors privacy and property. Timely and accurate identification of these domain names is significant for Internet content censorship and users security. In this work, we analyze the behavior of objectionable-related domain names from the real-world DNS traffic, finding that there exist evidently differences between objectionable-related domain names and none-objectionable ones. In this paper, we propose a stacking approach to objectionable-related domain names identification, VisSensor, that automatically extracts name features and latent visiting patterns of domain names from the DNS traffic and distinguishes objectionable-related ones. We integrate convolutional neural networks with fully-connected neural networks to collaborate features of different dimensions and improve experimental results. The accuracy of VisSensor is 88.48% with a false positive rate of \(9.11\%\). We also compared VisSensor with a public domain name tagging system, and our VisSensor performed better than the tagging system on the identification task of the objectionable-related domain names.

International audience; This book constitutes the thoroughly refereed proceedings of the First International Conference on Machine Learning for Networking, MLN 2018, held in Paris, France, in November 2018. The 22 revised full papers included in the volume were carefully reviewed and selected from 48 submissions. They present new trends in the following topics: Deep and reinforcement learning; Pattern recognition and classification for networks; Machine learning for network slicing optimization, 5G system, user behavior prediction, multimedia, IoT, security and protection; Optimization and new innovative machine learning methods; Performance analysis of machine learning algorithms; Experimental evaluations of machine learning; Data mining in heterogeneous networks; Distributed and decentralized machine learning algorithms; Intelligent cloud-support communications, resource allocation, energy-aware/green communications, software defined networks, cooperative networks, positioning and navigation systems, wireless communications, wireless sensor networks, underwater sensor networks.

With the development of unmanned aerial vehicle (UAV) systems, multi-UAV cooperation has attracted noticeable attention. In response to the communication constraints faced in UAV swarm coordination, both the lazy and the eager strategies were proposed to enable swarm-wide reliable information exchange to further behavior coordination for UAV swarms. However, these two algorithms are only evaluated in a fixed and homogeneous network scenario. Hence, how to choose the proper information exchange strategy for a UAV swarm in realistic dynamic and heterogeneous network environments remains an open while interesting problem. Therefore, in this paper, we first evaluate the convergence and payload cost of both strategies for robotic swarms in realistic network scenarios. Then we propose a novel online adaptive information exchange strategy by adopting single relay selection schemes to ensure low payload and fast convergence in various network environments. Numerical results reveal our novel strategy performs well across different network scenarios in terms of convergence and payload cost, showing its robustness, adaptive capability and potential applications in UAV swarms.

Software Defined Networking (SDN) was introduced with a philosophy of decoupling the control plane from the data plane which facilitates network management while ensuring programmability in order to improve performance and monitoring. OpenFlow which enabled SDN was first introduced to match twelve header fields whilst at current it matches forty one which is expected to grow exponentially. Therefore future networks must have the ability to flexibly parse packets through a common interface. Programming Protocol independent Packet Processing (P4) was introduced to achieve the aforementioned by programming the underlying switch, providing instructions and utilizing APIs to populate the forwarding tables. A P4 programmed switch will forward packets through a parser into multiple stages of match+action tables to find the destination node which is considered the most efficient mechanism for routing. This paper takes into the account the latest platform developed for service providers, Open Networking Operating System (ONOS) to deploy two environments configured in the aforementioned technologies in order to test their performance. Four case studies were drawn which were simulated in Mininet which incorporated SDN + P4 switches. A significant increase of performances were recorded when compared with the performance of cases using SDN only.

Nova proposes a departure from today’s complex monolithic database management systems (DBMSs) as a service using the cloud. It advocates a server-less alternative consisting of a cloud of simple components that communicate using high speed networks. Nova will monitor the workload of an application continuously, configuring the DBMS to use the appropriate implementation of a component most suitable for processing the workload. In response to load fluctuations, it will adjust the knobs of a component to scale it to meet the performance requirements of the application. The vision of Nova is compelling because it adjusts resource usage, preventing either over-provisioning of resources that sit idle or over-utilized resources that yield a low performance, optimizing total cost of ownership. In addition to introducing Nova, this vision paper presents key research challenges that must be addressed to realize Nova. We explore two challenges in detail.

Once the sparse representation-based classifier (SRC) was raised, it achieved a more outstanding performance than typical classification algorithm. Normally, SRC algorithm adopts \(l_1\)-norm minimization method to solve the sparse vector, and its computation complexity increases correspondingly. In this paper, we put forward a compressed sensing reconstruction algorithm based on residuals. This algorithm utilizes the local sparsity within figures as well as the non-local similarity among figure blocks to boost the performance of the reconstruction algorithm while remaining a median computation complexity. It achieves a superior recognition rate in the experiments of Yale facial database.

The pervasiveness of Internet of Things (IoT) solutions have stimulated research on the basic security mechanisms needed in the wide range of IoT use case scenarios, ranging from home automation to industrial control systems. We focus on access control for cloud-edge based IoT solutions for which—in previous work—we have proposed a lazy approach to Access Control as a Service for the specification, administration, and enforcement of policies. The validity of the approach was evaluated in a realistic smart-lock scenario. In this paper, we argue that the approach is adaptable to a wide range of IoT use case scenarios by validating the requirements elicited when analyzing the smart lock scenario.

Digitally-intensive PLLs have already demonstrated their effectiveness as frequency synthesizers for cellular applications, being able to fulfill the specifications in terms of phase noise, spurs and power dissipation thanks to the adoption of embedded digital processing that efficiently reduces the analog impairments. In this paper we review how these techniques further enable other capabilities, namely both wideband and linear frequency modulation. The application considered as a case study is the fast chirp generation for frequency-modulated continuous wave radar at millimeter waves. We illustrate how the combination of the two-point modulation of a digital PLL and the background digital pre-distortion of the DCO enable both fast and linear modulation.