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We report results of the studies relating to the fabrication of a paper-based humidity sensing element comprising a nanostructured polyaniline (PANI) coating on a filter paper substrate. The electrical conductivity of the PANI integrated conductive paper increases from $1.9\times 10^{-6}$ Scm−1 to $1.1\times 10^{-1}$ Scm−1 on modification of the polymerization protocol. This increase in conductivity is ascribed to the change in morphology of the PANI coating from nanogranular ($\text{N}_{\text{g}}$) to partially nanofibrous (pNf). We investigate the effect of observed morphologies of PANI-paper composites on their resistive-type humidity sensing performances. The partially nanofibrous (pNf) PANI-paper exhibits a bimodal humidity response due to polymer-swelling effect at higher humidity (≥ 55% RH). However, the nanogranular ($\text{N}_{\text{g}}$) PANI-paper yields a unimodal, linear humidity response within the humidity range, 16–96.2% RH, with a sensitivity of 9.79 $\text{k}\Omega $ /% RH (${R}^{2}~\approx 0.996$). Hence, the $\text{N}_{\text{g}}$ PANI-paper is a promising alternative to the conventional humidity sensors fabricated on ITO glass/bare glass/PET substrates. [ABSTRACT FROM AUTHOR]

Contribution: This article features a systematic literature review with the objective of presenting a study that reflects the current scenario of research on the cognitive load theory (CLT) in the domain of teaching and learning computer programming. Background: Computer programming is a highly cognitive skill, requiring mastering multiple competencies, and recognized as being difficult to learn, for this reason, the cognitive load (CL) in the learner’s working memory emerged as an influential concept, making CLT one of the most common theories in computing education research. Research Questions: What are the approaches that relate CLT to teaching and learning computer programming? What CLT-related concepts are covered? What evidence is reported with respect to this context? Methodology: Following a formal protocol, a survey was performed for papers linking CLT to teaching and learning programming published between 2010 and 2020. The selection of papers was based on a set of criteria established to drive the selection process, including alignment with the research questions and paper quality assessment. Findings: The approaches applied in the papers are based on measuring the CL; through instructional design based on the development or use of resources or tools, a range of different pedagogy strategies and the CLT concepts. With respect to the concepts, the subjective measurement technique and worked example effect are the most commonly deployed. As far as the evidence reported, the better part is related to the worked example effect and measuring CLs. [ABSTRACT FROM AUTHOR]

Are papers in computer security reproducible? The health of the reproducibility culture in a subfield of security biometrics was assessed in a reproducibility audit of all papers published in the first quarter of 2020. Many papers met some reproducibility criteria, but none met them all. Even in a culture of faster, better, cheaper, reproducibility needn't cost much, but its benefits can be substantial. Buy low, sell high. [ABSTRACT FROM AUTHOR]

Radio Frequency IDentification (RFID) is intended to supplant legacy (optical) bar code scanning technology found in many logistic and retail applications. RFID is distinguished by inexpensive, low power and compact form factor tags, whose longevity and efficacy are predicated on using passive communication techniques and on-tag power harvesting. Such tags employ backscatter modulation, which does not require any active RF components. As a result, backscatter has become an attractive design choice for short-range communications in power constrained wireless sensor networking scenarios. The purpose of this work is two-fold. First, it aims to expose backscatter communication as an emerging topic to a communication systems-theoretic audience. Since backscatter modulation and on-tag power harvesting efficiency are coupled, it is necessary to re-examine notions of power and spectral efficiency from an energy-constraint perspective; this leads to novel coded modulation schemes for future RFID systems. Further, we investigate RFID MIMO systems where the channel fading encountered has different statistics than the classical Rayleigh fading model. In turn,the trade off between diversity order and spatial multiplexing gains are distinct from wide-area MIMO. [ABSTRACT FROM PUBLISHER]

This paper investigates a futuristic spectrum sharing paradigm for heterogeneous wireless networks with imperfect channels. In the heterogeneous networks, multiple wireless networks adopt different medium access control (MAC) protocols to share a common wireless spectrum and each network is unaware of the MACs of others. This paper aims to design a distributed deep reinforcement learning (DRL) based MAC protocol for a particular network, and the objective of this network is to achieve a global $\alpha$ α -fairness objective. In the conventional DRL framework, feedback/reward given to the agent is always correctly received, so that the agent can optimize its strategy based on the received reward. In our wireless application where the channels are noisy, the feedback/reward (i.e., the ACK packet) may be lost due to channel noise and interference. Without correct feedback, the agent (i.e., the network user) may fail to find a good solution. Moreover, in the distributed protocol, each agent makes decisions on its own. It is a challenge to guarantee that the multiple agents will make coherent decisions and work together to achieve the same objective, particularly in the face of imperfect feedback channels. To tackle the challenge, we put forth (i) a feedback recovery mechanism to recover missing feedback information, and (ii) a two-stage action selection mechanism to aid coherent decision making to reduce transmission collisions among the agents. Extensive simulation results demonstrate the effectiveness of these two mechanisms. Last but not least, we believe that the feedback recovery mechanism and the two-stage action selection mechanism can also be used in general distributed multi-agent reinforcement learning problems in which feedback information on rewards can be corrupted. [ABSTRACT FROM AUTHOR]

The future connectivity landscape, and notably, the 5G wireless systems will feature Ultra-Reliable Low Latency Communication (URLLC). The coupling of high reliability and low latency requirements in URLLC use cases makes the wireless access design very challenging, in terms of both the protocol design and of the associated transmission techniques. This paper aims to provide a broad perspective on the fundamental tradeoffs in URLLC, as well as the principles used in building access protocols. Two specific technologies are considered in the context of URLLC: massive MIMO and multi-connectivity, also termed interface diversity. This paper also touches on the importance of the proper statistical methodology for designing and assessing extremely high-reliability levels. [ABSTRACT FROM AUTHOR]

In this paper, we study the diversity-multiplexing-gain tradeoff (DMT) of wireless relay networks under the half-duplex constraint. It is often unclear what penalty if any, is imposed by the half-duplex constraint on the DMT of such networks. We study two classes of networks; the first class, called KPP(I) networks, is the class of networks with the relays organized in K parallel paths between the source and the destination. While we assume that there is no direct source-destination path, the K relaying paths can interfere with each other. The second class, termed as layered networks, is comprised of relays organized in layers, where links exist only between adjacent layers. [ABSTRACT FROM PUBLISHER]

In one of the several manifestations, the future cellular networks are required to accommodate a massive number of devices, several orders of magnitude compared to today’s networks. At the same time, the future cellular networks will have to fulfill stringent latency constraints. To that end, one problem that is posed as a potential showstopper is extreme congestion for requesting uplink scheduling over the physical random access channel (PRACH). Indeed, such congestion drags along scheduling delay problems. In this paper, the use of self-organized device-to-device (D2D) clustering is advocated for mitigating PRACH congestion. To this end, this paper proposes two D2D clustering schemes, namely, random-based clustering and channel-gain-based clustering. Accordingly, this paper sheds light on random access within the proposed D2D clustering schemes and presents a case study based on a stochastic geometry framework. For the sake of objective evaluation, the D2D clustering is benchmarked by the conventional scheduling request procedure. Accordingly, this paper offers insights into useful scenarios that minimize the scheduling delay for each clustering scheme. Finally, this paper discusses the implementation algorithm and some potential implementation issues and remedies. [ABSTRACT FROM AUTHOR]

Within the context of time dissemination techniques for power systems applications, this paper discusses the use of the white rabbit (WR) protocol for synchrophasor networks. Specifically, this paper presents a phasor measurement unit (PMU) integrating the WR technology and its experimental validation with a focus on the synchrophasor phase estimation in steady state conditions, by using a PMU calibrator generating the reference signals. We further compare the accuracy of the developed PMU with other state-of-the-art time synchronization technologies for PMUs, i.e., global positioning system (GPS) and precision time protocol (PTP), demonstrating applicability of WR for PMU sensing networks. [ABSTRACT FROM AUTHOR]

The rapid development of the blockchain leads to a blowout of on-chain transactions, contracts, and currencies, which will further accelerate the increase of data. The existing blockchain systems typically support exact transaction queries, which, however, cannot satisfy the QoS requirements with intelligent adjustment in the blockchain systems. To this end, this paper takes the first step to define and address the practically important problem of transaction cardinality estimation for QoS-adjustable intelligent blockchain systems. We first establish a mathematical relationship between the bit string and transaction cardinality. Thus, we can leverage the number of leading 1s of the obtained bit string to estimate the transaction cardinality. We then improve the block header and body with a corresponding search algorithm to access bit strings in blocks. We also propose an estimation protocol with intelligent adjustable QoS to support accuracy-guaranteed and efficiency-optimized estimation. Finally, we design an authentication scheme and guarantee the reliability of our protocol through rigorous theoretical derivation. When achieving the transaction cardinality estimation in blockchain, two technical challenges need to be addressed. (i) To ensure efficient, verifiable, and overhead-saving bit string accessing mechanism in blockchain, we propose the Merkle Cardinality Tree (MCT) and target block filtering mechanism based on Bloom Filter (BF) in off-chain and improve on-chain block header by joining the abstract of MCT and BF. (ii) To improve estimation efficiency while guaranteeing accuracy requirements in hybrid blockchain scheme, we propose a Dynamic One-round Sampling-based cardinality Estimation (DOSE) protocol and integrate BF-DOSE to intelligently accelerate estimation. We build MCT in Ethereum and store the MCT Root in the block header for estimation authentication. Extensive experiments reveal that our BF-DOSE protocol can well satisfy various accuracy and efficiency requirements of QoS-adjustable intelligent blockchain systems, and is one to two orders of magnitude faster compared with benchmark schemes. [ABSTRACT FROM AUTHOR]

To obtain reliable results from conflicting data in mobile crowdsensing, numerous truth discovery protocols have been proposed in the past decade. However, most of them do not consider the data privacy of entities involved (e.g., workers and servers), and several existing privacy-preserving truth discovery protocols either provide limited privacy protection or have heavy computation and communication overheads due to iterative computation and transmission over large ciphertexts. In this paper, we aim to propose privacy-preserving and lightweight truth discovery protocols to tackle the above problems. Specifically, we carefully design an anonymization protocol named AnonymTD to delink workers from their data, where workers’ data are computed and transmitted without complicated encryption. To further reduce each worker's overheads in the scenarios where workers are willing to share their weights, we resort to the perturbation technology to propose a more lightweight truth discovery protocol named PerturbTD. Based on workers’ perturbed data, two cloud servers in PerturbTD complete most of the workload of truth discovery together, which avoids the frequent involvement of workers. The theoretical analysis and the comparative experiments in this paper demonstrate that our two protocols can achieve our security goals with low computation and communication overheads. [ABSTRACT FROM AUTHOR]

Energy consumption has become one of the main parameters in evaluating sensor systems in the IoT market. Long range sensor systems are not an exception. Their application in the outdoor environment makes them an ideal candidate to combine energy harvesting mechanisms with the low power features. Using just low power electric components is not enough to ensure energy efficiency. Techniques and mechanisms for harvesting and saving energy are presented in this paper and in its core, a low power, energy efficient communication protocol is described. The proposed protocol optimizes the way in which information is collected from the environment, packed and transmitted over long distances with minimum energy. It is specially designed for energy constrained sensor modules which rely on energy harvesting. The gathered information is transmitted in a form of two different packet types called Teach-in and Data telegrams, respectively. A detailed structure of these packets and the energy required for transmission is explained in this paper, along with a deeper protocol physical layer analysis. In addition, this paper demonstrates the huge potential for mass market, as a result of the many proposed solutions that have been tested and implemented in a fully developed functioning prototype. [ABSTRACT FROM AUTHOR]

This paper introduces a new consensus-based control scheme for distributed power systems to solve the distributed economic dispatch (DED) problem. With the development of renewable energy, smart grid, and microgrid, more and more distributed generators will be connected to power systems. Thus the distributed control schemes become more and more important for power systems to control and manage the distributed equipment. Therefore, some consensus-based methods are published previously to solve the DED problem. But the challenge to apply the consensus-based method is to meet the power balance constraint without the centralized facility, since the value of power mismatch is hard to be obtained for a distributed control system. To solve the problem, this paper proposes the method to combine the frequency control methods with the consensus protocol from graph theory to develop the DED control method, so that the real power between the load and the generation can be balanced during the economic dispatch. With this method, a totally distributed optimal control scheme is obtained. The PI frequency controller and neural network frequency controller are employed to develop the DED control method. Then the communication failure problem is considered in this paper. The robust DED control method is proposed to improve the robustness of this distributed control method, allowing the system to stay at the optimal dispatching even if the communication is failed. In addition, the model of transmission line losses is incorporated in the DED problem to reduce the line losses. Finally, several case studies are given in this paper to verify the proposed method. [ABSTRACT FROM AUTHOR]

This paper formulates and solves optimization problems whose objective is to maximize the sum-throughput of wireless sensor networks with radio frequency (RF) energy harvesting (EH) and backscatter communication. The paper proposes and analyzes three protocols for maximizing the sum-throughput; namely, the time-division with downlink data decoding protocol, hybrid power splitting/data decoding protocol, and backscatter-enabled combination protocol. The time-division protocol optimizes a wireless powered communication network (WPCN) with a two-way communication link between the sensors and a hybrid access point. The hybrid protocol optimizes a WPCN with a power splitting downlink data decoding phase. The backscattered-enabled combination protocol optimizes a WPCN with a power splitting downlink data decoding phase and backscatter communication enabled sensors. Numerical results show that the hybrid and combination protocols deliver up to 14.5% and 30.5% increase in sum-throughput, respectively, compared with the reference time-switching RF EH protocol in a dynamic environment. The findings are significant for the future widespread adoption of WPCN systems powered by RF energy sources in the real world by increasing the amount of harvested energy and system achievable data rate. [ABSTRACT FROM AUTHOR]

As an indispensable use case for the 5G wireless systems on the roadmap, ultra-reliable and low-latency communications (URLLC) is a crucial requirement for the coming era of wireless industrial automation. The key performance indicators for URLLC stand in sharp contrast to the requirements of enhanced mobile broadband: low-latency and ultra-reliability are paramount but high data rates are often not required. This paper aims to develop communication techniques for making a paradigm shift from the conventional human-type broadband communications to the emerging machine-type URLLC. One fundamental task for URLLC is to deliver short commands from a controller to a group of actuators within the stringent delay requirement and with high reliability. Motivated by the factory automation setting in which the tasks are assigned to groups of devices that work in close proximity to each other and can thus form clusters of reliable device-to-device (D2D) networks, this paper proposes a novel two-phase transmission protocol for achieving URLLC. In the first phase, within the latency requirement, the multi-antenna base station (BS) combines the messages of all devices within each group together and multicasts them to the corresponding groups; messages for different groups are spatially multiplexed. In the second phase, the devices that have decoded the messages successfully, herein defined as the leaders, help relay the messages to the other devices in their groups. Under this protocol, we design an innovative leader selection-based beamforming strategy at the BS by utilizing the sparse optimization technique. The proposed strategy leads to a desired sparsity pattern in user activity with at least one leader being able to decode its message in each group in the first phase, thus ensuring full utilization of the reliability enhancing D2D transmissions in the second phase. Simulation results are provided to show that the proposed two-phase transmission protocol considerably improves the reliability of the entire system within the stringent latency requirement as compared with existing schemes for URLLC. [ABSTRACT FROM AUTHOR]

This paper considers distributed estimation methods to enable the formation of Unmanned-Aerial-Vehicles (UAVs) that track a moving target. The UAVs (or agents) are equipped with communication devices to receive a beacon signal from the target and share information with neighboring UAVs. The shared information includes the time-of-arrival (TOA) of the beacon signal from the target and estimates on the target’s location. Every UAV processes the received information from the neighbors using a single-time-scale distributed estimation protocol. This differs from multi-time-scale protocols that require (i) many consensus iterations on a-priori estimates, (ii) fast communication among agents (in general, much faster than the sampling rate of the target dynamics), and thus, more-costly communication equipment and processing units. Further, our approach outperforms most single-time-scale methods in terms of observability assumption as these methods assume that the target is observable via the measurement data received from neighboring UAVs (referred to as local-observability). This requires more communications among the sensors. In contrast, our approach is only based on global-observability assumption, and thus, requires less networking (only strong-connectivity) and communication traffic along with less computational load by data-processing once at the same time-scale of sampling target dynamics. We consider modified time-difference-of-arrival (TDOA) measurements with a constant output matrix for the linearized model. UAVs make a pre-specified formation, and by estimating the target’s location via these measurements, move along with the target. Note to Practitioners—Inspired by recent development in industrial UAVs along with emerging progress in low-cost processing units, fog computing systems, and wireless communications, this paper considers mobile tracking of a moving target via a group of wireless-connected autonomous drones. In the classical tracking methods, which are prone to single-point-of-failure, all the sensors need to send their information to a ground central station over a long-range and costly data-transmission channel. In contrast, by collaborative tracking the processing and decision-making are distributed among a swarm of drones equipped with onboard miniaturized electronic parts such as sensors, microcontrollers, microprocessors, and communication units. This article provides an efficient algorithm to enable such drones to autonomously track the moving target in real-time. Note that the cost and tracking ability of the UAV swarm are directly determined by the computational efficiency and communication burden of the estimation algorithm. In this regard, most available estimation algorithms are over budget and even infeasible due to the need for fast data-transmission channels, fast CPUs, and high network traffic. Our proposed estimation technique outperforms similar algorithms in terms of required communication bandwidth, data-transmission rate, and computational resources, which considerably reduces the hardware cost and improves tracking efficiency in real-time large-scale applications. We show the feasibility and efficiency of our distributed tracking method by simulation. [ABSTRACT FROM AUTHOR]

Over recent years, we have seen a significant rise in electric mobility to overcome the anthropogenic emissions by conventional gasoline vehicles. However, the prerequisite of smoothening of peaks and imbalances through bidirectional charging is concatenated with the undesired impacts on reliability and security of power system operation when there are probable intrusions in the eXtreme Fast Charging (XFC) station, hence destabilizing the charging networks. So this paper applies STRIDE based threat modeling to analyze and identify multiple potential threats endured by the cyber-physical system (CPS) of XFC station by using weighted attack defense tree. Potential mitigation strategies are then suggested for the identified severe threats. In addition, this paper also develops a stochastic probabilistic tool, the Hidden Markov Model (HMM) for modeling the security attacks for a given range of identified attack vectors and hence employing an appropriate defense strategy against the malicious hacker. Also, a weighted attack defense tree has been developed to generate various attack scenarios. In the end, the results of the proposed work are substantiated and validated if it is able to considerably improve overall charging efficiency and cyber-physical security of the charging station network. [ABSTRACT FROM AUTHOR]

Contribution: A systematic literature review on the empirical evidence regarding the usage of programming languages for learning purposes is presented. The review analyzes different methods and tools at different educational levels and with different objectives. Background: Learning programming has gained relevance in the last decade. This is due to the massive presence of programmable elements ranging from computers to toys. Because of this, the interest of researchers on this topic has increased. Questions, such as what to use, in what educational stages to use it, the effectiveness of the method, and the focal objectives for learning programming are questions that do not have obvious answers. Research Questions: 1) What empirical evidence exists on the use of educational programming languages (EPLs)? 2) In what context is the research performed? 3) How is effectiveness reported in the literature after applying EPLs? 4) What pedagogical goals are achieved by using EPLs? Methodology: Following a formal protocol, automated searches were performed for primary studies from 2007 to 2018. A total of 62 studies were identified, of which 29 were selected and analyzed since they include some type of empirical evidence. Findings: After performing the evaluation, the results support the need for better approaches with empirical evidence when reporting research on the usage of EPLs. Some research opportunities are identified which concerns the used programming languages, the areas or stages of their application, or the need to have more empirical evidence in general and more studies in non-WEIRD (Western, educated, industrialized, rich, and democratic) contexts. [ABSTRACT FROM AUTHOR]

This paper considers the sample-data-based consensus problem of multiagent systems with time-varying delay and packet losses. To distinguish the time delays caused by network-induced time-delay and packet losses, the switched system is utilized. A lower gain controller is designed based on the solution of a parametric algebraic Riccati equation. The Lyapunov stability theory is utilized to obtain the limitations on the frequency and the duration of packet losses which guarantees the consensus of multiagent systems. On the other hand, we theoretically prove that refined time-delay function can reduce the conservatism. A simulation example is given to illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

There has been much recent interest in private information retrieval (PIR) in models where a database is stored across several servers using coding techniques from distributed storage, rather than being a simply replicated. In particular, a recent breakthrough result of Fazelli, Vardy, and Yaakobi introduces the notion of a PIR code and a PIR array code, and uses this notion to produce efficient PIR protocols. In this paper, we are interested in designing PIR array codes. We consider the case when we have $m$ servers, with each server storing a fraction $(1/s)$ of the bits of the database; here $s$ is a fixed rational number with $s > 1$. A PIR array code with the $k$ -PIR property enables a $k$ -server PIR protocol (with $k\leq m$) to be emulated on $m$ servers, with the overall storage requirements of the protocol being reduced. The communication complexity of a PIR protocol reduces as $k$ grows, so the virtual server rate, defined to be $k/m$ , is an important parameter. We study the maximum virtual server rate of a PIR array code with the $k$ -PIR property. We present upper bounds on the achievable virtual server rate, some constructions, and ideas how to obtain the PIR array codes with the highest possible virtual server rate. In particular, we present constructions that asymptotically meet our upper bounds and the exact largest virtual server rate is obtained when $1 < s \leq 2$. A $k$ -PIR code (and similarly a $k$ -PIR array code) is also a locally repairable code with symbol availability $k-1$. Such a code ensures $k$ parallel reads for each information symbol. So the virtual server rate is very closely related to the symbol availability of the code when used as a locally repairable code. The results of this paper are discussed also in this context where subspace codes also have an important role. [ABSTRACT FROM AUTHOR]

This paper considers secret-key generation between several agents and a base station that observe independent and identically distributed realizations of correlated random variables. Each agent wishes to generate the longest possible individual key with the base station by means of public communication. All keys must be jointly kept secret from all external entities. In this many-to-one secret-key generation setting, it can be shown that the agents can take advantage of a collective protocol to increase the sum rate of their generated keys. However, when each agent is only interested in maximizing its own secret-key rate, agents may be unwilling to participate in a collective protocol. Furthermore, when such a collective protocol is employed, how to fairly allocate individual key rates arises as a valid issue. This paper studies the tension between cooperation and self-interest with a game-theoretic treatment. This paper establishes that cooperation is in the best interest of all individualistic agents and that there exist individual secret-key rate allocations that incentivize the agents to follow the protocol. In addition, an explicit coding scheme that achieves such allocations is proposed. [ABSTRACT FROM AUTHOR]

This paper investigates how much the rate region of the two-user Gaussian interference channel can be enlarged by allowing the two source nodes to cooperate. Two cooperative transmission schemes are proposed, based on dirty-paper coding and the assumption that the radio bandwidth is partitioned into two parts, and each part is utilized by one source node. The achievable rate regions and the outage performance of these two schemes are compared with the simplified Han-Kobayashi scheme, which is an efficient coding scheme for the interference channel. Simulation results show that in some channel realizations, the rate region of the Han-Kobayashi scheme is a subset of the rate regions of our two proposed cooperative transmission schemes. Furthermore, a significant gain in outage performance can be obtained, as the cooperative schemes have twice the diversity order of the simplified Han-Kobayashi scheme. While both cooperative schemes are able to yield large diversity gain, one of them can be implemented by simple decoder. Besides, it has an efficient algorithm for maximizing its weighted sum rate, and can be extended easily to the multi-channel case. [ABSTRACT FROM PUBLISHER]

In this paper, we consider a cooperative simultaneous wireless information and power transfer (SWIPT) network with one source–destination pair and multiple energy harvesting relays. How to efficiently use these relays has been addressed in conventional cooperative networks, and this paper investigates the impact of SWIPT on the performance of such multirelay cooperative networks. In particular, the main contribution of this paper is that a closed-form expression of the outage probability achieved by the multirelay cooperative protocol is obtained, as well as its approximation at high SNR. In addition, the performance of the cooperative network with the SWIPT relays is compared with that in conventional systems with self-powered relays. [ABSTRACT FROM PUBLISHER]

Electroencephalography (EEG) signals are promising as alternatives to other biometrics owing to their protection against spoofing. Previous studies have focused on capturing individual variability by analyzing task/condition-specific EEG. This work attempts to model biometric signatures independent of task/condition by normalizing the associated variance. Toward this goal, the paper extends ideas from subspace-based text-independent speaker recognition and proposes novel modifications for modeling multi-channel EEG data. The proposed techniques assume that biometric information is present in the entire EEG signal and accumulate statistics across time in a high dimensional space. These high dimensional statistics are then projected to a lower dimensional space where the biometric information is preserved. The lower dimensional embeddings obtained using the proposed approach are shown to be task-independent. The best subspace system identifies individuals with accuracies of 86.4% and 35.9% on datasets with 30 and 920 subjects, respectively, using just nine EEG channels. The paper also provides insights into the subspace model’s scalability to unseen tasks and individuals during training and the number of channels needed for subspace modeling. [ABSTRACT FROM AUTHOR]

As the general development trend of the automotive industry, connected and autonomous vehicles (CAVs) can be used to increase transportation safety, promote mobility choices, reduce user costs, and create new job opportunities. However, with the increasing level of connectivity and automation, malicious users are able to easily implement different kinds of attacks, which threaten the security of CAVs. Hence, this paper provides a comprehensive survey on the cyber-security in the environment of CAVs with the aim of highlighting security problems and challenges. Firstly, based on the types of communication networks and attack objects, it classifies various cyber-security risks and vulnerabilities in the environment of CAVs into in-vehicle network attacks, vehicle to everything network attacks, and other attacks. Next, it regards cyber-risk as another type of attacks in the environment of CAVs. Then, it describes and analyzes up-to-date corresponding defense strategies for securing CAVs. In addition, it concludes several available cyber-security and safety standards of CAVs, which is helpful for the practical application of CAVs. Finally, several challenges and open problems are discussed for the future research. [ABSTRACT FROM AUTHOR]

The multi-hop protocols are proved effective in the railway disaster wireless monitoring system. However, farther transmission distance with the larger data will decline the valid lifetime and reliability of the system. Most existing studies focused primarily on the communication protocols optimization, and some works tried to utilize the limited computation ability at the network-level or node-level, which are insufficient for the stiff disaster information monitoring demands. This paper presents an adaptive hybrid computation and communication strategy to fully taking advantage of the sensor processing ability, and improve the energy efficiency at the link-level. Furthermore, an adaptive optimization model is designed to meet the different monitoring demands of the system, and the valid lifetime is improved accordingly. Numerical examples with various operational scenarios are developed to demonstrate the superiority and practicality of the proposed protocol in the lifetime improvement, energy consumption minimization and equalization compared with other outstanding protocols. [ABSTRACT FROM AUTHOR]

Intelligent reflecting surface (IRS) is a newly emerged technology that can increase the energy and spectral efficiency of wireless communication systems. This paper considers an IRS-aided multi-user multiple-input single-output (MISO) communication system, and presents a detailed analysis and optimization framework for the weighted sum-rate (WSR) of the downlink transmission over Rician fading channels. Unlike most of the prior works where the active beamformer at the base station (BS) and passive beamformer at the IRS are jointly designed based on the instantaneous channel state information (CSI), this paper proposes a low-complexity transmission protocol where the IRS passive beamforming and BS power allocation coefficient vector are optimized in the large timescale based on the statistical CSI, and the BS transmit beamforming is designed in the small timescale based on only the instantaneous CSI of the effective BS-user channels. Therefore, the channel training overhead in each channel coherence interval under our proposed protocol is independent of the number of IRS reflecting elements, which is in sharp contrast to most of the prior works. By considering maximum-ratio transmit beamforming at the BS, we derive a lower bound of the ergodic WSR in closed-form. Then, we propose an efficient algorithm to jointly optimize the IRS passive beamforming and BS power allocation coefficient vector for maximizing the ergodic WSR lower bound. Numerical results validate the tightness of our derived WSR bound and show that the proposed scheme outperforms various existing schemes in terms of complexity or capacity performance. [ABSTRACT FROM AUTHOR]

For high-speed quantum key distribution (QKD) post processing, information reconciliation is the most computational step, which usually acts as the system speed bottleneck. Reconciliation efficiency and operation throughput are the two most important performance parameters, but they are often compromised to each other in actual realization due to the available hardware resources. Another characteristic of the information reconciliation is that its channel is time-varying, and in order to guarantee high efficiency, some rate-compatible error correction scheme should be adopted. To cope with the above problems, this paper proposes a rate-compatible high-efficiency reconciliation algorithm based on quasi-cyclic (QC) low-density parity-check (LDPC) codes and puncturing algorithms. On the other hand, in order to obtain high throughput while maintaining low implementation complexity, the normalized min-sum algorithm (NMSA) is realized and optimized by using the fast prototyping tool of high-level synthesis (HLS). The proposed information reconciliation module was implemented on the Xilinx Zynq Ultrascale+ ZCU102 development board. Experimental results show that the maximum throughput rate of the implemented reconciliation module in this paper can reach 136 Mbps, while the efficiency factor is kept lower than 1.32 across the error rate range of 1.7%∼10.6% under the remaining frame error rate level of 10−3. The comprehensive good performance obtained by our design can strongly support the development of modern high-speed QKD systems. [ABSTRACT FROM AUTHOR]

The longest-chain and Greedy Heaviest Observed Subtree (GHOST) protocols are the two most famous chain-selection protocols to address forking in Proof-of-Work (PoW) blockchain systems. Inclusive protocol was proposed to lower the loss of miners who produce stale blocks and increase the blockchain throughput. This paper aims to make an analytical-model-based quantitative comparison of their capabilities against selfish mining attack. Analytical models have been developed for the longest-chain protocol but less to the GHOST protocol. However, the blockchain dynamics and evolution are different when adopting different chain-selection protocols. Therefore, the corresponding analytical models and/or the formulas of calculating metrics (such as miner profitability and system throughput) may be different. To address these challenges, this paper first develops a novel Markov model and the formulas of evaluation metrics, in order to analyze a GHOST-based blockchain system under selfish mining attack. Then extensive experiments are conducted for comparison and we observe that: (i) The GHOST protocol is more resistant to selfish mining attack than the longest-chain protocol from the aspect of relative revenue of selfish miners. (ii) Inclusive protocol can promote the security (evaluated in terms of miner profitability) improvement of the system which has little total computational power or a high forking probability. Additionally, the longest-chain protocol is more sensitive to inclusive protocol than GHOST protocol. (iii) It is hard for each of the two common-used difficulty adjustment algorithms to achieve higher system throughput and security. [ABSTRACT FROM AUTHOR]

This paper presents a method for controlling the voltage of inverter-based Microgrids by proposing a new scale-free distributed cooperative controller. The main contribution of this paper is that the proposed distributed cooperative controller is scale-free where is independent of any information about the communication system and the number of distributed generators, as such it works for any Microgrids with any size. Moreover, the communication network is modeled by a general time-varying graph which enhances the resilience of the proposed protocol against communication link failure, data packet loss, and arbitrarily fast plug and play operation in the presence of arbitrarily finite communication delays as the protocol does not require the knowledge of the upper bound on the delay. The stability analysis of the proposed protocol is provided. The proposed method is simulated on the CIGRE medium voltage Microgrid test system. The simulation results demonstrate the feasibility of the proposed scale-free distributed nonlinear protocol for regulating voltage of Microgrids in the presence of communication failures, data packet loss, noise, and degradation. [ABSTRACT FROM AUTHOR]

Radio frequency identification (RFID) has been widely used in many fields such as object tracking and inventory management. For RFID systems, grouping is a fundamental issue which can support efficient multicast transmissions, dynamic tag management, and accurate aggregate queries. Existing grouping protocols have drawbacks of unknown theoretical communication time, high computational cost on the server end and inability to deal with unexpected tags which are those tags whose IDs have not been collected by readers. In this paper, we would like to address the above limitations and consider a more general grouping problem that allows an arbitrary number of unexpected tags to present. Our objective is to design a protocol that guarantees the reader to efficiently and correctly notify each known tag of its group-ID, while the probability that an unexpected tag is mistakenly notified of any group-ID is smaller than a pre-determined value. In this paper, we first obtain a lower bound on the communication time for solving this generalized grouping problem. Then, we propose a near-optimal protocol, called OPT-G, and prove that its communication time approximately equals the lower bound. Finally, we report extensive simulation results that demonstrate OPT-G's near-optimal performance and its superiority over existing baseline schemes. [ABSTRACT FROM AUTHOR]

This paper investigates the robust containment control problem of multiagent systems with heterogeneous uncertainty and nonlinearity while the nonlinear parts have to satisfy the Lipschitz condition. In this paper, both input time-delay and data transmission time-delay between the agents are considered simultaneously and communication topology of the multiagent systems may switch in the steady-state condition. Under the mentioned conditions, the objective of this paper is to make all the followers’ states converge to the convex hull shaped by the leaders’ states with an expected exponential rate. To this end, an appropriate smooth protocol is proposed. Then, a Lyapunov–Krasovskii functional composed of five terms is proposed and the stability condition is denoted by two linear matrix inequalities (LMIs). In addition to the stability assurance, solving the LMIs would obtain the suitable gains for the protocol. Finally, some numerical simulations are given to verify the theoretical analysis. [ABSTRACT FROM AUTHOR]

The intelligent radio is a novel emerging paradigm catching on in many practical applications, in order to provide context awareness techniques, able to learn by the environment conditions applying machine learning frameworks. The channel state information (CSI) prediction is one of the main challenges that an intelligent radio has to face with. This paper deals with the CSI prediction in the case of a buffer aided relaying communication scheme with adaptive link selection previously proposed in the literature where a direct source-destination link is not available and with both links affected by an independent fading. In particular, the CSI prediction has been reduced here to a time series prediction problem, performed by involving the usage of the recurrent neural networks. Finally, the validation of the effectiveness of the proposed intelligent radio buffer-aided relaying scheme with adaptive link selection approach has been pursued by presenting performance comparisons with the previously proposed scheme under the assumption of an ideal and actual CSI estimations, respectively. [ABSTRACT FROM AUTHOR]

With the growing use of mobile devices, location-based services (LBS) are becoming increasingly popular. BLS deliver accurate services to individuals according to their geographical locations, but privacy issues have been the primary concerns of users. Privacy-preserving LBS (PPLBS) were proposed to protect location privacy, but there are still some problems: 1) a semi-trusted third party (STTP) is required to blur users’ locations; 2) both the computation and communication costs of generating a query are linear with the size of queried areas; 3) the schemes were not formally treated, in terms of definition, security model, security proof, etc. In this paper, to protect location privacy and improve query efficiency, an oblivious location-based services (OLBS) scheme is proposed. Our scheme captures the following features: 1) an STTP is not required; 2) users can query services without revealing their exact location information; 3) the service provider only knows the size of queried areas and nothing else; and 4) both the computation and communication costs of generating a query is constant, instead of linear with the size of queried areas. We formalise both the definition and security model of our OLBS scheme, and propose a concrete construction. Furthermore, the implementation is conducted to show its efficiency. The security of our scheme is reduced to well-known complexity assumptions. The novelty is to reduce the computation and communication costs of generating a query and enable the service provider to obliviously generate decrypt keys for queried services. This contributes to the growing work of formalising PPLBS schemes and improving query efficiency. [ABSTRACT FROM AUTHOR]

Covert communication is an method that plays an important role in secure data transmission. The technology embeds covert information into data and propagates it through covert channels. The communication quality depends on the choice of channel and data embedding techniques. Recently, blockchain has emerged to become the preferred channel to carry out covert communication for its decentralization and anonymity features. Existing covert transaction methods are constructed transaction-by-transaction, which makes them immune to text analysis-based detection methods. However, it is easy to expose their features on the transaction graph level. Unfortunately, there is yet no method to detect covert transactions by the features of transaction graph. In this paper, we propose a covert transaction detection method based on graph structure. By analyzing the statistical features of graph structure for addresses, we can infer whether they are the participants of covert transactions. Furthermore, we design a protection method of covert transactions based on graph generation networks. By adjusting the structural features between different addresses, our method enhances the security of multiple interrelated covert transactions. Experimental analysis on the Bitcoin Testnet verifies the security and the efficiency of the proposed methods. [ABSTRACT FROM AUTHOR]

This paper considers from the perspective of MAC layer, a throughput maximization problem of NOMA-ALOHA, ALOHA implemented over NOMA (non-orthogonal multiple access), that can decode simultaneously transmitted multiple packets via successive interference cancellation (SIC) if each of the multiple packets has a different power level from those of others. We start with a throughput optimization problem for two power levels and extend it to a problem for a general number of power levels. For the case of two power levels, we find upper and lower bounds of the maximum throughput and suggest a practical sub-optimal transmission probability whose throughput is close to the maximum. The maximum throughput of NOMA-ALOHA is at least 1.774 times higher than that of traditional slotted ALOHA in our numerical example. We extend the optimization problem into a general one with arbitrary number of power levels. We numerically analyze the performance through a relaxed problem of the original one with high complexity. Our numerical analysis shows that the maximum throughput of NOMA-ALOHA with three power levels is 2.33 times higher than simple ALOHA’s maximum throughput and that adding one power level to NOMA-ALOHA with two power levels enhances throughput at least by more than 28 percent. [ABSTRACT FROM AUTHOR]

Phasor measurement units (PMUs) are being widely installed in the transmission grid. Many power system applications based on PMUs have been developed or are under development in academia and industry. For those applications, data latency is often a critical factor that affects their performance thus making the topology of the communication network that exchanges real-time data between the control center (CC) and substations (SS) of vital importance. This paper introduces a method to conceptualize and analyze possible communication topologies by simulating them in Network Simulator 3 (NS3). Moreover, a new algorithm is developed to optimize the clustering of substations in such a way that the data latency performance of the decentralized communication topology can meet the requirements for PMU based applications. To validate the proposed methodology, the IEEE 118-bus system is used as the test case. A PMU based wide-area controller for transient stability is simulated in the MATLAB Simulink to validate the proposed communication topologies. It is concluded from the simulation results that the decentralized communication topology at a lower cost designed by optimizing the substation cluster boundaries can be an alternative choice and can help PMU based applications achieve good performance by limiting data latency to an acceptable level. Also, this paper can provide a technical guidance for power utilities choosing the most appropriate communication network for the PMU based real-time applications. [ABSTRACT FROM AUTHOR]

This paper proposes a novel distributed noise-resilient secondary control for voltage and frequency restoration of islanded microgrid inverter-based distributed generations (DGs) with an additive type of noise. The existing distributed methods commonly are designed as secondary control system systems that operate on the assumption of ideal communication networks among DGs. However, the channels are prone to stochastic noise, whereas each DG obtains noisy measurements of the states of its neighbors via environmental noises. The existing distributed noise-resilient methods, ignore a complete model of the system. In contrast, this paper proposes consensus protocols that take into account both the noisy measurements and a complete nonlinear model of the system, examines the mean-square average consensus for voltage and frequency restoration of islanded ac microgrids in an uncertain environment, and provides accurate proportional real power sharing. Our proposed consensus protocol contains two parts: the state feedback of the agent and the relative states of the DG and its neighboring DGs. Finally, simulation studies are carried out in MATLAB/SimPowerSystems to evaluate the performance of the control laws. Simulation results and comparison with previous work reveals the effectiveness of the proposed method in regulating microgrid voltage and frequency and providing accurate proportional real power sharing. [ABSTRACT FROM AUTHOR]

Real-time dynamic workload consists of tasks that can arbitrarily join and leave the system at run-time. To avoid incurring deadline misses, tasks that request to join the system must pass an admission test, which has to cope with potential scheduling transients originated by the residual effect of the tasks that previously left the system. This phenomenon may require some tasks to suffer an admission delay before being accepted for execution. This paper focuses on uniprocessor earliest-deadline first (EDF) scheduling with constrained deadlines and explicitly considers methods for handling scheduling transients in the presence of dynamic real-time workload. A generalized analysis framework is first presented to overcome several limitations of the existing approaches (including the support for overlapping transients), and is then used to derive methods for computing bounds on the admission delays incurred by tasks. Building on such results, an on-line protocol is proposed to handle the admission control of a dynamic workload, which also comes with a variant that can execute in polynomial time to favor its practical application. Furthermore, the paper shows how the presented analysis can be used off-line for analyzing mode-changes among static task sets. Experimental results are finally presented to evaluate the proposed algorithms. [ABSTRACT FROM AUTHOR]

This paper proposes interference mitigation techniques for provisioning ultrareliable low-latency wireless communication in an industrial automation setting, where multiple transmissions from controllers to actuators interfere with each other. Channel fading and interference are key impairments in wireless communication. This paper leverages the recently proposed “Occupy CoW” protocol that efficiently exploits the broadcast opportunity and spatial diversity through a two-hop cooperative communication strategy among distributed receivers to combat deep fading, but points out that because this protocol avoids interference by frequency division orthogonal transmission, it is not scalable in terms of bandwidth required for achieving ultrareliability, when multiple controllers simultaneously communicate with multiple actuators (akin to the downlink of a multicell network). The main observation of this paper is that full frequency reuse in the first phase, together with successive decoding and cancellation of interference, can improve the performance of this strategy notably. We propose two protocols depending on whether interference cancellation or avoidance is implemented in the second phase, and show that both outperform Occupy CoW in terms of the required bandwidth and power for achieving ultrareliability at practical values of the transmit power. [ABSTRACT FROM AUTHOR]

This paper is concerned with the consensus problem of general linear dynamic multiagent systems with stochastic sampling. In this paper, the sampling intervals randomly switch between two different values. The communication topology between agents is fixed and directed. Full- and reduced-order observers are designed based on neighbor agents’ relative output information. The algorithms to construct such observers are also provided. By using the estimated states of the agents, the observer-based consensus protocol with stochastic sampling are presented. Sufficient conditions to ensure consensus in mean square are derived by using Lyapunov stability theory. Finally, simulations are given to examine the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

This paper addresses the distributed consensus controller design approaches for one-sided Lipschitz nonlinear multiagents by employing relative state feedback. A new treatment for one-sided Lipschitz nonlinearity is rendered from the consensus control point of view. By employing the quadratic inner-boundedness and the one-sided Lipschitz constraints, a sufficient condition for asymptotic consensus of nonlinear systems under strongly connected communication topologies is provided. Further, a robust consensus protocol design scheme for the nonlinear multiagents is derived by ensuring the ${L_{2}}$ stability of the consensus error system. Furthermore, a novel robust consensus control scheme against amplitude-bounded perturbations is developed that guarantees asymptotic convergence of the consensus error into a compact set. Extensions to the proposed methodologies for the leader-following consensus for a spanning tree communication topology with the leader as the root are addressed. In contrast to the conventional consensus control methodologies, this paper is less conservative and can be applied to a broader class of nonlinear multiagent systems. Moreover, the proposed consensus control approach is less conservative for robustness against disturbances owing to its ability to handle amplitude-bounded disturbances and due to the relaxation of a balanced communication topology. A numerical simulation study is provided for the consensus control of eight mobile agents. [ABSTRACT FROM AUTHOR]

Electrical power system monitoring, protection, operation, and control schemes are undergoing significant changes toward the next generation fully automated, resilient, and self-healing grids. At present, there still exists a lack of available user-friendly tools for the synchronized measurement technology supported application design. This paper presents a synchro-measurement application development framework (SADF) to promote a simplified design and thorough validation of synchro-measurement (IEEE Standard C37.118.2-2011) supported user-defined applications under realistic conditions. The proposed SADF supports online receiving of a phasor measurement unit (PMU) or phasor data concentrator (PDC) provided data stream and enables simultaneous use of processed machine-readable synchro-measurements in advanced user-defined applications. This paper fills the scientific gap between the IEEE Standard C37.118.2-2011 specifications and its implementation by proposing a novel robust communication technique and efficient synchro-measurement data parsing methodology. As a proof of concept, the proposed SADF is implemented as a novel open-source MATLAB library. Combining this library with MATLAB’s signal processing and visualization functions allows mastering the design and validation of complex wide-area monitoring, protection, and control applications, as well as PMU/PDC performance and compliance verification. Finally, this paper verifies the proposed library against the standard specifications, assesses its interoperability and performance via a cyber-physical simulation platform, and presents online voltage magnitude monitoring as an example application. [ABSTRACT FROM AUTHOR]

Co-simulation of heterogeneous systems allows for in-depth analysis of various aspects of power systems’ operation while staying within the environments of the simulation tools that are best fit to represent their respective domains. Equipped with a proprietary co-simulation platform, the paper focuses on the issue of power-conjugate coupling between parts of power grids modeled in transient stability and electromagnetic transient simulation tools. The problems of co-simulation stability and precision in presence of delays are tackled by means of designing a proper coupling interface. It is shown that two established interface methods – the V-I method and the Transmission Line Interface – are special cases of a generalized interface framework proposed in the paper. Moreover, a new interface algorithm is described by parametrizing the generalized framework. Analytical tools are also formulated to aid in the analysis of interface stability and precision via the concepts of passivity and transparency. Simulation results of benchmark systems of various complexity demonstrate the application of the developed power coupling interface. [ABSTRACT FROM AUTHOR]

Recently, several methods for SARS-CoV-2 detection have been developed to obtain rapid, portable, cheap, and easy-to-use diagnostic tools. This review paper summarizes and discusses studies on the development of point-of-care devices for SARS-CoV-2 diagnosis with comparisons between them from several aspects. Various detection methods of the recently developed portable COVID-19 biosensor will be presented in this review. The discussion is divided into four major classifications based on the target biomarkers of SARS-CoV-2, such as antibodies, nucleic acids, antigens, and metabolic products. An overview of the potential development for future study is also provided. Moreover, basic knowledge of biosensors is also explained for tutoring the implementation of theory into the research of COVID-19 biosensors. This review paper is aimed to provide a tutorial by collecting the information on the development of a point-of-care device for SARS-CoV-2 detection to provide information for further research and propose the new COVID-19 portable diagnostic tool. [ABSTRACT FROM AUTHOR]

In a mobile radio-frequency identification (RFID) system, tagged items enter and leave the reader’s field at a constant speed. The possibility of tags leaving the reader’s interrogation zone without being identified is known as tag loss. Minimizing the tag loss ratio in the presence of random denial-of-service (DoS) attacking signals by optimizing the number of frames is investigated in this paper. The results show that the number of frame control is not needed to reduce the tag loss ratio if the tag entering rate is below a critical limit. The number of frames has to abruptly reduce to keep the tag loss ratio lower if the tag entering rate exceeds that critical limit. This critical limit of the tag entering rate is derived analytically. An analytical solution of the optimum number of frames in the presence of attacking signals that also minimize the tag loss ratio is devised. The technique for setting the optimum number of frames is also presented. The presented results in this paper with random DoS attacking signals is so general that those can be converted without DoS attacking signals by setting the DoS attacking signals equal to zero. The results of this paper can be used for mobile RFID system design with and without DoS attacking signals. [ABSTRACT FROM AUTHOR]