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It is now possible to detect dangerous arcing faults in the paper insulation of transformers and distinguish them from arcing faults in oil, using new sub-zones of Duval Pentagons 1 and 2. [ABSTRACT FROM AUTHOR]

This year the IEEE Transactions on Dielectrics and Electrical Insulation (TDEI) is celebrating its fiftieth anniversary. TDEI actually began in 1994 when 'Dielectrics' was added to the previous title of the same publication of IEEE Transactions on Electrical Insulation (TEI). The first issue of TEI was published in March 1965, fifty years ago, with a very modest beginning. That first issue, which can be accessed on IEEE Xplore, had only four papers constituting a total of 19 printed pages. TEI was international in outlook right from its beginning. The four papers in the first issue were submitted from Japan (one paper) and the USA (three papers). The second issue of TEI was published in November 1965 and had papers from the United Kingdom (two) and the USA (one). In its first year TEI had a total of seven papers totaling 48 pages. These papers covered a wide range of topics such as electrical failure of organic insulators, thermal behavior of enamel wires and other solid insulation, electrical breakdown of solids and gaseous insulation. Papers on these topics may still be seen in recent issues of TDEI. [ABSTRACT FROM AUTHOR]

Time-domain indirect methods based on Lyapunov stability theory and linear matrix inequality techniques (LMIs) have been applied for delay-dependent stability analysis of large-scale load frequency control (LFC) schemes. This paper aims to enhance the numerical tractability of large-scale LMIs by exploiting the special characteristics of the LFC loops. First, in the typical LFC model, only a few delayed states that are directly influenced by transmission delays are distinguished from other normal system states. Hence, an improved reconstruction model is formed, based on which the delay-dependent stability condition is established with the decreased order of the LMIs and decision variables. Then, to further improve the numerical tractability of the developed stability criterion, all weighting matrices required in the augmented Lyapunov functional are enforced to have structural restrictions by proposing an extended symmetry-exploiting technique. Case studies show that the method proposed in this paper significantly improves the calculation efficiency of stability criterion established for multi-area power systems at the cost of only a minor reduction in computational accuracy. [ABSTRACT FROM AUTHOR]

Stream processing is used in various fields. In the field of big data, stream aggregation is a popular processing technique, but it suffers serious setbacks when the order of events (e.g., stream elements) occurring is different from the order of events arriving to the systems. Such data streams are called “non-FIFO steams”. This phenomenon usually occurs in a distributed environment due to many factors, such as network disruptions, delays, etc. Many analyzing scenarios require efficient processing of such non-FIFO streams to meet various data processing requirements. This paper proposes an efficient scalable checkpoint-based bidirectional indexing approach, called $CPiX$ C P i X , for faster real-time analysis over non-FIFO streams. CPiX maintains the partial aggregation results in an on-demand manner per checkpoint. CPiX needs less time and space than the state-of-the-art approach. Extensive experiments confirm that CPiX can deal with out-of-order streams very efficiently and is, on average, about 3.8 times faster than the state-of-the-art approach while consuming less memory. [ABSTRACT FROM AUTHOR]

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]

5G wireless networks are expected to support ultra-reliable low latency communications (URLLC) traffic which requires very low packet delays (< 1 ms) and extremely high reliability (~99.999%). In this paper, we focus on the design of a wireless system supporting downlink URLLC traffic. Using a queuing network-based model for the wireless system, we characterize the effect of various design choices on the maximum URLLC load it can support, including: 1) system parameters such as the bandwidth, link SINR, and QoS requirements; 2) resource allocation schemes in orthogonal frequency-division multiple access (OFDMA)-based systems; and 3) hybrid automatic repeat request schemes. Key contributions of this paper which are of practical interest are: 1) study of how the minimum required system bandwidth to support a given URLLC load scales with associated QoS constraints; 2) characterization of optimal OFDMA resource allocation schemes which maximize the admissible URLLC load; and 3) optimization of a repetition code-based packet re-transmission scheme. [ABSTRACT FROM AUTHOR]

This paper describes a test compaction procedure that combines the advantages of using multicycle tests for test compaction with the advantages of using both broadside and skewed-load tests for increasing the fault coverage and achieving test compaction. The procedure is the first to combine these two concepts in a single procedure. The combination is made possible by a definition of a multicycle skewed-load test that is suggested in this paper, and complements the definition of a multicycle broadside test. Experimental results demonstrate the effectiveness of multicycle broadside and skewed-load tests in achieving test compaction for benchmark circuits. [ABSTRACT FROM AUTHOR]

Absolute time synchronization is a basic issue in wireless communication. With the advent of 5G, many emerging vertical industry applications have put forward demands for timing accuracy over air interface. High Precision Timing method over Air Interface based on PHY Layer Signals (TAP) is proposed for mobile networks. It is designed to provide microsecond level timing accuracy at a relatively low cost compared to the existing timing methods, such as GNSS, NTP, PTP, etc. The purpose of this paper is to comprehensively improve TAP, including timing accuracy, stability and compatibility, so as to promote its practical application. This paper proposes improvements to TAP from four aspects: timing algorithm, timing pilot signal, terminal timing process and timing parameters determination. We improve the TAP’s deficiencies in delay estimation, delay compensation accuracy and real-time matching of timing information. We implement the workflow of TAPv2 for UE based on FPGA. Finally, we settle the problem of TAP parameters determination by applying a DQN method. The simulations and tests not only show that the DQN model can effectively determine the TAP parameters, but also show TAPv2 can achieve higher accuracy and stability than TAP in multiple scenarios based on the interaction with baseband. [ABSTRACT FROM AUTHOR]

Due to the non-uniform geographic distribution and time-varying characteristics of the ground traffic request, how to make full use of the limited beam resources to serve users flexibly and efficiently is a brand-new challenge for beam hopping satellite systems. The conventional greedy-based beam hopping methods do not consider the long-term reward, which is difficult to deal with the time-varying traffic demand. Meanwhile, the heuristic algorithms such as genetic algorithm have a slow convergence time, which can not achieve real-time scheduling. Furthermore, existing methods based on deep reinforcement learning (DRL) only make decisions on beam patterns, lack of the freedom of bandwidth. This paper proposes a dynamic beam pattern and bandwidth allocation scheme based on DRL, which flexibly uses three degrees of freedom of time, space and frequency. Considering that the joint allocation of bandwidth and beam pattern will lead to an explosion of action space, a cooperative multi-agents deep reinforcement learning (MADRL) framework is presented in this paper, where each agent is only responsible for the illumination allocation or bandwidth allocation of one beam. The agents can learn to collaborate by sharing the same reward to achieve the common goal, which refers to maximize the throughput and minimize the delay fairness between cells. Simulation results demonstrate that the offline trained MADRL model can achieve real-time beam pattern and bandwidth allocation to match the non-uniform and time-varying traffic request. Furthermore, when the traffic demand increases, our model has a good generalization ability. [ABSTRACT FROM AUTHOR]

This paper considers a device-to-device (D2D) fog-radio access network wherein a set of users are required to store/receive a set of files. The D2D devices are connected to a subset of the cloud data centers and thus possess a subset of the data. This paper is interested in reducing the total time of communication, i.e., the completion time, required to disseminate all files among all devices using instantly decodable network coding (IDNC). Unlike previous studies that assume a fully connected communication network, this paper tackles the more realistic scenario of a partially connected network in which devices are not all in the transmission range of one another. The joint optimization of selecting the transmitting device(s) and the file combination(s) is first formulated, and its intractability is exhibited. The completion time is approximated using the celebrated decoding delay approach by deriving the relationship between the quantities in a partially connected network. The paper introduces the cooperation graph and demonstrates that the problem is equivalent to a maximum weight clique problem over the newly designed graph. Extensive simulations reveal that the proposed solution provides noticeable performance enhancement and outperforms previously proposed IDNC-based schemes. [ABSTRACT FROM PUBLISHER]

Motivated by applications in data center networks, in this paper, we study the problem of scheduling in an input queued switch. While throughput maximizing algorithms in a switch are well-understood, delay analysis was developed only recently. It was recently shown that the well-known MaxWeight algorithm achieves optimal scaling of mean queue lengths in steady state in the heavy-traffic regime, and is within a factor less than 2 of a universal lower bound. However, MaxWeight is not used in practice because of its high time complexity. In this paper, we study several low complexity algorithms and show that their heavy-traffic performance is identical to that of MaxWeight. We first present a negative result that picking a random schedule does not have optimal heavy-traffic scaling of queue lengths even under uniform traffic. We then show that if one picks the best among two matchings or modifies a random matching even a little, using the so-called flip operation, it leads to MaxWeight like heavy-traffic performance under uniform traffic. We then focus on the case of non-uniform traffic and show that a large class of low time complexity algorithms have the same heavy-traffic performance as MaxWeight, as long as it is ensured that a MaxWeight matching is picked often enough. We also briefly discuss the performance of these algorithms in the large scale heavy-traffic regime when the size of the switch increases simultaneously with the load. Finally, we perform empirical study on a new algorithm to compare its performance with some existing algorithms. [ABSTRACT FROM AUTHOR]

This paper analyzes the end-to-end delay performance in an edge-computing scenario where a set of Internet of Things devices (IoTDs) access the computation facilities of an Edge Node by means of a 5G based network. In particular, the paper deals with a two power levels slotted Aloha non-orthogonal-multiple-access (NOMA) scheme and formulates a stochastic end-to-end delay bound, in terms of complementary cumulative probability distribution, by resorting to the application of the martingale theory. In order to validate the proposed analysis, the paper proposes comparisons between the achieved analytical predictions and actual values derived by resorting to extensive computer simulations. Furthermore, the well known Boole bound has been formulated and compared with the proposed Martingale approach to highlight the better behavior of the proposed solution. [ABSTRACT FROM AUTHOR]

With the rapid growth of renewable energy and power electronic loads, voltage source converters (VSCs) have been commonly applied in different VSCs-based power systems, which also bring in stability issues due to their power electronic characteristics. The impedance-based stability theory and corresponding reshaping method can be used to analyze and solve system stability issue. However, dc stability issue in VSCs-based power systems becomes more complicated when considering ac/dc coupling relationship. This paper proposes an improved reshaping control strategy based on the detailed impedance model considering grid impedance and control delay. The influence of grid impedance, control delay and control parameters of VSC on dc stability are further analyzed to identify the cause of potential resonance risk. The proposed impedance reshaping method considers the trade-off between stability improvement and control performance, and compensates the impacts of grid impedance and control delay at the same time. The validity of stability analysis and reshaping method is further verified through the simulation and experimental results. [ABSTRACT FROM AUTHOR]

Intellectual property (IP) cores used in consumer electronics devices mandate protection against reverse engineering (RE) attacks. Functional obfuscation protects the design functionality by enhancing the complexity of RE attacks. This paper proposes a novel low cost (based on power-delay tradeoff) functional obfuscation methodology through employment of robust IP locking technique. In the proposed obfuscation methodology, several strong multipairwise secure IP locking block designs are presented that can only be actuated through application of valid serial key bits. As demonstration, this paper also shows a practical example of a functional obfuscated netlist structure of FIR filter. Proposed obfuscation on comparison with a recent approach for several DSP cores yielded a power reduction of ~10%, design cost reduction ~ 6.5% and security enhancement (strength of obfuscation) of $>\,\,4.29\,\,{e+9}$ times. [ABSTRACT FROM AUTHOR]

This paper proposes an ordered sequence detection (OSD) for digital pulse interval modulation (DPIM) in optical wireless communications. Leveraging the sparsity of DPIM sequences, OSD shows a comparable performance to the optimal maximum likelihood sequence detection with much lower complexity. Compared with the widely adopted sample-by-sample optimal threshold detection (OTD), it considerably improves the bit-error-rate (BER) performance by mitigating error propagation. Moreover, this paper proposes a barrier signal-aided digital pulse interval modulation (BDPIM), where the last of every $K$ symbols is allocated with more power as an inserted barrier signal. BDPIM with OSD (BDPIM-OSD) can limit the error propagation between two adjacent barriers. To reduce the storing delay when using OSD to detect extremely large packets, we propose BDPIM with a combination of OTD and OSD (BDPIM-OTD-OSD), within which long sequences are cut into pieces and separately detected. Approximate upper bounds of the average BER performance of DPIM-OTD, DPIM-OSD, BDPIM-OSD, and BDPIM-OTD-OSD are analysed. Simulations are conducted to corroborate our analysis. Optimal parameter settings are also investigated in uncoded and coded systems by simulations. Simulation results show that the proposed OSD and BDPIM bring significant improvement in uncoded and coded systems over various channels. [ABSTRACT FROM AUTHOR]

In this paper, a second-order bang–bang digital phase-locked loop (BBPLL) with dominant random walk phase noise and transport delay is analyzed using Fokker–Plank equations. Explicit closed-form expressions are derived for the timing error probability distribution function, jitter variance, and power spectral density (psd). For the type-II BBPLL considered in this paper, the timing error distribution is shown to be Laplacian and not Gaussian distributed as previously assumed, while the derived psd is Lorentzian, which is consistent with earlier works. The analytical solutions are valid as long as the continuous-time approximation of the BBPLL dynamics is accurate as is the case for typical operating loop bandwidths. The accuracy of the derived expressions is validated via simulation. [ABSTRACT FROM AUTHOR]

Building clock trees for tight skew constraints of clock delivery networks is standard in the industry. Tight slew constraints of high-performance designs require post-processing techniques to satisfy slew constraints after clock tree synthesis (CTS). Post-processing adversely impacts the power dissipation. This paper proposes slew merging region CTS (SMRcts); a novel algorithm to satisfy bounded slew and skew constraints simultaneously during synthesis. Experimental results performed on International Symposium on Physical Design (ISPD) 2010 benchmarks using a 20-nm FinFET technology show an average reduction of 15% power over a bounded skew approach. Comparison to the ISPD 2010 CTS contest solutions in the literature shows SMRcts producing a 51% improvement in a utility metric. Scalability of SMRcts is demonstrated on ISPD 2013 benchmarks with up to 100k sinks. [ABSTRACT FROM AUTHOR]

This paper considers the problem of reducing the broadcast decoding delay of wireless networks using instantly decodable network coding- based device-to-device communications. In contrast with the previous works that assume a fully connected network, this paper investigates a partially connected configuration in which multiple devices are allowed to transmit simultaneously. To that end, different events occurring at each device are identified so as to derive an expression for the probability distribution of the decoding delay. Afterward, the joint optimization problem over the set of transmitting devices and packet combination of each is formulated. The optimal solution of the joint optimization problem is derived using a graph-theoretic approach by introducing the cooperation graph in which each vertex represents a transmitting device with a weight translating its contribution to the network. This paper solves the problem by reformulating it as a maximum weight clique problem which can efficiently be solved. Numerical results suggest that the proposed solution outperforms state-of-the-art schemes and provides significant gain, especially for poorly connected networks. [ABSTRACT FROM AUTHOR]

Human-machine interactive systems show increasing demand for analysing fast moving objects in high-frame-rate videos. Robust foreground detection, which is able to reduce large amount of redundant background data from high-frame-rate video, becomes the essence to achieve ultra-high-speed human-machine interactions. This paper proposes a local spatial propagation based background model generation, a local linear illumination correction based background model update, and a regional central coordinates and edge keypoints constrained foreground region reselection. The three proposals make up a robust and hardware-friendly foreground detection method. Experimental results prove that the proposed hardware-friendly algorithm achieves high accuracy and robustness on various kinds of challenging cases. Meanwhile, the hardware implementation utilizes little hardware resources and achieves realtime processing of high-frame-rate (784 frame/second) video with the delay less than 1 ms/frame in image processing core. In addition, a practical system is implemented by combing a PC, a high-speed camera and a field programmable gate array (FPGA) for realworld applications. This work will significatively promote the development and application of high-speed human machine interaction. A demo of the proposed vision system working at 784 FPS is available at https://wcms.waseda.jp/em/5f84f75136a6. Note to Practitioners—This paper was motivated by the problem of high-frame-rate video contains large amount of redundant background pixels which makes ultra-high-speed human-machine interactions inaccessible. Existing approaches are mainly focused on designing complex background models, but processing speed, which is the most important issue for ultra-high-speed human-machine interactions, has received relatively little attention. This paper suggests a robust and hardware-friendly foreground detection algorithm which has been implemented as a hardware system by using an FPGA, a high-frame-rate camera, and a PC. We show that the hardware implementation utilizes less hardware resources and achieves real-time processing speed of 784 FPS with the delay less than 1 ms/frame in the image processing core. This work is a pioneering attempt of ultra-high-speed foreground detection, which will significatively speed up the wide applications of ultra-high-speed human machine interactions. [ABSTRACT FROM AUTHOR]

State-of-charge (SoC) imbalance and bus voltage deviation are two of the main problems in autonomous dc microgrids. Based on this concern, this paper presents an improved dual-quadrant SoC weighted control strategy and a distributed optimization control method to achieve SoC balance, ensuring accurate power-sharing and bus voltage recovery. Firstly, this paper couples the injected/released power with the current SoC and observed average SoC value to weight the droop coefficient, which is based on the charge/discharge mode for the energy storage system. Then a secondary controller is designed based on distributed optimal control to eliminate the bus voltage deviation caused by the line impedance difference. The proposed optimal control method optimizes the average bus voltage to the nominal value and achieve accurate power-sharing by constructing the correlated variables and voltage independent intermediate variables exchanged among bulk energy storage units (ESUs). Since the voltage observer cannot accurately observe the true average bus voltage under the communication delay, the proposed distributed optimal control method without the voltage observer can ensure that the average bus voltage is optimized to the nominal value, thus improving the robustness of the control system. Finally, the correctness and effectiveness of the proposed method are verified in Simulink/MATLAB. [ABSTRACT FROM AUTHOR]

Owning to the sub-standards being developed by IEEE Time-Sensitive Networking (TSN) Task Group, the traditional IEEE 802.1 Ethernet is enhanced to support real-time dependable communications for future time- and safety-critical applications. Several sub-standards have been recently proposed that introduce various traffic shapers (e.g., Time-Aware Shaper (TAS), Asynchronous Traffic Shaper (ATS), Credit-Based Shaper (CBS), Strict Priority (SP)) for flow control mechanisms of queuing and scheduling, targeting different application requirements. These shapers can be used in isolation or combination and there is limited work that analyzes, evaluates, and compares their performance, which makes it challenging for end-users to choose the right combination for their applications. This paper aims at (i) quantitatively comparing various traffic shapers and their combinations, (ii) summarizing, classifying, and extending the architectures of individual and combined traffic shapers and their Network calculus (NC)-based performance analysis methods, and (iii) filling the gap in the timing analysis research on handling ATS and CBS used for different priority queues, and two novel hybrid architectures of combined traffic shapers, i.e., TAS+ATS+SP and TAS+ATS+CBS when ATS and CBS used at the same queue. A large number of experiments, using both synthetic and realistic test cases, are carried out for quantitative performance comparisons of various individual and combined traffic shapers, from the perspective of upper bounds of delay, backlog, and jitter. To the best of our knowledge, we are the first to quantitatively compare the performance of the main traffic shapers in TSN. The paper aims at supporting the researchers and practitioners in the selection of suitable TSN sub-protocols for their use cases. [ABSTRACT FROM AUTHOR]

This paper analyzes the literature to identify ideas which may be applied to decentralized realtime railway traffic management. This system represents a new way for dealing with railway traffic perturbations in absence of a central decision maker. Specifically, we are interested in identifying techniques that may constitute suitable automatic mechanisms for the emergence of an effective system behavior. In this literature review, we discuss the possibility of exploiting the existing research works on other transport modes. The analysis of these works makes it clear that real-time railway traffic management is very peculiar. Hence, we consider different approaches: hierarchical self-organization, task allocation, reinforcement learning, consensus, auction and coopetition techniques. Some promising possibilities emerge, which we analyze proposing ideas for modeling decentralized real-time railway traffic management. [ABSTRACT FROM AUTHOR]

Wireless channel characterization and modeling is the foundation of vehicular communication systems. However, most of the existing researches on vehicle-to-vehicle (V2V) channel are aimed at the traditional scenarios such as urban and suburban, and the researches on some complicated vehicular scenarios are insufficient. For example, little attention is paid to viaduct, tunnel, and cutting scenarios in vehicular communications, and these complex scenarios often become the high-incidence area of communication interruption, and then affect the overall performance of the vehicular communication system due to the bad and unique channel characteristics. In this paper, to fill this gap, time-varying characteristics of V2V channels in viaduct, tunnel, and cutting scenarios are investigated. Specifically, based on 5.9 GHz channel measurements, channel non-stationarity is quantitatively evaluated and compared. Further, a detailed analysis of time-varying power and delay of multipath components (MPCs) is presented. Based on the obtained results, the mechanism of physical environment affecting channel characteristics is analyzed, and the impacts of vehicular scenarios are quantified. Besides, the impacts of scenarios on the spatial distribution of MPCs are investigated. The angular distributions of MPCs in the three typical V2V scenarios are revealed, and the corresponding statistical characteristics are presented. Moreover, the characteristics of MPC clusters in different scenarios are further quantified and analyzed, such as MPC number in each cluster and cluster lifetime. It is revealed that the non-stationarity of the V2V channel originates from the birth-death process of MPC clusters, and the birth-death process is modeled statistically. The results in the paper show the V2V channel propagation mechanism and can be used for the design of vehicular communication systems in complicated scenarios. [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]

This paper deals with stabilization of an ideal transformer model (ITM) circuit, used as an interfacing algorithm for hardware-in-the-loop simulations. The ITM allows for the distribution of simulation model computations over multiple processors or can be used in power hardware-in-the-loop simulations. When specific impedance conditions of the partitioned circuit are not met, this interfacing algorithm becomes unstable. This paper first presents a new theoretical approach for representing the ITM interfacing algorithm that is based on delay differential equations. With a stability analysis of the obtained time-delay system, a stabilization method is proposed, which increases the stability boundaries of the ITM algorithm. Simulation examples, including the scenario of a two-level inverter system, are provided. [ABSTRACT FROM AUTHOR]

It is vital to have an exclusive modification in semiconductor production process because of meeting differentiated customer demands in dynamic and competitive global minuscule semiconductor technology market and the highly complex fabrication process. In this paper, we propose a control system based on the dynamic mixed-effect least-square support vector regression (LS-SVR) control system for overlay error compensation with stochastic metrology delay to minimize the misalignment of the patterning process. Moreover, for the stability of the control system in the presence of metrology delay and to deal with nonlinearity among the overlay factors, the novel Lyapunov-based kernel function is merged with the LS-SVR controller. The proposed controller’s operation has been validated and implemented by a major semiconductor manufacturer in Taiwan. The experiments are verified that mixed-effect LS-SVR controller has the higher validity and higher efficiency in comparison with the exponentially weighted moving average (EWMA) and threaded EWMA controllers which had been previously implemented at the company or applied in similar studies. Note to Practitioners—Due to high production complexity in semiconductor manufacturing process, a meticulous and intelligent process control is needed to achieve higher throughput and customer satisfaction. Monitoring a complex system is challenging because the process components and variables operate autonomously and interoperate with other manufacturing segments. This paper proposes a novel run-to-run (R2R) control system to compensate the overlay error during the photolithography process that efficiently deals with the high-mixed manufacturing environment and metrology delay. [ABSTRACT FROM AUTHOR]

For the first time, considering the architecture of monolithic 3-D integration, we evaluate and benchmark the performance of 3-D logic circuits and stability/performance of 3-D 6T SRAM cells with monolayer and few-layer transition metal dichalcogenide (TMD) devices based on ITRS 2028 (5.9 nm) technology node. The impact of random variations on the cell stability is also investigated. With the possibility of adopting monolayer or few-layer TMDs for nFET- and pFET-tiers enabled by monolithic 3-D integration, this paper indicates that the trilayer TMD device may substantially degrade the performance of 3-D logic circuits in spite of its higher mobility. This paper also reveals that stacking the monolayer pFET-tier over the bilayer nFET-tier may provide better nominal stability and read/write performance for 6T superthreshold SRAM compared with the planar technology, whereas the optimum 3-D configuration for near-/sub-threshold operations appears to be the monolayer pFET-tier over the monolayer nFET-tier. Besides the 6T cell structure, 8T SRAM cells are also investigated with monolithic 3-D integration for near-threshold/subthreshold operation. The monolayer nFET-tier over the bilayer pFET-tier configuration is shown to be the optimum 3-D 8T near-threshold/subthreshold cell design. [ABSTRACT FROM AUTHOR]

Polarization and depolarization current measurements are promising on-site, off-line, non-destructive, non-invasive diagnostic tool for condition assessment of paper-oil insulation of transformers. Interpretation of the results of polarization and depolarization current is complex and hence not practiced as a routine diagnostic method for condition monitoring of transformers. This paper discusses various factors affecting polarization and depolarization current measurements with a deeper insight into the theoretical and practical aspects of this technique. Some of the concerns of PDC measurement are explained with support from simulation and experimental studies on paper oil insulation of a laboratory model transformer. Few case studies are discussed to highlight the difficulties in interpretation of results. [ABSTRACT FROM AUTHOR]

This paper proposes on-driving experience sharing algorithms at junctions in infrastructure-assisted vehicles-to-everything networks. For the purpose, a millimeter-wave (mmWave) technology is used because it provides multi-Gbps data rates which is helpful for handling users’ short stay times at junctions and spatial reuse due to high beam directionality which is helpful for interference-avoidance among densely deployed vehicles at junctions. To realize on-driving experience sharing, the proposed algorithms focus on joint resource allocation and scheduling for 3GPP-compliant multiple unicast vehicle-to-vehicle (V2V) communications where the vehicles are group leaders (GLs) in 3GPP Mode 4(d). The resource allocation stands for the roadside unit (RSU) allocation to scheduled V2V GL links where RSU is essentially required for overcoming blockage by establishing two-hop relaying. Because vehicles stay for short times at junctions, this paper designs two algorithms without or with delay considerations. Without delay considerations, the joint optimization of RSU allocation and scheduling was originally formulated as mixed 0-1 non-convex optimization. However our proposed algorithm reformulates the problem into mixed 0-1 convex optimization, which is computationally easier to solve. With delay considerations, our proposed algorithm dynamically controls video contents frame rates for time-average on-driving video sharing quality maximization subject to delay constraints, inspired by Lyapunov optimization. Extensive simulation results demonstrate that our algorithms can significantly outperform in a variety of scenarios. Furthermore, we conduct the cost analysis for the proposed algorithms in terms of capital expenditure (CAPEX) and operating expenditure (OPEX). [ABSTRACT FROM AUTHOR]

The age of information (AoI) is a key performance metric for data freshness in real-time systems, measuring the time elapsed between status updates received at a remote destination. This paper addresses the analysis of both the AoI and the delay for a system demanding timely status updates, consisting of an internet of things (IoT) community, and a multi-core edge computing node (EN). The IoT devices perform channel contention according to a slotted aloha non-orthogonal multiple access scheme with two transmission power levels to access the EN. The objective of the paper is the dynamic selection of both the EN computation capabilities and the suitable access probability for the two power levels, aiming at maximizing the time-average system utility, while guaranteeing the queues stability. The device end-to-end delay is analyzed by resorting to the martingale theoretical approximation under the condition that the Lyapunov optimization framework is performed on a time slot basis, hence leading to a novel instantaneous mixed integer problem formulation. Furthermore, the generalized benders decomposition method is employed to provide a suboptimal solution for the formulated problem. Finally, the accuracy of the proposed framework is validated by comparing the obtained analytical predictions with simulation results. [ABSTRACT FROM AUTHOR]

In recent years, the rapid growth of traffic has become a serious problem of mobile network operators. For effectively mitigating this traffic explosion problem, there have been many efforts to research on offloading the traffic from cellular links to direct communications among users. In this paper, we are motivated by users’ sharing activities, and hence propose the framework of Traffic Offloading assisted by Social network services (SNS) via opportunistic Sharing in mobile social networks (MSNs), TOSS, to offload SNS-based cellular traffic by user-to-user sharing. First, a subset of users who are to receive the same content was selected as initial population depending on their content spreading impacts in the online SNSs and their mobility patterns in the offline MSNs. Then users move, encounter and share the content via opportunistic local connectivity with each other, the content via opportunistic local connectivity with each other, e.g., Bluetooth, Wi-Fi Direct, Device-to-Device in LTE. Individual users have distinct access patterns, which potentially allow TOSS to exploit the user-dependent access delay between the content generation time and each user’s access time for content sharing purposes. The traffic offloading and content spreading among users are analyzed by taking into account various options in linking SNS and MSN traces. Four mobility traces and online SNS trace for evaluation are analyzed. An extended evaluation over a large-scale data set are further carried out, and the effectiveness of TOSS is further proved. [ABSTRACT FROM AUTHOR]

In this paper, we propose a receiver architecture capable of compensating for a time-varying signal distortion induced by the transmitter analog components. In the proposed architecture, the novel transmitter distortion compensating (TDC) block is implemented outside of the feedback control loop of the adaptive equalizer to suppress the feedback delay by optimizing the parameter used in the least mean square (LMS) algorithm. The proposed TDC block is designed for compensating for the DC offset, the IQ amplitude imbalance, the IQ orthogonality error, and the IQ timing skew. Our simulation results show that the proposed scheme significantly reduces the required signal-to-noise ratio penalty from the theoretical limit, which is imposed due to the transmitter components distortion. Furthermore, our theoretical analysis confirms that the delay induced in the feedback loop of the adaptive equalizer determines the upper bound of the LMS step size under the stable condition, hence allowing us to maximize the tracking speed of our receiver. [ABSTRACT FROM AUTHOR]

Flight delay prediction has recently gained growing popularity due to the significant role it plays in efficient airline and airport operation. Most of the previous prediction works consider the single-airport scenario, which overlooks the time-varying spatial interactions hidden in airport networks. In this paper, the flight delay prediction problem is investigated from a network perspective (i.e., multi-airport scenario). To model the time-evolving and periodic graph-structured information in the airport network, a flight delay prediction approach based on the graph convolutional neural network (GCN) is developed in this paper. More specifically, regarding that GCN cannot take both delay time-series and time-evolving graph structures as inputs, a temporal convolutional block based on the Markov property is employed to mine the time-varying patterns of flight delays through a sequence of graph snapshots. Moreover, considering that unknown occasional air routes under emergency may result in incomplete graph-structured inputs for GCN, an adaptive graph convolutional block is embedded into the proposed method to expose spatial interactions hidden in airport networks. Through extensive experiments, it has been shown that the proposed approach outperforms benchmark methods with a satisfying accuracy improvement at the cost of acceptable execution time. The obtained results reveal that deep learning approach based on graph-structured inputs have great potentials in the flight delay prediction problem. [ABSTRACT FROM AUTHOR]

Spatial modulation (SM) is one special type of multiple-input multiple-output (MIMO) technique whose advantage is that only one radio-frequency (RF) chain is needed. Recently, the so-called cross Z-complementary pair (CZCP) was proposed as the SM training sequence. Optimal channel estimation performance over frequency-selective channels can be achieved since the CZCPs have the specific zero correlation zone (ZCZ) for auto-correlation and cross-correlation sums. However, the ZCZ width of the CZCP is theoretically upper bounded by half sequence length. In this paper, the CZCP is extended to the cross Z-complementary set (CZCS) to have larger ZCZ width which can be used in SM to combat larger delay spread. Several generic constructions of CZCSs with large ZCZ widths and flexible lengths are proposed in this paper. Even the perfect CZCS, whose ZCZ width has the maximum value, can be obtained. Numerical simulations demonstrate that the proposed CZCS-based training sequence can tolerate large delay spreads to improve the channel estimation performance in SM. [ABSTRACT FROM AUTHOR]

Connected automated driving technologies have shown substantial benefits to improve the safety and efficiency of traffic. However, connected mixed traffic, which involves both connected automated vehicles and connected human-driven vehicles, is more foreseen for the realistic case in the near future. This brings new challenges because of the complexity of human elements in the system. In addition, the communication constraints in realistic connectivity such as random delays and packet losses bring even more challenges to the system. Therefore, this paper proposes a new anticipative and predictive automated vehicle control approach in connected mixed traffic. The approach first anticipates the states of surrounding vehicles including human-driven vehicles, and then integrates the anticipation into the predictive control of automated vehicles, which can help improve the control performance and also handle the communication constraints. An inverse model predictive control (IMPC) based anticipation approach has been proposed. The proposed approach, together with constant speed (CS), intelligent driver model (IDM) and artificial neural network (ANN) based anticipation methods are integrated with model predictive control (MPC) for automated vehicle control. The approaches have been tested in human-in-the-loop experiments and the results show that the integration with a newly proposed IMPC based anticipation has shown the best performance in terms of accuracy, efficiency and scalability in connected mixed traffic with both ideal and constrained communications. [ABSTRACT FROM AUTHOR]

Future communication networksrequire higher bandwidth, greater coverage, and better throughput. The Space-Air-Ground Integrated Network (SAGIN) has the advantage of wide-area coverage and can cover global communications. It can meet the needs of network resources for maritime activities and remote mountainous areas, which is of great significance to the realization of a new generation of communications networks. With the development of the network and the emergence of delay-sensitive applications such as the Internet of Things, improving the delay performance of the system has received extensive attention. SAGIN involves multiple networks and is more complex than other networks. If there is no reasonable management between different networks, it is easy to lead to difficult link deployment and high time delay. On the basis of research and customization of SFC technology, it can provide a wide range of services and other advantages. It has significant performance in application scenarios involving multi network integration. In order to solve the above problems, this paper studies the SAGIN architecture of SFC based on business types. A service function chain mapping method based on delays prediction is proposed. Calculate the delay of the deployment path and select the path with the lowest delay as the SFC mapping path. The service model is constructed according to the mapping path, and the network slices are divided based on the service type. The simulation results show that the SFC mapping algorithm based on time delay prediction is compared with the traditional SFC mapping scheme. The algorithm does not affect other indicators, the CPU resource utilization rate is 27.8 $\%$ higher, and the link resource utilization rate is 22.7 $\%$ higher. The service acceptance rate increased by 21.5 $\%$ , the latency performance increased by 38.2 $\%$ , and the total resource consumption is reduced by 25.2 $\%$. [ABSTRACT FROM AUTHOR]

Highway platooning of vehicles has been identified as a promising framework in developing intelligent transportation systems. By autonomous or semi-autonomous vehicle control and intervehicle coordination, an appropriately managed platoon can potentially offer enhanced safety, improved highway utility, increased fuel economy, and reduced emissions. This paper is focused on quantitative characterization of the impact of communication information structures and contents on platoon safety. By comparing different information structures that combine front sensors, rear sensors, and wireless communication channels, as well as different information contents such as distances, speeds, and drivers' actions, we reveal a number of intrinsic relationships between vehicle coordination and communications in platoons. Typical communication standards and related communication latency are used as benchmark cases in this paper. The findings of this paper provide useful guidelines in sensor selections, communication resource allocations, and vehicle coordination. [ABSTRACT FROM AUTHOR]

Vertical interconnects used in monolithic 3-D integrated circuits (3-D ICs), so-called monolithic interlayer vias (MIVs), are as small as local vias. Thus, redesigning an existing 2-D IC layout in a monolithic 3-D IC generally results in shorter wire length than the 2-D IC layout. In addition, MIVs have almost negligible resistance and capacitance, so their impact on signal delay is very small. Thus, redesigning a 2-D IC layout in a monolithic 3-D IC is expected to improve its performance significantly. Some researchers designed several monolithic 3-D IC layouts and showed their timing benefits in the literature. In this paper, we present analytical models for performance (timing) benefits of multitier gate-level monolithic 3-D ICs. The analytical models we develop in this paper can be used to quickly estimate the performance benefits multitier gate-level monolithic 3-D integration provides without physically redesigning 2-D IC layouts in 3-D. [ABSTRACT FROM AUTHOR]

In this paper, a radically new anticipatory perspective is taken into account when designing the user-to-access point (AP) associations for indoor visible light communications (VLC) networks, in the presence of users’ mobility and wireless-traffic dynamics. In its simplest guise, by considering the users’ future locations and their predicted traffic dynamics, the novel anticipatory association prepares the APs for users in advance, resulting in an enhanced location- and delay-awareness. This is technically realized by our contrived design of an efficient approximate dynamic programming algorithm. More importantly, this paper is in contrast to most of the current research in the area of indoor VLC networks, where a static network environment was mainly considered. Hence, this paper is able to draw insights on the performance trade-off between delay and throughput in dynamic indoor VLC networks. It is shown that the novel anticipatory design is capable of significantly outperforming the conventional benchmarking designs, striking an attractive performance trade-off between delay and throughput. Quantitatively, the average system queue backlog is reduced from 15 to 8 [ms], when comparing the design advocated to the conventional benchmark at the per-user throughput of 100 [Mbps], in a 15\times 15\times 5 [ \text{m}^{3} ] indoor environment associated with 8\times 8$ APs and 20 users walking at 1 [m/s]. [ABSTRACT FROM PUBLISHER]

This paper presents iRazor, a lightweight error detection and correction approach, to suppress the cycle time margin that is traditionally added to very large scale integration systems to tolerate process, voltage, and temperature variations. iRazor is based on a novel current-based detector, which is embedded in flip-flops on potentially critical paths. The proposed iRazor flip-flop requires only three additional transistors, yielding only 4.3% area penalty over a standard D flip-flop. The proposed scheme is implemented in an ARM Cortex-R4 microprocessor in 40 nm through an automated iRazor flip-flop insertion flow. To gain an insight into the effectiveness of the proposed scheme, iRazor is compared to other popular techniques that mitigate the impact of variations, through the analysis of the worst case margin in 40 silicon dies. To the best of the authors’ knowledge, this is the first paper that compares the measured cycle time margin and the power efficiency improvements offered by frequency binning and various canary approaches. Results show that iRazor achieves 26%–34% performance gain and 33%–41% energy reduction compared to a baseline design across the 0.6- to 1-V voltage range, at the cost of 13.6% area overhead. [ABSTRACT FROM AUTHOR]

A cross-layer based asymmetric resource allocation strategy for multi-destination relay systems in cellular downlink is proposed in this paper. Existing cross-layer schemes on relay networks are based on symmetric resource allocation (RA) where the transmit duration is assumed to be symmetric between base station to relay station (RS) and RS to mobile station links. This may not be realistic and hence our proposed model considers an asymmetric RA (ARA) in which the transmit durations are asymmetric. Very little work has been done in asymmetric resource allocation and many have failed to consider the queue stability and quality of service (QoS) requirements. Packet length ratio is also ignored in many of these works. In this paper, maximum delay threshold, minimum data rate requirement and zero overflow are considered as QoS requirements. This paper evolves an optimal cross-layer based ARA taking into account the above-mentioned factors. Simulation results are also verified in a cellular testbed which shows that the proposed ARA serves the edge users satisfactorily. Cellular parameters, such as blocking ratio, operating expenditure, electromagnetic pollution index, and QoS assurance, are evaluated and compared. [ABSTRACT FROM PUBLISHER]

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]

In this paper, robust exponential synchronization of memristor-based neural networks (MNNs) with nonidentical characteristics is investigated. Coefficient mismatch, time-varying delay mismatch, and activation function mismatch are considered between the drive and the response MNNs. Pinning control strategy is developed to realize robust exponential synchronization and the stability criteria is established by using the Lyapunov function method and differential inclusion theory. Furthermore, the stable region of controller parameters is computed to guarantee that the synchronization errors enter a predetermined error bound within given settling time. Finally, the effectiveness of the proposed methods is verified by the numerical simulations. The methods presented in this paper offer novel schemes for robust exponential synchronization of nonidentical MNNs. [ABSTRACT FROM AUTHOR]

This paper describes a novel approach to investigating the mechanisms related to partial discharge dynamics. Applying the chopped sequence provided insight into the dielectric void and allowed post partial discharge charge decay phenomena to be investigated. The measurements were performed on specimens with an embedded void having three different wall dielectric materials: insulating paper, thermosetting insulation or cross-linked polyethylene. The quantitative approach offers greater information regarding the relationship between measured quantities on phase-resolved patterns and charge decay phenomena inside the void. The comparison of PD inception phase angles between continuous and chopped sequence was used as an indicator for calculation of internal charge time decay in the void. The precise calculation of time constant for various void wall materials was presented. The decaying charge resulted in the variation of the electric field from deposited and accumulated charges. The presented methodology may allow the void to be analyzed with greater clarity, offering the potential to assess various mechanisms such as charge neutralization and conduction. [ABSTRACT FROM AUTHOR]

This paper addresses the estimation and compensation of I/Q imbalance, one of the most prominent impairments found in wideband zero-intermediate frequency transceivers (TRxs). The I/Q imbalance encountered in this kind of TRx comprises not only frequency-selective gain and phase imbalance but also delay imbalance. Unless appropriate compensation is applied, the I/Q imbalance significantly degrades the performance of a communication system. This paper presents a novel compensation technique for transmitter I/Q imbalance based on built-in-self-calibration, a low cost and robust compensation technique that enables manufacturing as well as in-field calibration with low computational complexity. The method's performance is evaluated in a TRx with 64-quadratic-amplitude modulation and 2 GHz of bandwidth implemented with real hardware. The measurements show that the proposed technique achieves an image rejection ratio greater than 35 dB in the entire 2 GHz bandwidth and an error vector magnitude lower than 3%. [ABSTRACT FROM AUTHOR]

Mixed vehicular traffic comprising small cars and two-wheeled vehicles (called motorcycles in this paper) arrive at a lane of a signalized road intersection. The traffic does not follow lane-discipline, in that the arriving vehicles do not necessarily queue up one behind the other. The motorcycles are small enough to stand side-by-side with cars or other motorcycles, so as to fill up the width of the lane. With such queue joining behavior, the waiting vehicles form batches, comprising motorcycles, and at most one car. During the green signal period the vehicles in the head-of-the-line batch exit the intersection together. In this paper, assuming a Poisson point process model for vehicle arrivals, we have provided an approximate analysis of such a queueing system. Our approach is to use an assembly queue model for the batching process. The batches generated by the assembly queue enter an interrupted M/SemiMarkov/1 (or M/SM/1) queue. By analyzing the assembly queue we characterize the batch input process for the interrupted M/SM/1 queue. We then develop an extension of the Webster mean delay formula for obtaining the approximate mean delay in the interrupted M/SM/1 queue. Numerical results from the analysis are compared with simulation results. The analysis is shown to be accurate in predicting the increase in the system capacity due to the batching behavior. [ABSTRACT FROM PUBLISHER]

Modern intelligent transport solutions can achieve an improvement of traffic flow on motorways. With lane-specific measurements and lane-specific control, more measures are possible. Single frequency precise point positioning (PPP) is a newly developed and affordable technique to achieve an improved position accuracy compared with global positioning system (GPS) standalone positioning. GPS-PPP allows for sub-meter accurate positioning, in real time, of vehicles on a motorway. This paper tests this technique in real life; moreover, it presents a methodology to map the lanes on a motorway using data collected by this technique. The methodology exploits the high accuracy and the fact that the most driving is within a lane. In a field test, a GPS-PPP equipped vehicle drives a specific motorway stretch 100 times, for which the GPS-PPP trajectory data are collected. Using these data, the positions and the widths of different lanes are successfully estimated. Comparison with the ground truth shows a dm accuracy. With the parametrized lanes, vehicles can be tracked down to a lane with the GPS-PPP device. [ABSTRACT FROM PUBLISHER]

In this paper, a novel management framework for fog computing with strategic computing speed control at fog nodes (FNs) is studied. In the considered model, mobile users declare requests of offloading resource-hungry computation tasks that are dynamically collected at a dedicated edge server (ES). Upon receiving these requests, the ES can decide to either self-process or delegate some workloads to third-party FNs for maximizing the overall management profit. Unlike the existing work, this paper takes into account strategic behaviors of FNs in computing speed control, i.e., each FN can strategically allocate its computing resource to maximize its utility, which consists of the benefit gained from executing offloaded tasks and the cost incurred by dissatisfied (delayed) service to its own subscribed tasks. To jointly address the long-term system performance and FNs’ strategic interactions, a scheduling mechanism integrating a noncooperative game and a queueing model is formulated. We then investigate two delegation reward settings, i.e., constant and utility-dependent delegation prices, and propose efficient adaptive algorithms to determine the optimal workload distribution at the ES and the computing speed equilibrium among FNs. Both theoretical analyses and simulations are conducted to evaluate the performance of the proposed solutions and demonstrate their superiorities over counterparts. [ABSTRACT FROM AUTHOR]

In this paper, we study how to learn a harmonious deep reinforcement learning (DRL) based lane-changing strategy for autonomous vehicles without Vehicle-to-Everything (V2X) communication support. The basic framework of this paper can be viewed as a multi-agent reinforcement learning in which different agents will exchange their strategies after each round of learning to reach a zero-sum game state. Unlike cooperation driving, harmonious driving only relies on individual vehicles’ limited sensing results to balance overall and individual efficiency. Specifically, we propose a well-designed reward that combines individual efficiency with overall efficiency for harmony, instead of only emphasizing individual interests like competitive strategy. Testing results show that competitive strategy often leads to selfish lane change behaviors, anarchy of crowd, and thus the degeneration of traffic efficiency. In contrast, the proposed harmonious strategy can promote traffic efficiency in both free flow and traffic jam than the competitive strategy. This interesting finding indicates that we should take care of the reward setting for reinforcement learning-based AI robots (e.g., automated vehicles) design, when the utilities of these robots are not strictly in alignment. [ABSTRACT FROM AUTHOR]

Acoustic underwater sensor network (UWSN) is important in terms of business and for military applications. Optimum UWSN design provides a reliable connection with maximum connectivity, minimal multipath, low technical cost, and emphasis on energy conservation. This paper examines the channel estimation parameters, such as channel impulse response, coherence bandwidth, BER due to delay for differentially detected MSK receiver, and transmission loss impact of underwater node placement in three scenarios (ground-based, buoys-based, and horizontal point-to-point sensor node). All data (bathymetry, altimetry, temperature, salinity, and depth) are real and have been sourced from different satellite databases. The case study of this paper is the Desaru beach in the eastern shore of Johor Bahru in Malaysia. In this investigation, Acoustics Toolbox of BELLHOP through MATLAB and mathematical analyzing method has been utilized. As a result, this paper indicates the maximum received power, and the lowest delay time characteristics and TL belong to horizontal point-to-point scenario; moreover, the ground-based scenario has the highest delay time and maximum coherence bandwidth among three scenarios. [ABSTRACT FROM PUBLISHER]