Search

A nonparametric procedure to estimate the conditional probability that a nonstationary geostatistical process exceeds a certain threshold value is proposed. The method consists of a bootstrap algorithm that combines conditional simulation techniques with nonparametric estimations of the trend and the variability. The nonparametric local linear estimator, considering a bandwidth matrix selected by a method that takes the spatial dependence into account, is used to estimate the trend. The variability is modeled estimating the conditional variance and the variogram from corrected residuals to avoid the biasses. The proposed method allows to obtain estimates of the conditional exceedance risk in non-observed spatial locations. The performance of the approach is analyzed by simulation and illustrated with the application to a real data set of precipitations in the USA.Supplementary materials accompanying this paper appear on-line. [ABSTRACT FROM AUTHOR]

Google proposed a new TCP congestion control algorithm (CCA), Bottleneck Bandwidth and Round-trip propagation time (BBR) which has opened up new dimensions in congestion control. BBR tries to operate near Kleinrock's operating point to avoid excessive queue formation at the bottleneck and to use the link bandwidth optimally. BBR creates a model of the network path by measuring the bottleneck bandwidth and minimum round-trip time (RTT) to maximize the delivery rate and minimize latency. BBR v2 is an updated version of BBR which addresses many shortcomings of the original BBR (BBR v1) such as interprotocol fairness, RTT fairness, and excessive retransmissions. However, BBR v2 has certain limitations in its operation in IEEE 802.11ac (Wi-Fi 5) networks. The default BBR v2 limits the throughput of Wi-Fi 5 and an increased latency has been observed. This is because the Wi-Fi 5 frame aggregation logic is underutilized and fewer frames are being sent to the Wi-Fi 5 interface. In this paper, we have proposed BBR-n (BBR new) which provides better throughput than the generic BBR v2 in the Wi-Fi 5 networks. Real-time experiments were performed over a physical testbed using Flent to confirm that BBR-n achieves over double throughput as compared to generic BBR v2 and reduced latency in networks as compared to pure loss-based variants such as Cubic and Reno. [ABSTRACT FROM AUTHOR]

To alleviate the congestion caused by the tidal traffic and to improve the operational performance of both directions in arterials, this paper proposes a coordinated control model for arterials with asymmetric traffic demands in both oversaturated and unsaturated directions. The model utilizes a three-step architecture: (1) A mixed-integer linear programming model is built to maximize the throughput according to the relationship between traffic supply and demand as well as the balance between inflow and outflow. (2) A quadratic programming model is constructed to minimize the vehicle delay in the oversaturated direction based on Lighthill-Whitham-Richards theory. (3) A mixed-integer linear programming model is built to maximize the variable bandwidth in the unsaturated direction by introducing the relaxation variable. Furthermore, a three-step algorithm is used to solve the model and obtain the optimal arterial signal timing. Finally, a simulation model is put forward to verify the coordinated model. The results indicate that the model meet the asymmetric traffic demand through optimizing the arterial throughput, reducing delay in the oversaturated direction and maximizing the green wave bandwidth in the unsaturated direction. [ABSTRACT FROM AUTHOR]

The popularity of video services such as video call or video on-demand has made it impossible for people to live without them in their daily lives. It can be anticipated that the explosive growth of vehicular communication owing to the widespread use of in-vehicle video infotainment applications in the future will result in increasing fragmentation and congestion of the wireless transmission spectrum. Accordingly, effective bandwidth management algorithms are demanded to achieve efficient communication and stable scalability in next-generation vehicular networks. To the best of our current knowledge, a noticeable gap remains in the existing literature regarding the application of the latest advancements in network communication technologies. Specifically, this gap is evident in the lack of exploration regarding how cutting-edge technologies can be effectively employed to optimize bandwidth allocation, especially in the realm of video service applications within the forthcoming vehicular networks. In light of this void, this paper presents a seamless integration of cutting-edge 6G communication technologies, such as terahertz (THz) and visible light communication (VLC), with the existing 5G millimeter-wave and sub-6 GHz base stations. This integration facilitates the creation of a network environment characterized by high transmission rates and extensive coverage. Our primary aim is to ensure the uninterrupted playback of real-time video applications for vehicle users. These video applications encompass video conferencing, live video, and on-demand video services. The outcomes of our simulations convincingly indicate that the proposed strategy adeptly addresses the challenge of bandwidth competition among vehicle users. Moreover, it notably boosts the efficient utilization of bandwidth from less crowded base stations, optimizes the fulfillment of bandwidth prerequisites for various video applications, and elevates the overall video quality experienced by users. Consequently, our findings serve as a successful validation of the practicality and effectiveness of the proposed methodology. [ABSTRACT FROM AUTHOR]

Most existing traditional congestion control algorithms are difficult to adapt to the highly dynamic link environment of wireless Ad hoc network. In order to solve the above problem, this paper proposed a method of improving the performance of congestion control based on deep reinforcement learning, Enhanced-CC. It conducted a preliminary detection of the congestion window by using the traditional congestion control algorithm. On this basis, the method used deep reinforcement technology to learn the real-time optimal congestion window range of the link. When the congestion window calculated by the traditional congestion control algorithm was too large or too small, the method adjusted the congestion window, so that the sending rate could match the highly dynamic link bandwidth, and the method could improve the transmission performance of the traditional congestion control algorithm. The experimental results show that Enhanced-CC can significantly improve the performance of traditional congestion control algorithms such as BBR, CUBIC, Westwood, Reno, and is superior to the performance of fully learning based congestion control algorithms such as PCC and PCC Vivace, and the combination of deep reinforcement learning and traditional congestion control algorithms such as Orca and DeepCC. [ABSTRACT FROM AUTHOR]

In elastic optical networks (EON), routing, modulation selection, and spectrum assignment (RMSA) is crucial in provisioning connection requests. Multipath RMSA offers a number of benefits including provisioning of ultra-high bandwidth demands and better utilization of fragmented spectrum resource. By Combining with traffic grooming, multipath RMSA and traffic grooming is able to provide better utilization of network resource in provisioning connection requests. Adding multi-hop routing mechanism to multipath RMSA and traffic grooming increases the flexibility for selecting paths resulting in higher probability of successfully finding routing paths for connection requests. Dynamic multipath RMSA problem in EON has been investigated extensively in the literature. Dynamic multi-hop multipath RMSA and traffic grooming problem in EON is far from been well studied. This paper proposes an algorithm for the dynamic multi-hop multipath RMSA and traffic grooming problem in OFDM-based elastic optical networks with sliceable bandwidth-variable transponders. Performance of the proposed algorithm is studied via simulation. Our simulation results show that the proposed algorithm yields lower bandwidth blocking ratio than an existing algorithm. [ABSTRACT FROM AUTHOR]

In this paper, an improved quadrature signal generator (QSG) parameter tuning procedure is proposed, based on a modification of an existing adaptive observer QSG algorithm. Namely, in the existing solution an observer-based QSG is proposed with a parameter tuning procedure that results in a bandwidth frequency equal to the QSG input signal frequency, while in this paper, a modification of this parameter tuning procedure is proposed that enables the QSG to operate with increased bandwidths. A comparative analysis is presented, which evaluates both the existing solution and the solution based on the novel observer parameter tuning algorithm. Also, it is shown that when existing and proposed observer-based QSG operates with bandwidths that surpass the input signal angular frequency, the high-pass resulting observer frequency characteristics are obtained. By using frequency responses, and simulation and experimental tests, which include basic QSG operation and the PLL based on the proposed QSG, the resulting improvements are presented and compared. Also, the adaptive observer-based QSG with improved parameter tuning procedure is employed in the positive sequence component separation algorithm for the nonsymmetrical three-phase system, which represents an original application this type of QSG structure. [ABSTRACT FROM AUTHOR]

E-government services will play an outstanding role in the next generation of the internet. With growing real-time requirements, internet generation has to offer Quality of Service (QoS) for various types of real-time streaming services. When the bandwidth required exceeds the to be had community resources, community paths can get congested, which leads to a postponement in packet transport and packet loss. This situation leads to the design of new techniques for congestion avoidance and control. One of the popular and suitable congestion management mechanisms which are useful in transmitting multimedia applications in the transport layer is TCP Friendly Rate Control Protocol (TFRC). The fact that bridging the existing e-government security service gap between developed and developing countries. In addition, revealed that system security is one of the major barriers that prevent citizens from adopting EGovernment services. Therefore, the network reliable and secure communication channel among government agencies and the entire system, and the Gap related to system quality were found to the security issues among the strongest barriers to hindering E-Government performance. The aim of this study is to examine some of the emerging issues surrounding the Security detection of E-Government Systems in Jordan. Furthermore, the main objective of this research enhances the speed up of training the TFRC protocol through the receiver to group losses and marks that occurred during the same round-trip time. In this paper, we increase stop-to-stop probing strategies which could degree bottleneck bandwidth alongside arbitrary, Accurate measurement of network bandwidth is crucial for network management applications as well as flexible Internet applications and protocols which actively manage and dynamically adapt to changing utilization of network resources. The constructed dataset physically resides in the (dataset) file stored on the data computer, but the configuration files for the dataset reside within a directory for software programs. A software program contains a set of configuration files that construct a dataset (including its extended dimensions) for a specific analysis purpose. It's not easily possible with standard testing approaches such as JUnit, because a node relies on the KNIME Core framework that handles tasks such as execution and data handling. Therefore, a node must be tested within a running KNIME instance. [ABSTRACT FROM AUTHOR]

Aiming at the problems of complex consensus process, poor stability, and the system is greatly affected by node activity, processing capacity, bandwidth and other factors in Hashgraph, this paper proposed a Hashgraph consensus algorithm based on credit. Firstly, the algorithm created a credibility model and combined it with a reward mechanism to standardize the behavior of nodes and encourage them to actively participate in data synchronization and consensus. Secondly, this paper introduced the consensus optimization process of leaders, and reduced the three steps of voting, votes collection and event confirmation in virtual voting to two steps of selecting leaders and confirming events, thus shortening the time of transaction completion and confirmation. Finally, in order to ensure the security and fairness of the leader nodes, this paper designed a leader selection algorithm based on credibility to realize the unpredictability of the leader nodes to resist the Byzantine nodes' attack on the leader nodes in advance. Experiments and security analysis show that the algorithm effectively reduces the system's dependence on nodes and has the advantages of strong system stability, high consensus efficiency, and strong security. [ABSTRACT FROM AUTHOR]

To solve the inconsistency of flow rules between the control plane and data plane caused by SDN data plane software and hardware faults, configuration faults, etc., this paper proposed a P4-based Consistency Verification mechanism for SDN control-data plane (P4 CV). P4 CV firstly sent probes with a specific structure to the data plane, and then each P4 switch inserted its runtime information of flow rules in the data plane into the probes. Finally, P4 CV adopted the consistency-verification algorithm, based on symbolic execution, to compare the configuration from the control plane and telemetry information from the data plane. The simulation results show that the single path verification time of P4 CV is not affected by the network topology and is only linearly related to the number of nodes on the path. In a multipath forwarding scenario, with the same network scale and traffic rules configured, P4 CV generates only 0.06‰ of bandwidth overhead and reduces the verification time by 42% compared with the existing scheme. [ABSTRACT FROM AUTHOR]

With the high penetration of renewable energy, new challenges, such as power fluctuation suppression and inertial support capability, have arisen in the power sector. Battery energy storage systems play an essential role in renewable energy integration. In this paper, a distributed virtual synchronous generator (VSG) control method for a battery energy storage system (BESS) with a cascaded H-bridge converter in a grid-connected mode is proposed. The VSG is developed without communication dependence, and state-of-charge (SOC) balancing control is achieved using the distributed average algorithm. Owing to the low varying speed of SOC, the bandwidth of the distributed communication networks is extremely slow, which decreases the cost. Therefore, the proposed method can simultaneously provide inertial support and accurate SOC balancing. The stability is also proved using root locus analysis. Finally, simulations under different conditions are carried out to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper considered a wireless communication network with multiple UAV base stations and multiple users.In the network,due to the limited spectrum resource,the backhaul links of the UAV base stations and the data links of the users shared the same spectrum.In order to use the spectrum resource efficiently and improve the communication performance of the users,this paper jointly optimized the bandwidth and power of the backhaul and data links as well as the flight trajectory of the UAV base stations,to maximize the minimum average rate of all users.This joint optimization was subject to the UAVs’ mobility,the total spectrum bandwidth,and the total transmit power,and the involved joint optimization problem was non-convex,thus it was difficult to find the optimal solution.This paper proposed an efficient algorithm to obtain a high-quality suboptimal solution of it.Simulation results show that the minimum user rate achieved by the proposed joint optimization algorithm is significantly higher than that of the benchmark schemes. [ABSTRACT FROM AUTHOR]

In nonparametric models, numerous penalization methods using a nonparametric series estimator have been developed for model selection and estimation. However, a penalization has been poorly understood combined with kernel smoothing. This can be attributed to the intrinsic technical and computational difficulties, which leads to different treatments from the developments of the penalized series estimators. Kernel smoothing is a popular and useful nonparametric estimation method; thus it is desirable to establish theoretical and computational analyses for penalized kernel smoothing. In this paper, we develop a novel penalized kernel quantile regression that has nice theoretical and computational properties in varying coefficient models. We show that the proposed method consistently identifies the partially linear structure of the varying coefficient model even when the number of covariates is allowed to increase with a sample size. We develop an efficient algorithm using the alternating direction method of multipliers with a computational convergence guarantee. We derive the plug-in bandwidth selection using high-dimensional kernel regression theory and the penalty parameter is selected by the proposed Bayesian Information Criterion. Our developments require novel high-dimensional kernel regression and computational analyses. The various simulations and real data analyses conducted in this study demonstrate the effectiveness and numerically verify the proposed method. • Propose a method that identifies the partially linear structure of the varying coefficient model. • Develop an efficient algorithm using the proximal alternating direction method of multipliers with a convergence guarantee. • Derive the novel plug-in bandwidth selection using high-dimensional kernel theory. [ABSTRACT FROM AUTHOR]

Traditional data update synchronization tends to update the entire file directly at a time or selectively update local changes. Although the latter method saves part of the communication bandwidth, but every time the file changes, no matter how much change is immediately updated, increasing the communication load, these two methods are not very good to meet the real-time requirements of the industrial Internet. Aiming at this problem, this paper proposed an end-to-end cloud collaborative data synchronization scheme for industrial Internet. In this scheme, it judged the threshold by calculating the difference file. If the value was within the threshold, the changed data blocks were encoded and compressed and uploaded to the corresponding cloud storage node for decompression storage. Otherwise, relevant information would be temporarily stored in the edge layer. Compared with RS encoding and Rsync differential algorithm, it can be seen that the proposed scheme improves the transmission efficiency of updated data, and improves the security through coding compression, and the overall performance is better than other methods. [ABSTRACT FROM AUTHOR]

In heterogeneous wireless networks, random packet loss and high latency lead to conventional TCP variants performing unsatisfactorily in the case of competing communications. Especially on high-latency wireless links, conventional TCP variants are unable to estimate congestion degrees accurately for fine-grained congestion control because of the effects of random packet loss and delay oscillations. This paper proposes a TCP variant at the sender side to identify congestion degrees, namely TCP-WBQ, which quickly responses to the real congestion and effectively shields against random packet loss and oscillations of latency time. The proposed algorithm of congestion control firstly constructs a backlog-queue model based on the dynamics of the congestion window, and deduces the two bounds of the model which delimit oscillations of the backlog queue for non-congestion and random packet loss respectively. TCP-WBQ detects congestion degrees more accurately and thus implements the corresponding schemes of adjusting the congestion window, maintaining a tradeoff between high throughputs and congestion avoidance. The comprehensive simulations show that TCP-WBQ works efficiently in bandwidth utilization with single and multiple bottleneck scenarios, and achieves high performance and competitive fairness in heterogeneous wireless networks. [ABSTRACT FROM AUTHOR]

In this paper, we propose a variational Bayesian method for estimation of varying-coefficient model. Within the local likelihood framework, we develop variational updates for the approximated posterior and obtain variational lower bound. Mean-field assumption naturally simplifies the estimation procedure, and overcomes the computational burden of traditional Bayesian methods in nonparametric setting. We also propose a Metropolis-Hastings algorithm to select the bandwidth. We conduct simulation study to demonstrate proposed procedure, and apply the proposed estimation method in the analysis of stock return data. [ABSTRACT FROM AUTHOR]

In order to minimize the average completion time of a series of geo-distributed data analytical jobs, this paper first introduced online random scheduling algorithm ranT A. ranT A actually showed the preference on the task assignment under the consideration of both computing capacity of edges and the network bandwidth. Furthermore, in order to avoid overloading those edges with low computing capacities, this paper proposed data redistribution mechanism ranT A-data based on ranT A by redistributing some data to the central data center along with the tasks. The result of ranT A -data could be proved concentrated on its optimum with high probability. Extensive simulations show that ranTA-data improves nearly 30% performance compared with traditional algorithms. [ABSTRACT FROM AUTHOR]

The key idea of this paper is the usage of Handover (HO) control message to decrease connection dropping in accordance. Motivated by addressing challenging problems, developing an effective Multi-layer parallel handover optimization scheme is critical to enhance network performance in heterogeneous network environment. This paper proposes a cross-layer-based adaptive vertical handoff algorithm to reduce the handover latency and signaling overhead. The used mobility protocol manage multiple physical paths over heterogeneous networks. This architecture is mainly composed of three parts, (i) Collecting network conditions, (ii) signaling between entities, and (iii) adaptive algorithm based on network conditions. The cross-layer scheme provides the sender with prediction of the available bandwidth. Numerical results highlight the enhancement brought by the capability of the IS to support dynamic information. The proposed architecture can be deployed on any Internet protocol layer such as application layer, transport layer and network layer. Evaluation results demonstrate the achieved improvements over the reference schemes. [ABSTRACT FROM AUTHOR]

For the problem that the ICI self-cancellation algorithm leads to the underutilization of the UFMC system frequency band, this paper proposed an improved scheme that combines partial self-cancellation and raised cosine windows. This scheme specifically inserted the self-eliminating sub-carriers into the UFMC system' s transmitting terminal band boundary, and performed windowing in the time domain at the receiving end of the UFMC system to achieve the purpose of suppressing UFMC system interference and improving system band utilization. This paper conducted simulation experiments of the algorithm on MATLAB platform. There were four self-cancelled sub-carriers on both sides of the sub-band, the system carrier-to-interference ratio increased compared with the self-cancellation algorithm, and the spectrum utilization of the system also increased by 10%. The simulation results show that the proposed algorithm can effectively suppress ICI, improve the system' s anti-jamming performance, and improve the system bandwidth utilization. [ABSTRACT FROM AUTHOR]

In this paper, an evolutionary optimization procedure is presented to generate band-pass metasurface-based filters in terahertz regime. As a measure of novelty, pass-band, transition, and out-band characteristics are investigated separately, all of which result in different metasurfaces for filtering applications. The presented approach is defined based on random hill climbing algorithm, regarding the established link between Matlab and HFSS software. A metasurface-based filter with specific properties is considered as the main problem to be solved by the optimization method. Moreover, the fuzzy theory, mean square method, and weighting coefficient procedure are considered to define an efficient fitness function evaluation approach. Also, a step-by-step procedure is used to generate desired structures with a great note of efficiency. The final generated structure has magnificent characteristics including sharp transitions together with transmittance around 0.68 and less than 0.04 at pass-band and out-band regions, respectively. Also, the generated metasurface benefits from wide bandwidth (65%) and great compactness compared to other previous works. [ABSTRACT FROM AUTHOR]

Highlights • The mobility of nodes in depth is utilized to improve tracking performance. • A complete tracking scheme including sensor selection and depth adjustment. • The method has the superiority in tracking accuracy and computation efficiency. • The observation model with additive and multiplicative noise is considered. Abstract The effective node depth adjustment of distance-measuring sensors for target tracking in underwater wireless sensor networks (UWSNs) is investigated in this paper. Due to the limited energy and bandwidth in UWSNs, there is only a part of sensors participating in the tracking task at each time step. In this paper, the mobility of sensor nodes in depth is utilized to improve the tracking accuracy on the premise of employing the same number of sensors. Firstly, the relationship between the depth of sensor nodes and direct conditional posterior Cramer-Rao lower bounds (D-CPCRLB) is derived and taken as the performance bound for tracking accuracy. Secondly, the problem of optimal depth adjustment with the constraint on total moving distance is converted into an optimization problem and the objective function of which is D-CPCRLB. Finally, by combining the optimal depth adjustment and sensor selection algorithm, the best task sensors with optimal depth adjustment are selected for the purpose of the energy-efficiency. In particular, according to the sensor combination classification, the optimization problem is disassembled into that with and without an analytical solution, which improves computation efficiency. The simulation results illustrate the performance of the proposed scheme in improving the tracking accuracy and energy consumption. [ABSTRACT FROM AUTHOR]

In this paper, an adaptive nonlinear differential limiter (ANDL) is proposed to efficiently alleviate the impact of impulsive noise (IN) in a communication system. Unlike existing nonlinear methods, the ANDL is implemented in the analog domain where the broader acquisition bandwidth makes outliers more detectable and consequently it is easier to remove them. While the proposed ANDL behaves like a linear filter when there is no outlier, it exhibits intermittent nonlinearity in response to IN. Therefore, the structure of the matched filter in the receiver is modified to compensate the filtering effect of the ANDL in the linear regime. In this paper, we quantify the performance of the ANDL by deriving a closed-form analytical bound for the average signal-to-noise ratio at the output of the filter. The calculation is based on the idea that the ANDL can be perceived as a time-variant linear filter whose bandwidth is modified based on the intensity of the IN. In addition, by linearizing the filter time parameter variations, we treat the ANDL as a set of linear filters where the exact operating filter at a given time depends upon the magnitude of the outliers. The theoretical average bit error rate is validated through simulations and the performance gains relative to classical methods such as blanking and clipping are quantified. [ABSTRACT FROM AUTHOR]

In this paper, a novel demapper for 2-D non-uniform constellations (2D-NUCs) is proposed, exploiting the characteristics of these constellations. It represents the combination of two underlying demapping techniques targeting the ATSC 3.0 compliant OFDM transceiver. On the one hand, for low code rates, we define a metric to perform condensed demapping. On the other hand, for high code rates, adaptive sub-region demapping is proposed. In this paper, a combination of both demapping methods is designed showing comparable performance to the classical ML demapper. The gap does not exceed 0.1 dB for all code rates of the ATSC 3.0 standard. Higher complexity reduction, from 79.2% to 95.4%, than state of art 2D-NUC demappers is obtained for 2D-256NUCs. These results are validated for ideal and non-ideal channel state information over additive white noise Gaussian and Rayleigh independently and identically distributed channels. Results are extended to 2D-1kNUCs and 2D-4kNUCs showing demapping complexity reduction from 96% to 99.7% with a negligible impact on performance. [ABSTRACT FROM AUTHOR]

NavIC (Navigation with Indian Constellation) constellation consists of four geosynchronous and three geostationary satellites and it is developed by ISRO, India. It provides position, velocity and timing services. Doppler Collision (DC) is a phenomenon where tracking errors are introduced in the measurements due to cross-correlation between the satellites. If relative doppler between satellites is less than the code loop bandwidth, then DC occurs. In this paper, to analyze DC impact on NavIC, the Doppler shift of each GEO satellite is calculated, the most effected GEO satellite pair is identified. In high dynamic applications like missile launches the effect of DC is very significant. In order to investigate DC in high dynamic conditions a simulation of trajectory path of the receiver is considered. For the precise position estimation, the contribution of DC error will be high, so it needs to be minimized. An efficient algorithm is developed to mitigate the DC using narrow correlator design of the receiver. Using the proposed algorithm, the DC duration for 1C-1G satellite pair has been reduced from 50min 21sec to 2sec in static conditions. Whereas in dynamic conditions from 4h20min 28sec to 5sec with DLL bandwidth of 4Hz and 0.1 chip spacing of receiver design. [ABSTRACT FROM AUTHOR]

Wireless network communication has developed rapidly in recent years, especially in the field of Internet of vehicles (IoV). However, due to the limitations of traditional network architecture, resource scheduling in wireless network environment is still facing great challenges. We focus on the urgent need of users for bandwidth resources in the IoV scenario under virtual network environment. This paper proposes a bandwidth aware multi domain virtual network embedding (BA-VNE) algorithm. The algorithm is mainly aimed at the problem that users need a lot of bandwidth in wireless communication mode, and solves the problem of bandwidth resource allocation from the perspective of virtual network embedding (VNE). In order to improve the performance of the algorithm, we introduce particle swarm optimization (PSO) algorithm to optimize the performance of the algorithm. In order to verify the effectiveness of the algorithm, we have carried out simulation experiments from link bandwidth, mapping cost and virtual network request (VNR) acceptance rate. The final results show that the proposed algorithm is better than other representative algorithms in the above indicators. [ABSTRACT FROM AUTHOR]

Mode swapping in characteristic mode analysis (CMA) affects consistent interpretation of the modal data. Mode tracking based on the eigenvector correlation can effectively determine the correct ordering of modes at each sampling frequency. However, there has been a lack of corresponding preprocessing for this mode‐tracking algorithm. For example, the applicable frequency band cannot be determined in advance. In this paper, cosine similarity is used to calculate the correlation between modes of adjacent frequencies. It is then proposed that the 3/2 proportional relationship between the maximum size of the structure and the minimum operating wavelength can be used to choose the reliable operating band range of the algorithm. Meanwhile, it is recommended that the meshing side length should be less than one‐tenth of a wavelength, and the adjacent sampling frequency interval should be less than the relative bandwidth of 10%. Through this preprocessing, correlation‐based algorithms can efficiently implement mode tracking for open conductors. [ABSTRACT FROM AUTHOR]

In this paper, we report the implementation and measured performance of our extreme-scale whole planetary ring simulation code on Sunway TaihuLight and two PEZY-SC2 systems: Shoubu System B and Gyoukou. The numerical algorithm is the parallel Barnes-Hut tree algorithm, which has been used in many large-scale astrophysical particle-based simulations. Our implementation is based on our FDPS framework. However, the extremely large numbers of cores of the systems used (10 M on TaihuLight and 16 M on Gyoukou) and their relatively poor memory and network bandwidth pose new challenges. We describe the new algorithms introduced to achieve high efficiency on machines with low memory bandwidth. The measured performance is 47.9, 10.6 PF, and 1.01PF on TaihuLight, Gyoukou and Shoubu System B (efficiency 40%, 23.5% and 35.5%). The current code is developed for the simulation of planetary rings, but most of the new algorithms are useful for other simulations, and are now available in the FDPS framework. [ABSTRACT FROM AUTHOR]

An upcoming capable technology named as Next generation Ethernet passive optical network (NG-EPON); to handle enormous bandwidth and effective distribution requirements for prospective Internet based services. Standardization procedures for NG-EPON are in progress. Transmission of data traffic from Optical Network Units (ONUs) towards Optical Line Terminal (OLT) in NG-EPON is carried out through four wavelengths each operating at a data rate of 25Gbps. Dynamic wavelength and bandwidth allocation (DWBA) algorithms are needed for the efficient arbitration of the bandwidth resources between the subscribers. In this paper, we have proposed two different DWBA algorithms for NG-EPON; DWBA-I and DWBA-II. DWBA-I is a Quality-of-Service based algorithm that has been designed to manage the different types of data traffic in NG-EPON. DWBA-I performs better than the different existing DBA algorithms in terms of packet delay, completion time and packet drop ratio. DWBA-II is an algorithm designed to meet the system requirement specifications of NG-EPON and handle traffic requirements of subscribers in a cost effective manner. DWBA-II algorithm is comparatively analyzed and evaluated with First-Fit-DWBA and Modified-IPACT algorithms. Performance of DWBA-II is better on the basis of average delay, grant utilization, completion time and packets drop ratio. Performance of DWBA-I and DWBA-II has been evaluated through simulation results. [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 PUBLISHER]

This paper is concerned with the state estimation problem for a class of discrete-time singularly perturbed systems with distributed time-delays. During the data transmission through a network channel of limited bandwidth, for the sake of collision avoidance and energy saving, a dynamic event-triggered scheme is employed to schedule the data communication from the sensors to the designed estimator. First, for a given singular perturbation parameter (SPP), by constructing a novel Lyapunov–Krasovskii SPP-dependent functional, sufficient conditions are obtained to guarantee the exponentially mean-square ultimate boundedness of the error dynamics of the state estimation. Furthermore, in the case that the SPP does not exceed a predefined upper bound, a design algorithm is developed for the desired state estimator ensuring that the error dynamics is exponentially mean-square ultimately bounded. In this case, by solving certain matrix inequalities, the estimator gain is characterized without needing to know the exact SPP (as long as it stays below the given upper bound). Moreover, the ultimate bound of the error dynamics is estimated. Finally, simulation results are given to confirm the validity and advantages of the proposed design scheme of the state estimator. [ABSTRACT FROM AUTHOR]

In this paper, we consider a mission-critical control system, where a dynamic plant is monitored by a mobile device (MD), and the monitored signal is transmitted to a remote controller via heterogeneous cellular and Wi-Fi networks. We propose an optimal control-aware machine-to-machine (M2M) transmission strategy for mission-critical control applications, in which control performance is measured by remote estimation error and system stability while limited by bandwidth cost. Specifically, the problem of minimizing estimation error, subject to the constraints of cellular usage costs and system stability, is formulated as an infinite-horizon constrained Markov decision process (CMDP), where the MD has options to transmit through Wi-Fi or cellular, or to stay idle. We solve the problem by utilizing the Lagrange multiplier approach, and prove that the optimal strategy is a randomized mixture of two threshold structure strategies. Furthermore, to estimate the structured optimal strategy, we present an algorithm called simultaneous perturbation stochastic approximation (SPSA), in which the complexity is $O(|\mathcal {A}|)$ lower than a non-structured one with $|\mathcal {A}|$ being the number of the actions. [ABSTRACT FROM AUTHOR]

Next generation ethernet passive optical network (NG-EPON) is a promising technology to cater huge bandwidth and efficient distribution demands of the future Internet services. IEEE working group has been doing efforts for the standardization of NG-EPON. Four wavelength channels of 25Gbps each are supported by NG-EPON for the transmission of optical network unit (ONU) traffic towards optical line terminal (OLT). Dynamic wavelength and bandwidth allocation (DWBA) algorithms are needed for the efficient arbitration of bandwidth resources between subscribers. In this paper, we have proposed a DWBA algorithm named as efficient bandwidth management algorithm (EBMA) for NG-EPON. EBMA has been designed to manage the diversified traffic requirements of different ONUs. EBMA performance is evaluated comparatively with modified IPACT (M-IPACT) and first fit (FF-DWBA) algorithms. EBMA for NG-EPON proves to be better on the basis of packet delay, packet drop ratio and grant utilization. Simulation results showed improved performance of EBMA in comparison with M-IPACT and FF-DWBA algorithms. [ABSTRACT FROM AUTHOR]

In order to solve the problem of network service interruption caused by random failure of the substrate physical node in the network function virtualization environment, this paper proposed a service function chain deployment method with network service reliability and delay constraint to ensure the reliability of network service. Firstly, the method adopted a backup mechanism for resource sharing of adjacent virtual network function backup instances and a single-path and multi-path hybrid routing strategy. Then, it established a mixed integer linear programming model for the service chain reliability deployment problem under delay constraints and designed a service function chain deployment algorithm based on K shortest path extension. The simulation results show that the proposed method reduces the node and bandwidth resource overhead and improves the network service request acceptance rate compared with the existing methods. [ABSTRACT FROM AUTHOR]

In order to bridge the semantic gap and improve the performance, different scheduling strategies should be applied to virtual CPUs( vCPU ) which execute different types of tasks. Thus, the scheduling of vCPU should be optimized . This paper proposed the STC (virtual CPU scheduler based on task classification), a scheduling model of virtual CPUs which was based on task classification. In STC, vCPUs and physical CPUs were classified into two types, that were short vC PU and long vCPU, which were accordingly mapped to short CPU and long CPU . Moreover, STC built classifier based on machine learning, and tasks were classified into I/0-bound ones and CPU-bound ones, which were allocated to short vCPUs and long vC PUs. STC improved the 110 responding speed without influencing the computing performance. Compared with default CFS algorithm, the experiment results show that STC has achieved time delay 18% decrease, bandwidth 17% - 25% improvement, and ensures the fairness of the whole system. [ABSTRACT FROM AUTHOR]

In order to reduce the effect of the packet disorder on the transmission performance at the receiver in the CMT system, this paper developed a new data allocation scheme in the transmission terminal. The scheme predicted the packet forward transmission delay based on the bandwidth, round trip transmission delay and congestion window of the path, and used it as a measure factor of the path transmission priority in the CMT system. The sender assigned packets in the queue for each path based on the path transmission priority and sender cache status, which did not cause the receiver to be out of order. Simulation results show that compared with the round-robin and ATLB algorithm, the proposed data allocation scheme can reduce the number of disorder data apparently. [ABSTRACT FROM AUTHOR]

In order to improve the bandwidth utilization, this paper researched on optimization of the static segment of FlexRay based on slot multiplexing. It encoded the transmitted signal into a message frame, and transformed the problem into a constrained packing problem. It encapsulated the signal with multiple relationships into a message frame and solved it by BFD algorithm. Based on this, it put forward a method that could maximize the bandwidth and minimize the number of frame ID. Finally, the verification object was the FlexRay chassis synthesis control and safety system. Experimentally, the proposed algorithm increases the bandwidth utilization by 18.7%, reduces the proportion of FID in each communication cycle by 90.47%, and increases the static time slot utilization in the cycle by 41.52%. [ABSTRACT FROM AUTHOR]

The broadcast congested clique model (BClique) is a message-passing model of distributed computation where n nodes communicate with each other in synchronous rounds. First, in this paper we prove that there is a one-round, deterministic algorithm that reconstructs the input graph G if the graph is d-degenerate, and rejects otherwise, using bandwidth b =scrO (dcdot log n). Then, we introduce a new parameter to the model. We study the situation where the nodes, initially, instead of knowing their immediate neighbors, know their neighborhood up to a fixed radius r. In this new framework, denoted BClique[r], we study the problem of detecting, in G, an induced cycle of length at most k (Cycleleq k) and the problem of detecting an induced cycle of length at least k+1 (Cycle>k). We give upper and lower bounds. We show that if each node is allowed to see up to distance r =lfloor k/2rfloor + 1, then a polylogarithmic bandwidth is sufficient for solving Cycle>k with only two rounds. Nevertheless, if nodes were allowed to see up to distance r =lfloor k/3rfloor, then any one-round algorithm that solves Cycle>k needs the bandwidth b to be at leastOmega (n/log n). We also show the existence of a one-round, deterministic BClique algorithm that solves Cycleleq k with bandwitdh b =scrO (n1/lfloor k/2rfloorcdot log n). On the negative side, we prove that, ifepsilon leq 1/3 and 0 < r leq k/4, then any epsilon -error, R-round, b-bandwidth algorithm in the BClique[r] model that solves problem Cycleleq k satisfies R cdot b = Omega (n1/lfloor k/2rfloor). [ABSTRACT FROM AUTHOR]

• The effective load balancing is achieved by genetic algorithm-assisted offline/online weight-updating strategies. • The fragmentation suppression is realized with less than half of the previous complexity and no transmission disruption. • More than 80% of spectrum fragments are suppressed due to the flexible-grouping mechanism. • The service blocking probability is kept as zero when the traffic load is lower than 300 Erlang in NSFNET and USNET. • The quality of service (QoS) of transmission requests with high priority is greatly enhanced. With the significant increasing of network bandwidth demands, the development of spatial division multiplexing elastic optical networks (SDM-EONs) attracts much attention from both academic and industry. Due to the continuity and contiguity constraints in spectrum allocation, the generation of spectrum fragments causes serious impacts on the performance of SDM-EONs. Meanwhile, the load imbalance is a main negative factor of SDM-EONs' performance. In this paper, we focus on the issues of spectrum fragmentation and load imbalance. Specifically, we first design a genetic algorithm-assisted offline weight modulation and an online dynamic weight adjustment strategy to realize load-balanced adaptive routing. Then, we introduce a flexible-grouping mechanism to suppress the generation of spectrum fragments. Finally, we propose a weight-updating and flexible-grouping routing, spectrum and core assignment (WUFG RSCA) algorithm based on mixed super-channel for SDM-EONs. Our simulation results confirm that the proposed algorithm obtains effective reduction in spectrum fragments and network service blocking probability. In addition, the results prove that the WUFG RSCA algorithm can improve the spectrum resource utilization and enhance the quality of service for transmission requests with high priority. [ABSTRACT FROM AUTHOR]

This paper presents the VLSI architecture and hardware implementation of a highly efficient deblocking filter (DBF) for High Efficiency Video Coding systems. In order to reduce the number of data accesses and thus to enhance the timing efficiency, novel data structures and memory access schemes for image pixels are proposed. Furthermore, a novel edge-fetching order is presented to strike a balance between the processing throughput and complexity. Based on the proposed structure and access pattern, a six-stage pipelined two-line DBF engine with low-latency data access sequence is designed, aiming to achieve high processing throughput while at the same time maintaining low complexity. The detailed storage structure and data access scheme are illustrated and VLSI architecture for the DBF engine is depicted in this paper. In addition, the proposed DBF is implemented using TSMC 90-nm standard cell library. The experimental results based on postlayout estimations show that the proposed design can achieve 60 frames/s for a frame resolution of $4096\times 2048$ pixels (ultra high definition resolution) assuming an operating frequency of 100 MHz. Moreover, this design occupies an area complexity of 466.5 kGE with a power consumption of 26.26 mW. In comparison with prior designs targeting similar system specification and throughput, the proposed design results in a significantly reduced area complexity. [ABSTRACT FROM PUBLISHER]

This paper presents predictive current-mode control for a single-phase high-frequency transformer-isolated dual-active bridge dc-to-dc converter. The predictive control algorithm increases the bandwidth of the current loop of the converter which enables tracking of the current reference within one switching cycle. The paper further demonstrates that the application of the predictive control algorithm can remove transient dc offset from the current in high-frequency isolation transformer within one switching cycle. Direct control of the converter current protects the transformer from saturation even at transient conditions. The control algorithm has been implemented on an experimental setup and transient tests have been performed to validate controller performance. Since the predictive control algorithm is dependent on the measured value of the leakage inductance of the transformer, a compensator has been implemented to improve the parameter insensitivity of the proposed controller. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a compressive random access (CRA) scheme using multiple resource blocks (RBs) to support massive connections for machine type communications. The proposed CRA scheme is scalable. As a result, if the number of devices increases, more RBs can be added to support them. Thanks to multiple RBs, we can employ fast retrial between RBs for re-transmissions of collided packets, which can result in short access delay. For stable CRA with fast retrial, we derive conditions (with a rate control scheme), and analyze the steady-state performance to find the throughput and delay. Through analysis and simulation results, we can see that the proposed scheme can perform better than conventional multichannel ALOHA and enjoy a tradeoff between the performance and complexity in terms of the number of RBs. [ABSTRACT FROM AUTHOR]

In cellular heterogeneous networks (HetNets), a number of distributed base stations cooperatively provide services to multiple mobile users. This paper addresses joint base-station activation and coordinated beamforming design for downlink transmission in HetNets. To this end, a mixed integer program is formulated to optimize the total power consumption of a HetNet. A novel approach based on Benders’ decomposition is then put forth to obtain the optimal solution for the problem of interest with guaranteed convergence. Building on our new formulation, a dual-subgradient algorithm is also proposed to find an approximate solution in polynomial time. The proposed approaches can be generalized to more general setups, including robust beamforming designs under channel uncertainty, and coordinated beamforming for multi-cell scenarios. [ABSTRACT FROM AUTHOR]

A $K$ -tier heterogeneous downlink millimeter wave (mmWave) cellular network with user-centric small cell deployments is studied in this paper. In particular, we consider a heterogeneous network model with user equipments (UEs) being distributed according to a Poisson cluster process (PCP). Distinguishing features of mmWave communications including directional beamforming and a sophisticated path loss model incorporating both line-of-sight and non-line-of-sight transmissions, are taken into account. Initially, we determine general expressions for the association probabilities of different tier BSs. Using tools from stochastic geometry, we then characterize the Laplace transform of the interference and derive a general expression for the signal-to-interference-plus-noise ratio coverage probability. While these expressions are applicable to any PCP, we later specialize the results to two popular PCPs, namely, first, Thomas cluster process, where the UEs are clustered around the base stations (BSs) according to a Gaussian distribution, and second, Matérn cluster process, where the UEs are scattered according to a uniform distribution. Subsequently, upper and lower bounds for the coverage probability are provided. Special cases are also addressed, providing the insight that when the cluster size grows without bound, our PCP-based model specializes to a Poisson point process-based model. Area spectral efficiency is investigated as well. Moreover, we have discussed extensions to cases in which more practical antenna gain patterns are taken into account and also the shadowing is considered. Via numerical and simulation results, we explore the effects of the beamwidth of the main lobe, the main lobe directivity gain, the biasing factor and the transmit power of the small-cell BSs to get insight on the performance in practical scenarios. Performance in dense networks is also analyzed numerically. [ABSTRACT FROM AUTHOR]

In this paper, spatial modulation (SM) is introduced to layered division multiplexing (LDM) systems for enlarging the spectral efficiency (SE) over broadcasting transmission. First, the SM aided LDM (SM-LDM) system is proposed, in which different layered services utilize SM for terrestrial broadcasting transmission with different power levels. Then a SE analysis framework for SM-LDM systems is proposed, which is suitable for the SM-LDM systems with linear combining. Moreover, the closed-form SE lower bound of SM-LDM systems with maximum ratio combining (MRC) is derived, which is based on this framework. Since the theoretical SE analysis of single transmit antenna (TA) LDM systems with MRC and spatial multiplexing (SMX) aided LDM systems with MRC lacks a closed-form expression, the closed-form SE is also derived for these systems. Monte Carlo simulations are provided to verify the tightness of our proposed SE lower bound. Furthermore, it can be shown via simulations that our proposed SM-LDM systems always have a better SE performance than single-TA LDM systems, which can even outperform the SE of SMX aided LDM (SMX-LDM) systems. [ABSTRACT FROM AUTHOR]

Band selection is an effective approach to mitigate the “Hughes phenomenon” of hyperspectral image (HSI) classification. Recently, sparse representation (SR) theory has been successfully introduced to HSI band selection, and many SR-based methods have been developed and shown great potential and superiority. However, due to the inherent limitations of the SR scheme, i.e., individually representing each band with only a few other bands from the same subspace, the SR-based methods cannot effectively capture the global structures of the data, which limit the band selection performance. In this paper, to overcome this obstacle, the novel Laplacian-regularized low-rank subspace clustering (LLRSC) algorithm is proposed for HSI band selection. On the one hand, the low-rank subspace clustering model is introduced to capture the global structure information for the learned representation coefficient matrix and deal with the HSI band selection task in the clustering framework. On the other hand, considering the high correlation between adjacent bands, 1-D Laplacian regularization is utilized to incorporate the neighboring band information and further reduce the representation bias. Lastly, an eigenvalue analysis algorithm based on band mutation information is utilized to estimate the appropriate size of the band subset. The experimental results indicate that the proposed LLRSC algorithm outperforms the other state-of-the-art methods and achieves a very competitive band selection performance for HSIs. [ABSTRACT FROM AUTHOR]

In this paper, we address a practical but adverse problem that successive interference cancellation (SIC) is imperfect in a massive non-orthogonal multiple access (NOMA) system. The benefits of a multiple-antenna base station are exploited to support massive access through user clustering in the spatial domain and alleviate the impact of imperfect SIC. In particular, transmit beams and powers are jointly optimized to mitigate the intra-cluster and inter-cluster interference, so as to improve the overall performance in the presence of imperfect SIC. Specifically, we design the joint optimization algorithms from the perspectives of maximizing the weighted sum rate and minimizing the total power consumption, respectively. Moreover, in order to reduce the computational complexity, we design the massive NOMA algorithms with zero-forcing beamforming fixedly. The impacts of imperfect SIC on the design of massive NOMA algorithms are revealed, and it is found that the proposed algorithms are still applicable even if SIC is perfect. Finally, simulations results validate the theoretical claims and show that obvious performance gain can be obtained over the baseline algorithms. [ABSTRACT FROM AUTHOR]

Abstract In recent years, edge computing becomes an increasingly popular alternative. Edge computing allows the computation is implemented in the edge of network, in which the data are stored in the edge of network, to improve the efficiency of data process. However, some resource management techniques in cloud or distributed system cannot better suit for edge computing. Therefore, there exist some challenges on the performance improvement of edge computing. In this paper, the main purpose is to combine the optimal placement of data blocks and the optimal scheduling of tasks to reduce the computation delay and response time for the submitted tasks and improve user experience in edge computing. In optimal placement of data blocks, the value of the data blocks considers not only the popularity of the data blocks, but the data storage capacity and replacement ratios of an edge server that will store those data blocks. Furthermore, the replacement cost for placed data blocks is regarded as an important component of data block placement. This optimal placement scheme can avoid replacing the placed data blocks repeatedly so that the bandwidth overhead is reduced. In optimal scheduling of tasks, the containers are taken as the lightweight resource unit for the services for user requests to make full use of data storage in edge servers and improve the services performance of edge servers. Finally, extensive experiments are conducted to value the performance of task scheduling strategy. The results show that the performance of the proposed task scheduling algorithm is better than that of the compared algorithms. Highlights • The placement of data blocks and the scheduling of tasks are studied in edge computing. • The value of data blocks considers the popularity and replacement ratios. • The replacement cost for placed data blocks is considered. • The experiments are conducted to value the performance of proposed strategy. [ABSTRACT FROM AUTHOR]

Abstract Conventional medical image watermarking techniques focus on improving invisibility and robustness of the watermarking mechanism to prevent medical disputes. This paper proposes a medical image watermarking algorithm based on the significant difference of cellular automata transform (CAT) for copyright protection. The medical image is firstly subsampled into four subimages, and two images are randomly chosen to obtain two low-frequency bandwidths using CAT. Coefficients within a low-frequency bandwidth are important information in an image. Hence, the difference between two low-frequency bandwidths is used as an important feature in the medical image. From these important features, watermarks and cover images can be used to generate an ownership share image (OSI) used for verifying the medical image. Besides appearing like cover images, the OSI will also be able to register with a third party. When a suspected medical image requires verification, the important features from the suspected medical image are first extracted. The master share image (MSI) can be generated from the important features from the suspected medical image. Lastly, the OSI and MSI can be combined to extract the watermark to verify the suspected medical image. The advantage of our proposed method is that the medical image does not require alteration to protect the copyright of the medical image. This means that while the image is protected, medical disputes will be unlikely and the appearance of the registered OSI will carry significant data to make management more convenient. Lastly, the proposed method has the features of having better security, invisibility, and robustness. Moreover, experimental results have demonstrated that our method results in good performance. Highlights • A robust lossless medical watermarking scheme for copyright protection is proposed. • The CAT coefficient is used to produce an OSI for verifying the medical image. • The appearance of OSI is meaningful information to promote its management. • Our scheme can keep the quality of the medical image for copyright protection. [ABSTRACT FROM AUTHOR]

In this paper, an adaptive synthesis using the particle swarm optimization (PSO) for implementations of resonator-coupled filters is proposed. The coupling matrix of in-band filtering response is achieved and optimized by the PSO-based synthesis. Meanwhile, the stopband coupling matrix of the filter is predicted based on the combination of extra resonant nodes representing stopband spurious and parasitic effect of input/output ports. In addition, an enhanced accurate prediction of filter performance is calculated by the proposed approach, considering the practical fabrication tolerance on filter design. To verify principles mentioned earlier, various resonator-coupled filters are implemented. The calculation, EM-simulation, and measurement of filters show good agreements in both passband and stopband. [ABSTRACT FROM AUTHOR]

This paper presents a macromodeling technique for modeling distributed circuits characterized by noisy frequency-domain data. The proposed method is based on an iterative Loewner matrix (LM) approach. Using the LM approximation of previous iterations, the singular values and orthonormal matrices of the Loewner pencil are made to be more accurate. This approach is shown to minimize the biasing effect of the noisy data due to the nonlinearity of the singular value decomposition operation, resulting in more accurate poles and residues. Numerical examples illustrate that for noisy frequency-domain data, the proposed algorithm creates more accurate macromodels when compared with the traditional LM approach. [ABSTRACT FROM AUTHOR]