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In this paper, we analyze a two-queue random time-limited Markov-modulated polling model. In the first part of the paper, we investigate the fluid version: fluid arrives at the two queues as two independent flows with deterministic rate. There is a single server that serves both queues at constant speeds. The server spends an exponentially distributed amount of time in each queue. After the completion of such a visit time to one queue, the server instantly switches to the other queue, i.e., there is no switch-over time. For this model, we first derive the Laplace–Stieltjes transform (LST) of the stationary marginal fluid content/workload at each queue. Subsequently, we derive a functional equation for the LST of the two-dimensional workload distribution that leads to a Riemann–Hilbert boundary value problem (BVP). After taking a heavy-traffic limit, and restricting ourselves to the symmetric case, the BVP simplifies and can be solved explicitly. In the second part of the paper, allowing for more general (Lévy) input processes and server switching policies, we investigate the transient process limit of the joint workload in heavy traffic. Again solving a BVP, we determine the stationary distribution of the limiting process. We show that, in the symmetric case, this distribution coincides with our earlier solution of the BVP, implying that in this case the two limits (stationarity and heavy traffic) commute.

The system considered in this paper operates with a feedback that is characterized by a gain and a desired final state (DFS), which is the main parameter of interest in the present study. The system is, however, subjected intermittently to stochastic inputs according to a Markov process. Since the system operates in two modes | under the feedback to the DFS and under a stochastic input|the Interacting Multiple Model (IMM) estimator is used. Two approaches are considered: (i) the DFS is a discrete-valued random variable | one of a finite number of possible states | with an a priori probability mass function (pmf), and (ii) the DFS is a continuous-valued random variable with an a priori probability density function (pdf). For Approach (i), we use a multiple IMM estimator (MIMM) that features one IMM for each one of the possible DFS. The a posteriori probability of the model for each IMM, i.e., of each DFS, will be computed based on the likelihood function (LF) of the corresponding IMM. For Approach (ii), we design a single IMM to handle the unknown DFS to be estimated (mode M1), and the random inputs (mode M2). Simulation results explore several scenarios and investigate the degree of observability of this stochastic problem.

We consider the optimal control of input-queued switches under a cost-weighted variant of MaxWeight scheduling, for which we establish theoretical properties that include showing the algorithm exhibits optimal heavy-traffic queue-length scaling. Our results are expected to be of theoretical interest more broadly than input-queued switches.

In this article, a coupled Two-relaxation-time Lattice Boltzmann-Volume penalization (TRT-LBM-VP) method is presented to simulate flows past obstacles. Two relaxation times are used in the collision operator, of which one is related to the fluid viscosity and the other one is related to the numerical stability and accuracy. The volume penalization method is introduced into the TRT-LBM by an external forcing term. In the procedure of the TRT-LBM-VP, the processes of interpolating velocities on the boundaries points and distributing the force density to the Eulerian points are unneeded. Performing the TRT-LBM-VP on a certain point, only the variables of this point are needed. As a consequence, the TRT-LBM-VP can be conducted parallelly. From the comparison between the result of the cylindrical Couette flow solved by the TRT-LBM-VP and that solved by the Single-relaxation-time LBM-VP (SRT-LBM-VP), the accuracy of the TRT-LBM-VP is higher than that of the SRT-LBM-VP. Flows past a single circular cylinder, a pair of cylinders in tandem and side-by-side arrangements, two counter-rotating cylinders and a NACA-0012 airfoil are chosen as numerical experiments to verify the present method further. Good agreements between the present results and those in the previous literatures are achieved.

The basic load balancing scenario involves a single dispatcher where tasks arrive that must immediately be forwarded to one of $N$ single-server queues. We discuss recent advances on scalable load balancing schemes which provide favorable delay performance when $N$ grows large, and yet only require minimal implementation overhead. Join-the-Shortest-Queue (JSQ) yields vanishing delays as $N$ grows large, as in a centralized queueing arrangement, but involves a prohibitive communication burden. In contrast, power-of-$d$ or JSQ($d$) schemes that assign an incoming task to a server with the shortest queue among $d$ servers selected uniformly at random require little communication, but lead to constant delays. In order to examine this fundamental trade-off between delay performance and implementation overhead, we consider JSQ($d(N)$) schemes where the diversity parameter $d(N)$ depends on $N$ and investigate what growth rate of $d(N)$ is required to asymptotically match the optimal JSQ performance on fluid and diffusion scale. Stochastic coupling techniques and stochastic-process limits play an instrumental role in establishing the asymptotic optimality. We demonstrate how this methodology carries over to infinite-server settings, finite buffers, multiple dispatchers, servers arranged on graph topologies, and token-based load balancing including the popular Join-the-Idle-Queue (JIQ) scheme. In this way we provide a broad overview of the many recent advances in the field. This survey extends the short review presented at ICM 2018 (arXiv:1712.08555)., To appear in SIAM Review. arXiv admin note: substantial text overlap with arXiv:1712.08555

We consider exponential single server queues with state-dependent arrival and service rates that evolve under influences of external environments. The transitions of the queues are influenced by the environment’s state and the movements of the environment depend on the status of the queues (bidirectional interaction). The environment is constructed in a way to encompass various models from the recent Operations Research literature, where a queue is coupled with an inventory or with reliability issues. With a Markovian joint queueing-environment process, we prove separability for a large class of such interactive systems; that is, the steady state distribution is of product form and explicitly given. The queue and the environment processes decouple asymptotically and in steady state. For nonseparable systems, we develop ergodicity and exponential ergodicity criteria via Lyapunov functions. By examples we explain principles for bounding departure rates of served customers (throughputs) of nonseparable systems by throughputs of related separable systems as upper and lower bound.

A numerical cloud model with Lagrangian particles coupled to an Eulerian flow is adapted for distributed memory systems. Eulerian and Lagrangian calculations can be done in parallel on CPUs and GPUs, respectively. The fraction of time when CPUs and GPUs work simultaneously is maximized at around 80 % for an optimal ratio of CPU and GPU workloads. The optimal ratio of workloads is different for different systems because it depends on the relation between computing performance of CPUs and GPUs. GPU workload can be adjusted by changing the number of Lagrangian particles, which is limited by device memory. Lagrangian computations scale with the number of nodes better than Eulerian computations because the former do not require collective communications. This means that the ratio of CPU and GPU computation times also depends on the number of nodes. Therefore, for a fixed number of Lagrangian particles, there is an optimal number of nodes, for which the time CPUs and GPUs work simultaneously is maximized. Scaling efficiency up to this optimal number of nodes is close to 100 %. Simulations that use both CPUs and GPUs take between 10 and 120 times less time and use between 10 to 60 times less energy than simulations run on CPUs only. Simulations with Lagrangian microphysics take up to 8 times longer to finish than simulations with Eulerian bulk microphysics, but the difference decreases as more nodes are used. The presented method of adaptation for computing clusters can be used in any numerical model with Lagrangian particles coupled to an Eulerian fluid flow.

In this paper, we develop two finite difference weighted essentially non-oscillatory (WENO) schemes with unequal-sized sub-stencils for solving the Degasperis-Procesi (DP) and $\mu$-Degasperis-Procesi ($\mu$DP) equations, which contain nonlinear high order derivatives, and possibly peakon solutions or shock waves. By introducing auxiliary variable(s), we rewrite the DP equation as a hyperbolic-elliptic system, and the \mdp equation as a first order system. Then we choose a linear finite difference scheme with suitable order of accuracy for the auxiliary variable(s), and two finite difference WENO schemes with unequal-sized sub-stencils for the primal variable. One WENO scheme uses one large stencil and several smaller stencils, and the other WENO scheme is based on the multi-resolution framework which uses a series of unequal-sized hierarchical central stencils. Comparing with the classical WENO scheme which uses several small stencils of the same size to make up a big stencil, both WENO schemes with unequal-sized sub-stencils are simple in the choice of the stencil and enjoy the freedom of arbitrary positive linear weights. Another advantage is that the final reconstructed polynomial on the target cell is a polynomial of the same degree as the polynomial over the big stencil, while the classical finite difference WENO reconstruction can only be obtained for specific points inside the target interval. Numerical tests are provided to demonstrate the high order accuracy and non-oscillatory properties of the proposed schemes.

Our primary objective in this article is to compare the spectral densities of some cyclostationary time series. By using the limiting distributions of the discrete Fourier transform, a novel approach is introduced to determine whether the spectral densities of some uncorrelated cyclostationary time series are the same or not. Also, the ability of the proposed technique is examined by employing simulated and real datasets.

We investigate fluid scaling of single server queueing systems under the shortest job first with aging (SJFA) scheduling policy. We use the measure-valued Skorokhod map to characterize the fluid limit for SJFA queues with a general aging rule and establish convergence results to the fluid limit. We treat in detail examples of linear and exponential aging.

In the mobile edge computing environments, Quality of Service (QoS) prediction plays a crucial role in web service recommendation. Because of distinct features of mobile edge computing, i.e., the mobility of users and incomplete historical QoS data, traditional QoS prediction approaches may obtain less accurate results in the mobile edge computing environments. In this paper, we treat the historical QoS values at different time slots as a temporal sequence of QoS matrices. By incorporating the compressed matrices extracted from QoS matrices through truncated Singular Value Decomposition (SVD) with the classical ARIMA model, we extend the ARIMA model to predict multiple QoS values simultaneously and efficiently. Experimental results show that our proposed approach outperforms the other state-of-the-art approaches in accuracy and efficiency.

Existing Orthogonal Frequency-Division Multiplexing (OFDM) variants based on cyclic prefix (CP) allow for efficient time synchronization, but suffer from lower power efficiency compared to zero-padded (ZP)-OFDM. Because of its power efficiency, ZP-OFDM is considered as an appealing solution for the emerging low-power wireless systems. However, in the absence of CP, time synchronization in ZP-OFDM is a challenging task. In this paper, the non-data-aided (NDA) maximum-likelihood (ML) time synchronization for ZP-OFDM is analytically derived. We show that the optimal NDA-ML synchronization algorithm offers a high lock-in probability and can be efficiently implemented using Monte Carlo sampling (MCS) technique in combination with golden-section search method in one dimension. To obtain the optimal NDA-ML time synchronization algorithm, we first derive a closed-form expression for the joint probability density function (PDF) of the received ZP-OFDM samples in frequency-selective fading channels. The derived expression is valid for doubly-selective fading channels with mobile users as well. The performance of the proposed synchronization algorithm is evaluated under various practical settings through simulation experiments. It is shown that the proposed optimal NDA-ML synchronization algorithm and its MCS implementation substantially outperforms existing NDA time synchronization algorithms in terms of lock-in probability and mean-squared error (MSE).

A high fidelity flow simulation for complex geometries for high Reynolds number (Re) flow is still very challenging, requiring a more powerful HPC system. However, the development of HPC with traditional CPU architecture suffers bottlenecks due to its high power consumption and technical difficulties. Heterogeneous architecture computation is raised to be a promising solution to the challenges of HPC development. GPU accelerating technology has been utilized in low order scheme CFD solvers on the structured grid and high order scheme solvers on unstructured meshes. The high-order finite difference methods on structured grids possess many advantages, e.g., high efficiency, robustness, and low storage. However, the strong dependence among points for a high-order finite difference scheme still limits its application on the GPU platform. In the present work, we propose a set of hardware-aware technology to optimize data transfer efficiency between CPU and GPU, as well as communication efficiency among GPUs. An in-house multi-block structured CFD solver with high order finite difference methods on curvilinear coordinates is ported onto the GPU platform and obtains satisfying performance with a speedup maximum of around 2000x over a single CPU core. This work provides an efficient solution to apply GPU computing in CFD simulation with specific high order finite difference methods on current GPU heterogeneous computers. The test shows that significant accelerating effects can be achieved for different GPUs.

Atmospheric mass density (AMD) plays a vital role in the drag calculation for space objects in low Earth orbit (LEO). Many empirical AMD models have been developed and used for orbit prediction and...

A moisture advection scheme is an essential module of a numerical weather/climate model representing the horizontal transport of water vapor. The Piecewise Rational Method (PRM) scalar advection scheme in the Global/Regional Assimilation and Prediction System (GRAPES) solves the moisture flux advection equation based on PRM. Computation of the scalar advection involves boundary exchange, and computation of higher bandwidth requirements is complicated and time-consuming in GRAPES. Recently, Graphics Processing Units (GPUs) have been widely used to solve scientific and engineering computing problems owing to advancements in GPU hardware and related programming models such as CUDA/OpenCL and Open Accelerator (OpenACC). Herein, we present an accelerated PRM scalar advection scheme with Message Passing Interface (MPI) and OpenACC to fully exploit GPUs' power over a cluster with multiple Central Processing Units (CPUs) and GPUs, together with optimization of various parameters such as minimizing data transfer, memory coalescing, exposing more parallelism, and overlapping computation with data transfers. Results show that about 3.5 times speedup is obtained for the entire model running at medium resolution with double precision when comparing the scheme's elapsed time on a node with two GPUs (NVIDIA P100) and two 16-core CPUs (Intel Gold 6142). Further, results obtained from experiments of a higher resolution model with multiple GPUs show excellent scalability.

In this paper, an offloading algorithm based on Markov Decision Process (MDP) is proposed to solve the multi-objective offloading decision problem in Mobile Edge Computing (MEC) system. The feature of the algorithm is that MDP is used to make offloading decision. The number of tasks in the task queue, the number of accessible edge clouds and Signal-Noise-Ratio (SNR) of the wireless channel are taken into account in the state space of the MDP model. The offloading delay and energy consumption are considered to define the value function of the MDP model, i.e. the objective function. To maximize the value function, Value Iteration Algorithm is used to obtain the optimal offloading policy. According to the policy, tasks of mobile terminals (MTs) are offloaded to the edge cloud or central cloud, or executed locally. The simulation results show that the proposed algorithm can effectively reduce the offloading delay and energy consumption.

Edge infrastructures, including edge computing servers, are increasingly powered by renewable energy and smart grid combined. Two-way energy trading allows the surplus or shortfall of renewable energy to be traded between a server and the smart grid, but is non-trivial due to randomly varying computation demands and renewables. This paper proposes a new online policy, namely, distributed online resource allocation and load management (DORL), which enables such an edge server and its serving devices to minimize their energy cost and energy consumption, respectively, in a fully distributed manner. The key idea is that we employ the stochastic dual-subgradient method to interpret the battery of the server as a virtual queue. Based on the virtual queue and task queues, the CPU frequencies of the devices and the edge server, the offloading transmit rates of the devices (to the server) and the energy trading decisions of the server (with the smart grid) are decoupled over time and among devices, and optimized on an ongoing basis. Furthermore, we prove that the DORL yields a feasible and asymptotically optimal solution with a cost-backlog tradeoff of [\eta, 1\eta]. Simulations show that the DORL reduces the system cost by nearly 50%, as compared to existing benchmarks.

In this brief, a new discrete-time implementation is proposed for the super-twisting control with a semi-implicit Euler method. In contrast to the conventional realization methods, the proposed implementation scheme exploits two signum functions in the super-twisting algorithm (STA) such that the numerical chattering is totally avoided and the control precision is enhanced in terms of smallest control errors in the steady state. It has an advantage that the control accuracy is insensitive to the gain overestimation of STA, which benefits the gain tuning of the STA in practice. These superiorities of the proposed scheme are demonstrated through simulations and comparisons with other state of the art relevant to STA realization methods.

Power packet dispatching system has been proposed for smart power management in the form of discretized packet. In this paper, we discuss the routing optimization of power packets on the network of power routers. We propose a cost metric for the power packet delivery by circuit analysis of the router network. Using the metric, we formulate the optimization problem as a general shortest path problem from a source node to a load node. The result of numerical simulations shows that the proposed algorithm can allocate distributed power sources to load demands and identify the optimal path for the power delivery., This paper was submitted to Nonlinear Theory and Its Applications, IEICE on May 21, 2021

This article presents Maximum Visibility Approach (MVA), a new time series forecasting method based on the Complex Network theory. MVA initially maps time series data into a complex network using the visibility graph method. Then, based on the similarity measures between the nodes in the network, MVA calculates the one-step-ahead forecasts. MVA does not use all past terms in the forecasting process, but only the most significant observations, which are indicated as a result of the autocorrelation function. This method was applied to five different groups of data, most of them showing trend characteristics, seasonal variations and/or non-stationary behavior. We calculated error measures to evaluate the performance of MVA. The results of statistical tests and error measures revealed that MVA has a good performance compared to the accuracy obtained by the benchmarks considered in this work. In all cases, MVA surpassed other forecasting methods in Literature, which confirms that this work will contribute to the field of time series forecasting not only in the theoretical aspect, but also in practice.

The footprint noise is a type of coherent noise that arises from the acquisition geometry. The footprint noise is commonly seen in 3-D seismic volumes and greatly affects the amplitude-based processing and interpretation steps in the seismic exploration workflow. Thus, removal of the footprint noise is necessary for warranting a reliable interpretation output of seismic data processing. However, because footprint noise is usually weak and also spatially coherent, it is inevitable to cause damages to useful signals during its removal steps. Here, we propose a dictionary learning (DL)-based method to effectively remove the footprint noise. We design an algorithm framework to effectively learn the dictionary atoms of the signal waveforms and separate the features of the footprint noise from the learned atoms. Considering the special features of the footprint noise in the dictionary atoms, we propose a statistics-guided way to separate the dictionary atoms into footprint-affected and footprint-free atoms. Then, the footprint-affected atoms are processed via a 2-D median filtering step. The combination between the untouched footprint-free atoms and filtered footprint-affected atoms result in a better dictionary of the signal waveforms and the footprint atoms. We use residual DL to encode the input data by a linear combination of signal atoms and footprint atoms. Removal of footprint atoms and their corresponding sparse coefficients leads to a successful footprint removal. We use both 3-D synthetic and field data examples to demonstrate the effectiveness of the proposed method.

In a wireless communication system, the transmitted signal is exposed to various surfaces where it bounces and results in several delayed versions of the same signal at the receiver end. The delayed signals are in the form of electromagnetic waves that are diffracted and reflected from the various object surfaces. These result in co-channel interferences for wireless systems. MIMO has proven to be a striking solution for the new generation of wireless systems. MIMO-OFDM system with QPSK modulation is considered as the wireless system for studying the performance of interference cancellation techniques. The BER performance is studied in channels such as Rayleigh and Rician Fading Channels. The effects of interference are reduced to a certain extent by the inclusion of CDMA (spread spectrum technique) as Technique 1. The effects of interference on this system have been further reduced using the LMS filter as Technique 2. Hence, to show better performance in MIMO-OFDM systems, it is recommended to employ both CDMA and LMS filters to decrease the effects of co-channel interference. It is observed that the parameter BER reduces as the SNR increases for both these channels. Doi: 10.28991/esj-2021-01313 Full Text: PDF

Phase Modulation Orthogonal Frequency Division Multiplexing (PM-OFDM) and Code Division Multiple Access (CDMA) have distinctive advantages. On one hand, PM-OFDM is an attractive technique to combat multipath fading and reduce high PAPR in conventional OFDM. On the other hand, CDMA has the ability to serve multiple users at the same time and/or frequency. In this article, a new PM-OFDM-CDMA system that combines PM-OFDM and CDMA is proposed. The idea behind the proposed technique is to combine the advantages of these techniques in order to enhance the performance of the 5G system by serving multiple users simultaneously. The performance of the proposed system is analysed in terms of BER under different channel conditions. A Minimum Mean Square Equaliser (MMSE) scheme is used in order to avoid the effect of multipath effect and noise simultaneously. From the simulation results, we conclude that the proposed system has good performance that can improve 5G wireless communication networks, especially for battery-powered mobile devices. This amounts to the constant envelope of the proposed waveform which generates constant instantaneous power and therefore reduced PAPR.

Communications systems concerted over wireless channels depend on the environment. Communications system can be more reliable and efficient by properly analyzing wireless channels. Today's most important features are a high data rate and reliable performance to exploiting viable networks during this new information age. The channel is not time-invariant in wireless communication, so the received signal exhibits amplitude, phase, and angle variations due to multipath fading. Increasing data rates and reducing bandwidth make Orthogonal Frequency Division Multiplexing (OFDM) an important component of wireless communication systems. The OFDM technique uses many carriers very efficiently. With this scheme, interference is robustly reduced, and fading scenarios are easily accommodated. Analyzing digital modulation schemes requires evaluating link performance with fading channels. The paper compares channel performance over varying fading environments using a variety of modulation schemes. We study the BER and SNR properties of the AWGN, Rician fading and Rayleigh fading channels modulated with BPSK, QPSK, and M-ary QAM.

To save energy consumption of Ethernet switches, IEEE has standardized a new energy-efficient operation for Ethernet links with a low-power state and transition mechanisms between the high-power state for transporting traffic and the low-power state.In this paper, we propose a queueing model with the Markov Modulated Compound Poisson Process that is able to characterize backbone packet traffic. We derive a closed-form solution for the stationary distribution of the proposed queueing model. We show that our model can capture an entire system where the transition times are constant.

The Internet is nowadays suffering dramatically serious attacks, with the distributed denial of service (DDoS) attacks being the representative and dominant ones. It is seen that, to stabilize the buffer queue length around a given target under DDoS attacks in the relevant routes is vitally important and helpful to mitigate the attacks and to improve the quality of service (QoS) for normal users. In the current paper, a stochastic queue dynamic model with L e ´ vy jump noise, which is affected by the continuous Brownian motion and the discontinuous Poisson process, is worked out to develop a novel and accurate mathematical framework for the stability of a route queue that deals with constant-rate DDoS attacks. This article proposes a security defensive mechanism in the network for solving the network collapse that can possibly be caused by DDoS attacks, otherwise. Particularly, based on the formulation of a stochastic queue dynamic with L e ´ vy jump noise, the mechanism that characterizes the behavior of the queue at routers is presented for stabilizing the queue length under constant-rate DDoS attacks. By applying the stochastic control theory into analyzing the performance of queue dynamic under constant-rate DDoS attacks, some explicit conditions are established under which the instantaneous queue length converges to any given target in a route. Simulation results demonstrate the satisfaction of the proposed defense mechanism with sharp contrast to the state of the art active queue management (AQM) schemes.

In this work, we leverage the clustered $\beta$ -Ginibre point process (GPP) and the queueing theory to analyse the delay performance in a large-scale repulsive fog radio access network (F-RAN) with computation offloading, which plays a key role on the delay performance. In particular, the average delay defined as the mean value of delay for executing the computing tasks and the task completion probability (TCP) defined as the probability of the delay for executing the computing task being smaller than a target delay, are derived in analytical forms and validated by Monte Carlo simulations. Based on these results, the optimal rate threshold, which affects the task offloading probability and the transmission delay, and the optimal cloud offloading probability to minimize the average delay and maximize the TCP are jointly analysed numerically. Moreover, an approximated result of the average delay is provided to reduce its computational complexity. The results show that the repulsion in the F-RAN significantly decreases the average delay and increases the TCP, but equipped with the optimal rate threshold and the cloud offloading probability, the effects of repulsion on the average delay and the TCP become trivial. Furthermore, with the optimal cloud offloading probability and rate threshold, the average delay and the TCP can be significantly reduced and improved in the hybrid processing mode compared with those in the local processing mode, respectively. The optimal rate thresholds lie in the range of 3 to 13 Mbps under our simulation environment, which can reduce a maximum of 60% of the average delay and increase a minimum of 0.17 of the TCP.

This short note discusses open problems and partial solutions related to Sheldon M Ross's second conjecture about the classical single server queue subject to a randomly time-varying rate arrival rate., Comment: This preprint has not undergone peer review or any post-submission improvements or corrections. The Version of Record of this article is published in Queueing Systems 2022, and is available online at https://doi.org/10.1007/s11134-022-09824-0

This article is devoted to the analysis of a queuing system formed by two flows with density functions of the gamma distribution law in order to derive a solution for the average delay of requests in the queue, which is the main characteristic for any queuing system. According to this characteristic, for example, packet delays in packet-switched networks are estimated when they are modeled using the queuing system. In queuing theory, studies of G/G/1 systems are especially relevant because there is no solution in the final form for the general case. Therefore, in the study of such systems, various particular distribution laws are used as an arbitrary distribution law for G. In the study of G/G/1 systems, an important role is played by the method of spectral decomposition of the solution of the Lindley integral equation, and most of the results in the theory of queuing were obtained using this method. The article presents the derivation of the calculation formula for the average delay of requests in the queue in the system under consideration, also based on the spectral decomposition method.

We investigate the impact of fading correlation on the performance of the doubly dirty fading multiple access channel (MAC) with non-causally known side information at transmitters. Using Copula theory, we derive closed-form expressions for the outage probability and the coverage region under arbitrary dependence conditions. We show that a positive dependence structure between the fading channel coefficients is beneficial for the system performance, as it improves the outage probability and extends the coverage region compared to the case of independent fading. Conversely, a negative dependence structure has a detrimental effect on both performance metrics.

We study a G/GI/1 single-server queuing model with i.i.d. service times that are independent of a stationary process of inter-arrival times. We show that the distribution of the waiting time converges to a stationary law as time tends to infinity provided that inter-arrival times satisfy a Gartner-Ellis type condition. A convergence rate is given and a law of large numbers established. These results provide tools for the statistical analysis of such systems, transcending the standard case with independent inter-arrival times.

Chained Training Scheme (CTS) and Chained training scheme with Revised Sequence (CRS) were proposed to train artificial neural networks (ANNs) to design doubly reinforced concrete (RC) beams. CRS a...

We consider an acyclic network of single-server queues with heterogeneous processing rates. It is assumed that each queue is fed by the superposition of a large number of i.i.d. Gaussian processes with stationary increments and positive drifts, which can be correlated across different queues. The flow of work departing from each server is split deterministically and routed to its neighbors according to a fixed routing matrix, with a fraction of it leaving the network altogether. We study the exponential decay rate of the probability that the steady-state queue length at any given node in the network is above any fixed threshold, also referred to as the ‘overflow probability’. In particular, we first leverage Schilder’s sample-path large deviations theorem to obtain a general lower bound for the limit of this exponential decay rate, as the number of Gaussian processes goes to infinity. Then, we show that this lower bound is tight under additional technical conditions. Finally, we show that if the input processes to the different queues are nonnegatively correlated, non-short-range dependent fractional Brownian motions, and if the processing rates are large enough, then the asymptotic exponential decay rates of the queues coincide with the ones of isolated queues with appropriate Gaussian inputs.

In the present work, we propose a novel modulation scheme for 5G wireless communication system. Our contribution is to combine PM-OFDM (Phase Modulation Orthogonal Frequency Division Multiplexing) and CDMA (Code Division Multiple Access) to exploit their distinctive advantages. On the one hand, PM-OFDM is an effective technique to combat multipath fading effects. On the other hand, CDMA can serve multiple users who are using the same resources of time/frequency. The aim is to make a combination of PM-OFDM and CDMA techniques. In this paper, the OFDM-CDMA scheme and its PAPR (Peak-to-Average Power Ratio) statistics are reviewed. In this paper, the proposed scheme PM-OFDM-CDMA is described and its performances in terms of PAPR, power spectral density, and BER (Bit Error Rate) are analyzed. Moreover, MMSE (Minimum Mean Square Error) equalizer is used to avoid multipath and noise effects simultaneously. The simulation through AWGN (Additive white Gaussian noise) and Rayleigh channels is performed using MATLAB. From the simulation results, we observed that PM-OFDM-CDMA is an efficient technique in terms of energy consumption (PAPR = 0dB). Besides, CE-OFDM-CDMA offers high spectral efficiency with low BER due to its low PAPR. In CE-OFDM-CDMA method, the shape of the spectrum varies according to the value of the modulation index h. The band occupied by the spectrum increases with the value of h. Therefore, CE-OFDM-CDMA could be considered as a suitable technique for 5G applications.

Age of Information (AoI) is a critical metric in status update systems as these systems require the fresh updates. This letter investigates the uplink of an Internet-of-Thing (IoT) network where ${L}$ nodes transmit their information packets to a base station. The effects of the arrival rate of packets at the nodes, the number of nodes in the system, and queue length of each node have been studied by devising a discrete time Markov chain (MC) model. This model helps in predicting the values of AoI and probability of packet drops in such systems. The notion of first-in first-out is used for queuing, which transmits the oldest packet first, resulting in decreasing the overall AoI of the system. The results show that AoI increases with the increase in queue length, number of nodes and arrival rate and we quantify the aforementioned metrics using the MC model. The results found using the MC model are also validated using extensive simulations.

This paper proposes a general analytical approach to derive the outage probability of hybrid automatic repeat request with incremental redundancy (HARQ-IR) over correlated fading channels in closed-form. Unlike prior analyses, the consideration of channel correlation is one of the key reasons making the outage analysis involved. Using conditional Mellin transform, the outage probability of HARQ-IR over correlated Rayleigh fading channels is exactly expressed as a mixture of outage probabilities of HARQ-IR over independent Nakagami fading channels, where the weights are negative multinomial probabilities. Its straightforward application is to conduct asymptotic outage analysis to gain more insights, in which the asymptotic outage probability is obtained in a concise form. The asymptotic outage probability possesses some special properties which ease optimal power allocation and rate selection of HARQ-IR. Finally, numerical results are presented for validations and discussions.

In this paper, we study the asymptotic behavior of the tail probability of the number of customers in the steady-state $M/G/1$ retrial queue with Bernoulli schedule, under the assumption that the service time distribution has a regularly varying tail. Detailed tail asymptotic properties are obtained for the (conditional and unconditional) probability of the number of customers in the (priority) queue, orbit and system, respectively., 18 pages; revised version: 20 pages

Implementation of the cross-fade audio effect requires shaping the fade profile for a certain audio content that is to be faded out, as well as customizing the audio fade for an additional audio content, which is to be faded in, with the purpose of achieving a smooth transition between the two different audio contents. Similar to the case of applying adjustable fades, the audio cross-fades are usually carried out in the off-line mode, by employing various transcendental functions to shape the audio fades (both fade-out and fade-in effects). To improve the computational capabilities by minimizing the delay between receiving the position within the cross-fade effect and returning both the volume of the faded out section and the volume of the faded in one, we consider that, during the cross-fade effect, the audio volume of each of the two overlapping sections is the output of a rational function i.e. a mapping defined by a rational fraction. A plain HTML5/JavaScript implementation, prepared to be tested in any major browser, is advanced in the paper in order to highlight the suitability of the suggested approach to audio cross-fade customization with real-time computing.

We study the reachability problem for queue automata and lossy queue automata. Concretely, we consider the set of queue contents which are forwards resp. backwards reachable from a given set of queue contents. Here, we prove the preservation of regularity if the queue automaton loops through some special sets of transformation sequences. This is a generalization of the results by Boigelot et al. and Abdulla et al. regarding queue automata looping through a single sequence of transformations. We also prove that our construction is possible in polynomial time.

In this paper, we conduct rate-distortion and outage probability analyses for Wyner-Ziv (WZ) systems, where the information sequences from a source and a helper are transmitted to the destination over block Rayleigh fading multiple access channels (MACs). This work has been motivated by decision-making systems, where the aim is to make right decisions based on the observations. Hence, the most critical performance metric is the accuracy of decisions, even allowing distortion in wireless transmission. A sufficient condition for the successful transmissions is that the WZ and MAC regions intersect. For the ease of calculating the outage probability, we propose an approximated, yet accurate, WZ rate region. The outage probabilities of the WZ systems are then evaluated both in orthogonal and MAC transmissions. It is shown that the transmission efficiency of the system with MAC is significantly improved compared to orthogonal transmission. Furthermore, a helper-selection scheme is introduced to further reduce the outage probability of the WZ-MAC systems. The results show that the outage probability decreases, of which decay corresponds to the $(L+1)$ -order diversity with $L$ helpers in small value range of the average signal-to-noise ratio (SNR), while it converges into $L$ as the average SNR becomes large.

This paper considers Preemptive Mobile Computation Offloading when concurrent local execution (CLE) is used to guarantee task execution time constraints. By allowing simultaneous local and remote execution, CLE ensures that job deadlines are always satisfied in the face of unforeseen wireless channel conditions. In the preemptive offloading case, at the start of each time slot, a decision is made to either continue or temporarily interrupt the offload. This mechanism allows the system to adapt when channel conditions change. The paper considers the case for homogeneous Markovian wireless channels. Using Markovian decision process stopping theory, an online energy-optimal computation offloading algorithm is formulated for preemptive offloading, referred to as Optimal Preemptive Offloading (OPO). Since the computational complexity of OPO can be prohibitive, the paper introduces three computationally efficient techniques motivated by OPO: 1) water-filling ; 2) water-filling with scheduling ; and 3) generalized water-filling . For each method, two variations are considered. The first ( Equ ) uses the equilibrium channel state probabilities in offloading decision calculations, and the second ( Exp ) uses Markovian transition matrix exponentiation. This results in six algorithms with a wide variety of energy performance and computational complexity. Performance of the algorithms is compared that shows the tradeoffs between complexity and mobile energy saving performance.

Consider a multihop wireless network serving multiple flows in which wireless interference constraints between links are described by a link-interference graph. The timely-throughput of a flow is defined as the throughput of packets of that flow that reach their destination node within a specified deadline, and the weighted timely throughput of the network is their weighted average over the flows with a given set of positive weights. The problem is particularly challenging, and has generally been open, when there is wireless interference between transmissions. We show that a modified CSMA routing-scheduling policy with an appropriate set of attempt probabilities is nearly optimal for maximizing weighted timely-throughput. This policy has the useful property that the routing-scheduling decision for an individual packet is solely a function of its location and time-to-deadline, and so a wireless node does not require knowledge of the global network state. It is easily implementable in a decentralized fashion by the nodes given the attempt probabilities. A gradient-based adaptive CSMA routing-scheduling policy to determine the optimal attempt probabilities is further provided. It moves along the gradient of the timely throughput and converges to a local maximum.

In this article, we study the Euler's discretization effect on a sliding-mode control system with a supertwisting algorithm (STA). We start from the undisturbed STA and show that the trajectory eventually converges to an exactly bounded region around the origin. Periodic behaviors are explored. Furthermore, the discretization effect on the disturbed STA is established, and the stability analysis is given. Simulation results demonstrate the effectiveness of the proposed strategies.

In this article, in addition to two commonly known noise parameters—dark count rate (DCR) and afterpulsing (AP)—we explore another interesting phenomenon–random telegraph signal (RTS) noise—during the transitional phase of the avalanching process. We present the properties of the RTS noise and their dependence on the biasing voltage and temperature. An analytical model is used to extract the dimension of the defects in the depletion region from the variation of the RTS noise current amplitude with biasing voltage. By comparing the DCR and AP of single-photon avalanche diode (SPAD) samples with different defect dimensions derived from the RTS noise properties, a trend that the SPAD with a larger defect dimension shows a higher DCR and AP is found.

In this paper, we study a large system of $N$ servers each with capacity to process at most $C$ simultaneous jobs and an incoming job is routed to a server if it has the lowest occupancy amongst $d$ (out of N) randomly selected servers. A job that is routed to a server with no vacancy is assumed to be blocked and lost. Such randomized policies are referred to JSQ(d) (Join the Shortest Queue out of $d$) policies. Under the assumption that jobs arrive according to a Poisson process with rate $N\lambda^{(N)}$ where $\lambda^{(N)}=\sigma-\frac{\beta}{\sqrt{N}}$, $\sigma\in\mb{R}_+$ and $\beta\in\mb{R}$, we establish functional central limit theorems (FCLTs) for the fluctuation process in both the transient and stationary regimes when service time distributions are exponential. In particular, we show that the limit is an Ornstein-Uhlenbeck process whose mean and variance depend on the mean-field of the considered model. Using this, we obtain approximations to the blocking probabilities for large $N$, where we can precisely estimate the accuracy of first-order approximations., Comment: 29 pages

Tension Leg Platform (TLP) is an offshore platform structure used for deep-sea oil and gas exploration. The main structure of the TLP consists of a deck, pontoon, mooring system, and foundation. TLP operates in a balance of buoyancy, structural weight, and mooring tension. The problem is the construction of TLP in the deep sea, where sometimes extreme waves appear could damage the TLP structure. This paper proposes a new model of TLP that is more stable to extreme waves. The method is to separate the mass of the deck and the mass of the pontoon into two flexible parts, which are connected by a cantilever spring system. Thus the TLP motion becomes two degrees of freedom (TLP 2-DOF). Using the dynamic vibration absorber (DVA) method, the ratio of the deck mass, pontoon mass, and spring stiffness are adjusted so that the primary mass movement is minimal. Furthermore, the ratio of the amplitude of the deck movement as the primary mass to the wave amplitude is analyzed, which is known as the operator response amplitude (RAO). The results showed that the TLP 2-DOF model was more stable. As an illustration, at resonance conditions, this model can reduce RAO to about 67%.

Discrete-time queueing models find a large number of applications as they are used in modeling queueing systems arising in digital platforms like telecommunication systems and computer networks. In this paper, we analyze an infinite-buffer queueing model with discrete Markovian arrival process. The units on arrival are served in batches by a single server according to the general bulk-service rule, and the service time follows general distribution with service rate depending on the size of the batch being served. We mathematically formulate the model using the supplementary variable technique and obtain the vector generating function at the departure epoch. The generating function is in turn used to extract the joint distribution of queue and server content in terms of the roots of the characteristic equation. Further, we develop the relationship between the distribution at the departure epoch and the distribution at arbitrary, pre-arrival and outside observer’s epochs, where the first is used to obtain the latter ones. We evaluate some essential performance measures of the system and also discuss the computing process extensively which is demonstrated by some numerical examples.

We study ergodic properties of Markovian multiclass many-server queues which are uniform over scheduling policies, as well as the size n of the system. The system is heavily loaded in the Halfin-Whitt regime, and the scheduling policies are work-conserving and preemptive. We provide a unified approach via a Lyapunov function method that establishes Foster-Lyapunov equations for both the limiting diffusion and the prelimit diffusion-scaled queueing processes simultaneously. We first study the limiting controlled diffusion, and we show that if the spare capacity (safety staffing) parameter is positive, then the diffusion is exponentially ergodic uniformly over all stationary Markov controls, and the invariant probability measures have uniform exponential tails. This result is sharp, since when there is no abandonment and the spare capacity parameter is negative, then the controlled diffusion is transient under any Markov control. In addition, we show that if all the abandonment rates are positive, the invariant probability measures have sub-Gaussian tails, regardless whether the spare capacity parameter is positive or negative. Using the above results, we proceed to establish the corresponding ergodic properties for the diffusion-scaled queueing processes. In addition to providing a simpler proof of the results in Gamarnik and Stolyar [Queueing Syst (2012) 71:25-51], we extend these results to the multiclass models with renewal arrival processes, albeit under the assumption that the mean residual life functions are bounded. For the Markovian model with Poisson arrivals, we obtain stronger results and show that the convergence to the stationary distribution is at an exponential rate uniformly over all work-conserving stationary Markov scheduling policies., 28 pages

We consider a millimeter-wave communication system where the fading channel follows the Nakagami- $m$ distribution. We derive performance limits of such a system in terms of the diversity and coding gains. First, we argue that although traditional design criteria for space-time codes (STCs) are optimal for Rayleigh and Rician fading channels, they fail to capture the optimal diversity and coding gains for Nakagami- $m$ fading channels. Then, we derive a tight upper bound on the average pair-wise error probability at high signal-to-noise ratios. From such a bound, we obtain upper and lower bounds on the diversity and coding gains of any STC over the Nakagami- $m$ fading channel. We then identify necessary and sufficient conditions for STCs to achieve the upper bounds, leading to a fundamental trade-off between maximizing the diversity and coding gains. We also investigate the effect of blockage using stochastic geometry. We show that the diversity and coding gains are limited by the non-line-of-sight link. Numerical simulations assuming different fading scenarios further illustrate that STCs that satisfy the new design achieve full diversity. Whereas, STCs that are otherwise optimal for Rayleigh and Rician channels do not. Furthermore, in a typical indoor environment, blockage reduces the coding gain by 1.5 dB for BERs less than 10 $^{-3}$ .

In this paper we study the M/M/1 queueing model with retrial on network. We derive the steady state probability of customers in the network, the average number of customers in the all the three nodes in the system, the queue length, system length using little’s formula. The particular case is derived (no retrial). The numerical examples are given to test the correctness of the model.