Uncertainty-Aware Resource Provisioning for Network Slicing Luu, Quang-Trung; Kerboeuf, Sylvaine; Kieffer, Michel
IEEE eTransactions on network and service management,
2021-March, 2021-3-00, 20210301, 2021-03-01, Letnik:
18, Številka:
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Network slicing allows Mobile Network Operators to split the physical infrastructure into isolated virtual networks (slices), managed by Service Providers to accommodate customized services. The ...Service Function Chains (SFCs) belonging to a slice are usually deployed on a best-effort premise: nothing guarantees that network infrastructure resources will be sufficient to support a varying number of users, each with uncertain requirements. Taking the perspective of a network Infrastructure Provider (InP), this article proposes a resource provisioning approach for slices, robust to a partly unknown number of users with random usage of the slice resources. The provisioning scheme aims to maximize the total earnings of the InP, while providing a probabilistic guarantee that the amount of provisioned network resources will meet the slice requirements. Moreover, the proposed provisioning approach is performed so as to limit its impact on low-priority background services, which may co-exist with slices in the infrastructure network. Taking all these constraints into account leads to an integer programming problem with many nonlinear constraints. These constraints are first relaxed to get an integer linear programming formulation of the slice resource provisioning problem. This problem is then solved considering the slice resource provisioning demands jointly. A suboptimal approach is finally proposed where slice resource provisioning demands are considered sequentially. Both solutions are compared to provisioning schemes that do not account for best-effort services sharing the common infrastructure network, as well as uncertainties in the slice resource demands.
This study extends recent results by Garcia et al. on an event-triggered communication to reach consensus in multi-agent systems. First, it studies the effect of two types of additive and bounded ...state perturbations on the consensus and on the communications. Second, it describes an improved agent state estimator as well as an estimator of the state estimation uncertainty to trigger communications. Convergence to consensus is studied. Simulations show the effectiveness of the proposed estimators in the presence of state perturbations.
In parameter estimation, it is often desirable to supplement the estimates with an assessment of their quality. A new family of methods proposed by Campi et al. for this purpose is particularly ...attractive, as it makes it possible to obtain exact, non-asymptotic confidence regions under mild assumptions on the noise distribution. A bottleneck of this approach, however, is the numerical characterization of these confidence regions. So far, it has been carried out by gridding, which provides no guarantee as to its results and is only applicable to low dimensional spaces. This paper shows how interval analysis can contribute to removing this bottleneck.
Statistical multiplexing of video contents aims at transmitting several variable bit rate (VBR) encoded video streams over a band-limited channel. Rate-distortion (RD) models for the encoded streams ...are often used to control the video encoders. Buffering at the output of encoders is one of the several techniques used to smooth out the fluctuating bit rate of compressed video due to variations in the activity of video contents. In this paper, a statistical multiplexer is proposed where a closed-loop control of both video encoders and buffers is performed jointly. First, a predictive joint video encoder controller accounting for minimum quality, fairness, and smoothness constraints is considered. Second, all buffers are controlled simultaneously to regulate the buffering delays. This delay is adjusted according to a reference delay constraint. The main idea is to update the encoding rate for each video unit according to the average level of the buffers, to maximize the quality of each program and effectively use the available channel rate. Simulation results show that the proposed scheme yields a smooth and fair video quality among programs thanks to the predictive control. A similar buffering delay for all programs and an efficient use of the available channel rate are ensured thanks to the buffer management and to the predictive closed-loop control.
Treats joint source and channel decoding in an integrated wayGives a clear description of the problems in the field together with the mathematical tools for their solutionContains many detailed ...examples useful for practical applications of the theory to video broadcasting over mobile and wireless networksTraditionally, cross-layer and joint source-channel coding were seen as incompatible with classically structured networks but recent advances in theory changed this situation. Joint source-channel decoding is now seen as a viable alternative to separate decoding of source and channel codes, if the protocol layers are taken into account. A joint source/protocol/channel approach is thus addressed in this book: all levels of the protocol stack are considered, showing how the information in each layer influences the others.This book provides the tools to show how cross-layer and joint source-channel coding and decoding are now compatible with present-day mobile and wireless networks, with a particular application to the key area of video transmission to mobiles. Typical applications are broadcasting, or point-to-point delivery of multimedia contents, which are very timely in the context of the current development of mobile services such as audio (MPEG4 AAC) or video (H263, H264) transmission using recent wireless transmission standards (DVH-H, DVB-SH, WiMAX, LTE). This cross-disciplinary book is ideal for graduate students, researchers, and more generally professionals working either in signal processing for communications or in networking applications, interested in reliable multimedia transmission. This book is also of interest to people involved in cross-layer optimization of mobile networks. Its content may provide them with other points of view on their optimization problem, enlarging the set of tools which they could use.Pierre Duhamel is director of research at CNRS/ LSS and has previously held research positions at Thomson-CSF, CNET, and ENST, where he was head of the Signal and Image Processing Department. He has served as chairman of the DSP committee and associate Editor of the IEEE Transactions on Signal Processing and Signal Processing Letters, as well as acting as a co-chair at MMSP and ICASSP conferences. He was awarded the Grand Prix France Telecom by the French Science Academy in 2000. He is co-author of more than 80 papers in international journals, 250 conference proceedings, and 28 patents. Michel Kieffer is an assistant professor in signal processing for communications at the Université Paris-Sud and a researcher at the Laboratoire des Signaux et Systèmes, Gif-sur-Yvette, France. His research interests are in joint source-channel coding and decoding techniques for the reliable transmission of multimedia contents. He serves as associate editor of Signal Processing (Elsevier). He is co-author of more than 90 contributions to journals, conference proceedings, and book chapters. Treats joint source and channel decoding in an integrated wayGives a clear description of the problems in the field together with the mathematical tools for their solutionContains many detailed examples useful for practical applications of the theory to video broadcasting over mobile and wireless networks
This paper addresses the low-delay location of faults due to lightning strikes using single-ended measurements in HVDC grids. A combined data-driven and model-driven approach is used to estimate the ...fault location iteratively. No prior knowledge of the voltage evolution at the fault location is required. Once the first wavefront due to a fault is detected at some observation location of the HVDC grid, the measurements are fed to a model of the propagation of transient waves along the lines. The model is parameterized by the estimated fault location. As a result, a model of the waveform samples starting from the second wavefront is obtained. The measured and modeled waveform samples are then compared to update the estimate of the fault location. The performance of the proposed approach is evaluated via simulations, including field measurements of lightning currents. Typical location accuracy of 300 m is obtained by considering observations performed at 1 MHz over an observation time interval of less than 1.5 ms.
The protection of meshed HVDC grids requires the fast identification of faults affecting the transmission lines. Communication-based methods are thus not suited due to the transmission delays. Many ...approaches involving a model of the transient behavior of the faulty line have recently been proposed. Nevertheless, an accurate description of the traveling wave phenomenon in multi-conductor lines such as overhead lines requires complex computations ill-suited for fast fault identification. This paper presents a single-ended fault identification algorithm using a closed-form parametric model of the fault transient behavior. The model combines physical and behavioral parts and depends explicitly on the parameters that characterize the fault, namely the fault distance and impedance. When a fault is suspected, the fault parameters are estimated so that the model fits best the received measurements. The confidence region of the estimated fault parameters is used to decide whether the protected line is actually faulty or not. The proposed algorithm is tested on a 4 station grid simulated with EMTP-RV software. The method is able to identify the faulty line using a measurement window of less than 0.5 ms. This allows ultra-fast fault clearing and can hence improve the overall reliability of future HVDC grids.
This paper considers the problem of impulse noise mitigation when video is encoded using a SoftCast-based Linear Video Coding (LVC) scheme and transmitted using an Orthogonal Frequency-Division ...Multiplexing (OFDM) scheme for multi-carrier modulation over a wideband channel prone to impulse noise. In the time domain, the impulse noise is modeled as realization of a sequence of independent and identically distributed Bernoulli-Gaussian variables. A Fast Bayesian Matching Pursuit algorithm is employed for impulse noise mitigation. This approach requires the provisioning of some OFDM subchannels to estimate the impulse noise locations and amplitudes. Provisioned subchannels cannot be used to transmit data and lead to a decrease of the video quality at receivers in absence of impulse noise. Using a phenomenological model (PM) of the residual noise variance after impulse mitigation in the subchannels, we have proposed an algorithms that is able to get the amount of subchannel to provision which minimizes the mean-square error of the decoded video at receivers. Simulation results show that the PM can accurately predict the number of subchannels to provision and that impulse noise mitigation can significantly improve the decoded video quality compared to a situation where all subchannels are used for data transmission.
This paper addresses the problem of formation control and tracking of some reference trajectory by an Euler–Lagrange multi-agent systems. The reference trajectory is only known by a subset of agents. ...This work is inspired by recent results by Yang et al. and adopts an event-triggered control strategy to reduce the number of communications between agents. For that purpose, to evaluate its control input, each agent maintains estimators of the states of its neighbor agents, as well as an estimate of its reference trajectory. Communication is triggered when the discrepancy between the actual state of an agent and the estimate of this state as evaluated by neighboring agents reaches some threshold. Communications are also triggered when the reference trajectory estimate is degraded. The impact of additive state perturbations on the formation control is studied. A condition for the convergence of the multi-agent system to a stable formation is studied. The time interval between two consecutive communications by the same agent is shown to be strictly positive. Simulations show the effectiveness of the proposed approach.
Conventional data compression schemes aim at implementing a trade-off between the rate required to represent the compressed data and the resulting distortion between the original and reconstructed ...data. However, in more and more applications, what is desired is not reconstruction accuracy but the quality of the realization of a certain task by the receiver. In this paper, the receiver task is modeled by an optimization problem whose parameters have to be compressed by the transmitter. Motivated by applications such as the smart grid, this paper focuses on a goal function which is of Lp-norm-type. The aim is to design the precoding, quantization, and decoding stages such that the maximum of the goal function obtained with the compressed version of the parameters is as close as possible to the maximum obtained without compression. The numerical analysis, based on real smart grid signals, clearly shows the benefits of the proposed approach compared to the conventional distortion-based compression paradigm.
•General framework for designing compression methods for the Lp norm minimization problem.•Novel linear and nonlinear transformation schemes by taking into account the performance degradation in terms of the Lp norm induced by model reduction.•Tailor the quantization rule to be goal-oriented by considering the impact of the precoding and the final use of the compressed data.•Evaluation of the proposed coding schemes with a real dataset and show the significant performance improvement compared to existing conventional transformation and quantization techniques.
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