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Optimal CPU scheduling in data centers via a finite-time distributed quantized coordination mechanism

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arXiv 2021年

作者： Rikos, Apostolos I. Grammenos, Andreas Kalyvianaki, Evangelia Hadjicostis, Christoforos N. Charalambous, Themistoklis Johansson, Karl H. Division of Decision and Control Systems KTH Royal Institute of Technology StockholmSE-100 44 Sweden Department of Computer Science and Technology University of Cambridge Cambridge United Kingdom Alan Turing Institute London United Kingdom Department of Electrical and Computer Engineering University of Cyprus Nicosia1678 Cyprus Department of Electrical Engineering and Automation School of Electrical Engineering Aalto University Espoo02150 Finland

In this paper we analyze the problem of optimal task scheduling for data centers. Given the available resources and tasks, we propose a fast distributed iterative algorithm which operates over a large scale network of nodes and allows each of the interconnected nodes to reach agreement to an optimal solution in a finite number of time steps. More specifically, the algorithm (i) is guaranteed to converge to the exact optimal scheduling plan in a finite number of time steps and, (ii) once the goal of task scheduling is achieved, it exhibits distributed stopping capabilities (i.e., it allows the nodes to distributely determine whether they can terminate the operation of the algorithm). Furthermore, the proposed algorithm operates exclusively with quantized values (i.e., the information stored, processed and exchanged between neighboring agents is subject to deterministic uniform quantization) and relies on event-driven updates (e.g., to reduce energy consumption, communication bandwidth, network congestion, and/or processor usage). We also provide examples to illustrate the operation, performance, and potential advantages of the proposed algorithm. Finally, by using extensive empirical evaluations through simulations we show that the proposed algorithm exhibits state-of-the-art performance. Copyright © 2021, The Authors. All rights reserved.

关键词： Multitasking

On a network SIS model with opinion dynamics 21st

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On a network SIS model with opinion dynamics

21st IFAC World Congress 2020

作者： Xuan, Weihao Ren, Ruijie Paré, Philip E. Ye, Mengbin Ruf, Sebastian Liu, Ji School of Mechanical Engineering University of Leeds United Kingdom Division of Decision and Control Systems KTH Royal Institute of Technology Stockholm Sweden Faculty of Science and Engineering ENTEG University of Groningen Netherlands Center for Complex Networks Research Department of Psychology Northeastern University United States Department of Electrical and Computer Engineering Stony Brook University United States

This paper proposes a network continuous-time susceptible-infected-susceptible (SIS) model coupled with individual opinion dynamics, where the opinion dynamics models an individual's perceived severity of illness or perceived susceptibility. The effects of opinion dynamics on the network SIS model are studied by analyzing the limiting behaviors of the system model, equilibria of the system and their stability. Copyright © 2020 The Authors. This is an open access article under the CC BY-NC-ND license

关键词： Dynamics

Three-dimensional tracking and height verification of polystyrene particles with piezo actuator positioning by means of multi-wavelength evanescent fields 20

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Three-dimensional tracking and height verification of polyst...

20th International Conference of the European Society for Precision engineering and Nanotechnology, EUSPEN 2020

作者： Blattler, Aran Khajornrungruang, Panart Suzuki, Keisuke Permpatdechakul, Thitipat Graduate School of Computer Science and Systems Engineering Kyushu Institute of Technology Fukuoka Japan Department of Intelligent and Control Systems Advanced Mechanical Division Kyushu Institute of Technology Fukuoka Japan

ISBN: (纸本)9780995775176

To understand the nanoparticle motion behaviours on a surface, we have studied to investigate the three-dimension tracking of an individual nanoparticle with nanometre localisation accuracy. In three-dimensional nanoparticle moving position, the X and Y coordinates are on the parallel plane to the surface, which their coordinates can be tracked in general microscopy. However, the Z coordinate is the nanoparticle height position perpendicularly to the surface plane, which could not be generally tracked without longitudinal scanning method. In this paper, the polystyrene 100 nm standard particles were used to investigate the three-dimensional tracking. The individual standard nanoparticles were fixed on the tip, which was vertically travelled with the piezo actuator for movement control on the third dimension to verify the actual height Z. Our developed optical microscopy apparatus has been applying multi-wavelength evanescent fields, and obtaining multi scattering light intensities from the observed nanoparticles near to surface. Commonly, the X and Y coordinates of nanoparticle were determined by the centre of mass of each scattering light intensity. The height Z was investigated from the integration of the detected scattering intensities of each wavelength. By using our method, the height Z uncertainty could be measured approximately less than ±20 nm, and the penetration height measurability was approximately 250 nm far from the reference surface. Consequently, we could three-dimensionally track the individual standard nanoparticle in recording speed higher than 50 frames per second. Copyright © Proceedings of the 20th International Conference of the European Society for Precision engineering and Nanotechnology, EUSPEN 2020. All rights reserved.

关键词： Nanoparticles

Reinforcement Learning Based Approach for Flip Attack Detection

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Reinforcement Learning Based Approach for Flip Attack Detect...

IEEE Conference on decision and control

作者： Hanxiao Liu Yuchao Li Jonas Mårtensson Lihua Xie Karl Henrik Johansson School of Electrical and Electronic Engineering Nanyang Technological University Singapore School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden Division of Decision and Control Systems the School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden

ISBN: (数字)9781728174471

ISBN: (纸本)9781728174488

This paper addresses the detection problem of flip attacks to sensor network systems where the attacker flips the distribution of manipulated sensor measurements of a binary state. The detector decides to continue taking observations or to stop based on the sensor measurements, and the goal is to have the flip attack recognized as fast as possible while trying to avoid terminating the measurements when no attack is present. The detection problem can be modeled as a partially observable Markov decision process (POMDP) by assuming an attack probability, with the dynamics of the hidden states of the POMDP characterized by a stochastic shortest path (SSP) problem. The optimal policy of the SSP solely depends on the transition costs and is independent of the assumed attack possibility. By using a fixed-length window and suitable feature function of the measurements, a Markov decision process (MDP) is used to approximate the behavior of the POMDP. The optimal solution of the approximated MDP can then be solved by any standard reinforcement learning methods. Numerical evaluations demonstrates the effectiveness of the method.

关键词： Detectors Markov processes Reinforcement learning Cost function Aerospace electronics Velocity measurement Time measurement

Obstacle avoidance via hybrid feedback

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arXiv 2021年

作者： Berkane, Soulaimane Bisoffi, Andrea Dimarogonas, Dimos V. The Department of Computer Science and Engineering University of Quebec in Outaouais Gatineau Canada ENTEG The J.C. Willems Center for Systems and Control University of Groningen Groningen Netherlands The Division of Decision and Control Systems KTH Royal Institute of Technology Stockholm Sweden

In this paper we present a hybrid feedback approach to solve the navigation problem of a point mass in the n−dimensional space containing an arbitrary number of ellipsoidal shape obstacles. The proposed hybrid control algorithm guarantees both global asymptotic stabilization to a reference and avoidance of the obstacles. The intuitive idea of the proposed hybrid feedback is to switch between two modes of control: stabilization and avoidance. The geometric construction of the flow and jump sets of the proposed hybrid controller, exploiting hysteresis regions, guarantees Zeno-free switching between the stabilization and the avoidance modes. Simulation results illustrate the performance of the proposed hybrid control approach for 2-dimensional and 3-dimensional scenarios. © 2021, CC BY.

关键词： Stabilization

Inverse filtering for hidden Markov models with applications to counter-adversarial autonomous systems

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arXiv 2020年

作者： Mattila, Robert Rojas, Cristian R. Krishnamurthy, Vikram Wahlberg, Bo Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Department of Electrical and Computer Engineering Cornell University IthacaNY United States

Bayesian filtering deals with computing the posterior distribution of the state of a stochastic dynamic system given noisy observations. In this paper, motivated by applications in counter-adversarial systems, we consider the following inverse filtering problem: Given a sequence of posterior distributions from a Bayesian filter, what can be inferred about the transition kernel of the state, the observation likelihoods of the sensor and the measured observations? For finite-state Markov chains observed in noise (hidden Markov models), we show that a least-squares fit for estimating the parameters and observations amounts to a combinatorial optimization problem with non-convex objective. Instead, by exploiting the algebraic structure of the corresponding Bayesian filter, we propose an algorithm based on convex optimization for reconstructing the transition kernel, the observation likelihoods and the observations. We discuss and derive conditions for identifiability. As an application of our results, we illustrate the design of counter-adversarial systems: By observing the actions of an autonomous enemy, we estimate the accuracy of its sensors and the observations it has received. The proposed algorithms are evaluated in numerical examples. Copyright © 2020, The Authors. All rights reserved.

关键词： Hidden Markov models

Heterogeneous Entity Representation for Medicinal Synergy Prediction

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arXiv 2024年

作者： Wu, Jiawei Wen, Jun Yan, Mingyuan Dong, Anqi Gao, Shuai Wang, Ren Chen, Can School of Medicine National University of Singapore 119077 Singapore Harvard Medical School Harvard University BostonMA02115 United States Division of Decision and Control Systems Department of Mathematics KTH Royal Institute of Technology StockholmSE-100 44 Sweden Harvey Cushing Neuro-Oncology Laboratories Department of Neurosurgery Brigham and Women's Hospital Harvard Medical School BostonMA02115 United States Department of Electrical and Computer Engineering Illinois Institute of Technology ChicagoIL60616 United States School of Data Science and Society University of North Carolina at Chapel Hill Chapel HillNC27599 United States Department of Mathematics University of North Carolina at Chapel Hill Chapel HillNC27599 United States

Motivation: Forecasting the synergistic effects of drug combinations facilitates drug discovery and development, especially regarding cancer therapeutics. While numerous computational methods have emerged, most of them fall short in fully modeling the relationships among clinical entities including drugs, cell lines, and diseases, which hampers their ability to generalize to drug combinations involving unseen drugs. These relationships are complex and multidimensional, requiring sophisticated modeling to capture nuanced interplay that can significantly influence therapeutic efficacy. Results: We present a novel deep hypergraph learning method named Heterogeneous Entity Representation for MEdicinal Synergy prediction (HERMES) to predict the synergistic effects of anti-cancer drugs. Heterogeneous data sources, including drug chemical structures, gene expression profiles, and disease clinical semantics, are integrated into hypergraph neural networks equipped with a gated residual mechanism to enhance high-order relationship modeling. HERMES demonstrates state-of-the-art performance on two benchmark datasets, significantly outperforming existing methods in predicting the synergistic effects of drug combinations, particularly in cases involving unseen drugs. Availability: The source code is publicly available at https://***/Christina327/*** Codes 92C50, 05C65, 68T07 © 2024, CC BY.

关键词： Gene expression

Robust Voltage control in DC Networks with Uncertain Nonlinear Load Dynamics

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Robust Voltage Control in DC Networks with Uncertain Nonline...

IEEE Conference on decision and control

作者： Amirreza Silani Giacomo Casadei Michele Cucuzzella Jan C. Wilems Center for Systems and Control ENTEG Faculty of Science and Engineering University of Groningen AG Groningen The Netherlands Control & Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Laboratoire Ampere Dpt. EEA of the Ecole Centrale de Lyon Université de Lyon Ecully France Department of Electrical Computer and Biomedical Engineering University of Pavia Pavia Italy

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

In this letter, we propose a control scheme for regulating the voltage in Direct Current (DC) power networks. In contrast with other works in the literature where the loads are assumed to be constant, we consider uncertain time-varying loads described as the outputs of nonlinear dynamical exosystems with uncertain parameters. Based on the output regulation methodology, the proposed control scheme ensures the robust stability of the overall network and achieves voltage regulation in presence of impedance (Z), current (I), and power (P) loads. The simulation results illustrate excellent performance of the proposed control scheme.

关键词： Robust stability Simulation Regulation Impedance Voltage control

Corrigendum to “Consistency analysis of the Simplified Refined Instrumental Variable method for Continuous-time systems” [Automatica 113 (2020) 108767]

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Automatica 2022年 136卷

作者： Siqi Pan Rodrigo A. González James S. Welsh Cristian R. Rojas School of Electrical Engineering and Computing University of Newcastle Callaghan NSW 2308 Australia Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm 10044 Sweden