Feedback Control of Cyber-Physical Systems with Multi Resource Dependencies and Model Uncertainties

The problem of modeling and controlling re- sources in a system with interaction between hardware and software is considered. A model encompassing both hardware and software dynamics is developed together with an on- line estimation scheme in order reduce dependence on a- priori information. A control structure is presented in order to control performance under constrained resource situations and to reduce effects of estimation errors and disturbances. The approach is applied to a conversational video case and evaluated through simulations

Dynamic Thermal and Power Management: From Computers to Buildings

Thermal and power management have become increasingly important for both computing and physical systems. Computing systems from real-time embedded systems to data centers require effective thermal and power management to prevent overheating and save energy. In the mean time, as a major consumer of energy buildings face challenges to reduce the energy consumption for air conditioning while maintaining comfort of occupants. In this dissertation we investigate dynamic thermal and power management for computer systems and buildings. (1) We present thermal control under utilization bound (TCUB), a novel control-theoretic thermal management algorithm designed for single core real-time embedded systems. A salient feature of TCUB is to maintain both desired processor temperature and real-time performance. (2) To address unique challenges posed by multicore processors, we develop the real-time multicore thermal control (RT-MTC) algorithm. RT-MTC employs a feedback control loop to enforce the desired temperature and CPU utilization of the multicore platform via dynamic frequency and voltage scaling. (3) We research dynamic thermal management for real-time services running on server clusters. We develop the control-theoretic thermal balancing (CTB) to dynamically balance temperature of servers via distributing clients\u27 service requests to servers. Next, (4) we propose CloudPowerCap, a power cap management system for virtualized cloud computing infrastructure. The novelty of CloudPowerCap lies in an integrated approach to coordinate power budget management and resource management in a cloud computing environment. Finally we expand our research to physical environment by exploring several fundamental problems of thermal and power management on buildings. We analyze spatial and temporal data acquired from an real-world auditorium instrumented by a multi-modal sensor network. We propose a data mining technique to determine the appropriate number and location of temperature sensors for estimating the spatiotemporal temperature distribution of the auditorium. Furthermore, we explore the potential energy savings that can be achieved through occupancy-based HVAC scheduling based on real occupancy data of the auditorium

Thermal-aware real-time scheduling using timed continuous Petri Nets

We present a thermal-aware, hard real-time (HRT) global scheduler for a multiprocessor system designed upon three novel techinques. First, we present a modeling methodology based on Timed Continuous Petri nets (TCPN) that yields a complete state variable model, including job arrivals, CPU usage, power, and thermal behavior. The model is accurate and avoids the calibration stage of RC thermal models. Second, based on this model, a linear programming problem (LPP) determines the existence of a feasible HRT thermal-aware schedule. Last, a sliding-mode controller and an online discretization algorithm implement the global HRT scheduler, which is capable of managing thermal constraints, context switching, migrations, and disturbances

KONTROL SUHU DAN ANALISIS TRANSFER PANAS KONVEKSI PADA CENTRAL PROCESSING UNIT (CPU)

Central Processing Unit (CPU) adalah tempat pemrosesan instruksi – instruksi program dilakukan. CPU dapat menjadi cepat panas bila digunakan dalam jangka waktu lama serta penggunaan dalam keadaan full load dari beberapa komponen CPU, di antaranya adalah processor, memory, dan VGA. Suhu maksimum yang dimiliki processor atau biasa disebut critical temperatures dan CPU utilization yang menggambarkan kinerja processor dapat dijadikan acuan seberapa optimal processor bekerja. Salah satu cara untuk menurunkan suhu processor adalah dengan menambahkan heat sink dan kipas di daerah sekitar processor. Energi panas dari processor ditransferkan melalui heat sink dengan cara absorpsi, proses transfer panas konduksi dan konveksi. Proses konveksi paksa dari heat sink ke udara lingkungan akan dibantu menggunakan kipas. Kecepatan kipas diatur menggunakan kontrol Proporsional, kontrol Integral, dan kontrol Derivatif (PID). Penentuan parameter kontrol PID menggunakan metode kurva Ziegler Nichols, simulasi uji coba variasi nilai parameter kontrol PID menggunakan software MATLAB, eksperimen pada sistem dan juga pemodelan menggunakan software Comsol Multiphysics 4.4. Berdasarkan penelitian ini dapat disimpulkan bahwa suhu dapat mencapai kestabilan lebih cepat pada saat diaplikasikan kontrol PID dengan nilai parameter Kp = 40, Ki = 33.33, Kd = 4, suhu stabil 324 K tercapai dalam waktu 500 s. Sedangkan tanpa kontrol PID suhu stabil pada 326 K tercapai dalam waktu 3000 s. Kata kunci: transfer panas, konveksi paksa, kontrol PID

A Novel Mitigation Method for Noise-Induced Temperature Error in CPU Thermal Control

It has been reported that in the thermal control of real-time computing systems, zero-mean thermal sensor noise can induce a significant steady-state error between the target and actual temperatures of a CPU. Unlike the usual case of zero-mean sensor noise resulting in zero-mean temperature fluctuations around the target value, this noise-induced temperature error manifests in the form of a bias, i.e., the mean of the error is not zero. Existing work has analyzed the main cause of this error and produced a solution, known as TCUB-VS. However, this existing solution has a few drawbacks: the transient response is sluggish, and the exact value of the noise standard deviation is necessary in the design stage. In this paper, we propose a novel method of avoiding noise-induced temperature error while overcoming the limitations of the existing work. The proposed method uses an estimated CPU temperature for the part of the controller that is sensitive to noise while using actual measurements for the other part of the controller. In this way, our proposed method eliminates noise-induced temperature error and overcomes the drawbacks of the existing work. To show the efficacy of our proposed method, theoretical results are obtained using a stochastic averaging approach, and experimental results are presented along with simulations.1

On the Optimality of RM and EDF for Non-Preemptive Real-Time Harmonic Tasks

ABSTRACT In this paper, we study non-preemptive uniprocessor realtime scheduling using the non-preemptive RM (npRM) and EDF (npEDF) scheduling algorithms. We discuss the limitations of existing studies, identifying pessimism in current schedulability analysis and inefficiencies in existing processor speedup results. Focusing on harmonic task sets, we show that even with restrictions placed on the execution times of the tasks, npRM and npEDF are not able to schedule all feasible task sets. We obtain necessary conditions for the feasibility of the harmonic tasks with arbitrary integer period ratios. Then we derive sufficient conditions for the schedulability of npRM and npEDF upon harmonic task sets. Based on these conditions, a superior speedup factor which guarantees the schedulability in cases where there are fewer restrictions on the execution times is derived. Results from simulation experiments show an average speedup factor three times less than the only existing feasible method to obtain speedup factor

Software development of reconfigurable real-time systems : from specification to implementation

This thesis deals with reconfigurable real-time systems solving real-time tasks scheduling problems in a mono-core and multi-core architectures. The main focus in this thesis is on providing guidelines, methods, and tools for the synthesis of feasible reconfigurable real-time systems in a mono-processor and multi-processor architectures. The development of these systems faces various challenges particularly in terms of stability, energy consumption, response and blocking time. To address this problem, we propose in this work a new strategy of i) placement and scheduling of tasks to execute real-time applications on mono-core and multi-core architectures, ii) optimization step based on Mixed integer linear programming (MILP), and iii) guidance tool that assists designers to implement a feasible multi-core reconfigurable real-time from specification level to implementation level. We apply and simulate the contribution to a case study, and compare the proposed results with related works in order to show the originality of this methodology.Echtzeitsysteme laufen unter harten Bedingungen an ihre Ausführungszeit. Die Einhaltung der Echtzeit-Bedingungen bestimmt die Zuverlässigkeit und Genauigkeit dieser Systeme. Neben den Echtzeit-Bedingungen müssen rekonfigurierbare Echtzeitsysteme zusätzliche Rekonfigurations-Bedingungen erfüllen. Diese Arbeit beschäftigt sich mit rekonfigurierbaren Echtzeitsystemen in Mono- und Multicore-Architekturen. An die Entwicklung dieser Systeme sind verschiedene Anforderungen gestellt. Insbesondere muss die Rekonfigurierbarkeit beachtet werden. Dabei sind aber Echtzeit-Bedingungen und Ressourcenbeschränkungen weiterhin zu beachten. Darüber hinaus werden die Kosten für die Entwicklung dieser Systeme insbesondere durch falsche Designentscheidungen in den frühen Phasen der Entwicklung stark beeinträchtigt. Das Hauptziel in dieser Arbeit liegt deshalb auf der Bereitstellung von Handlungsempfehlungen, Methoden und Werkzeugen für die zielgerichtete Entwicklung von realisierbaren rekonfigurierbaren Echtzeitsystemen in Mono- und Multicore-Architekturen. Um diese Herausforderungen zu adressieren wird eine neue Strategie vorgeschlagen, die 1) die Funktionsallokation, 2) die Platzierung und das Scheduling von Tasks, 3) einen Optimierungsschritt auf der Basis von Mixed Integer Linear Programming (MILP) und 4) eine entscheidungsunterstützende Lösung umfasst, die den Designern hilft, eine realisierbare rekonfigurierbare Echtzeitlösung von der Spezifikationsebene bis zur Implementierungsebene zu entwickeln. Die vorgeschlagene Methodik wird auf eine Fallstudie angewendet und mit verwandten Arbeiten vergliche

Abordagens para reconfiguração de sistemas de tempo real com QoS e restrições de energia e temperatura

Tese (doutorado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia de Automação e Sistemas, Florianópolis, 2015.Esta tese propõe uma infraestrutura para alocação dinâmica de recursos do processador em sistemas de tempo real com tarefas multi-modais ou não, sob restrições de escalonabilidade, consumo de energia e temperatura. Tal infraestrutura pode ser usada para sistemas de tempo real crítico, não crítico e sistemas embarcados que necessitam de garantia de economia de energia. A alocação dinâmica é modelada como um problema de otimização discreto e contínuo (convexos e lineares po rparte) para os quais foram analisados algoritmos eficientes para resolução do problema.Embora o problema discreto formulado seja NP-Difícil, os outros possuem soluções eficientes conhecidas e as análises numéricas e simulações mostraram que os modelos usados alcançam bons resultados, com baixo custo computacional.Abstract : This thesis proposes a framework for dynamic reconfiguration, value-based processor resource allocation in multi-modal or not real-time applications, under schedulability, energy consumption and temperature constraints. The framework is suitable for critical and soft real-time adaptive embedded systems which need guarantees of energy savings. The dynamic allocation is formulated as a discrete and continuous (convex and piecewise linear) optimization problem for which efficients algorithms were tested. Although the discrete problem is NP-Hard, the others have efficient solution and numerical analysis and simulations have shown that the used algorithms and models achieves very good results, with low computational cost

Thermal and QoS-Aware Embedded Systems

While embedded systems such as smartphones and smart cars become essential parts of our lives, they face urgent thermal challenges. Extreme thermal conditions (i.e., both high and low temperatures) degrade system reliability, even risking safety; devices in the cold environments unexpectedly go offline, whereas extremely high device temperatures can cause device failures or battery explosions. These thermal limits become close to the norm because of ever-increasing chip power densities and application complexities. Embedded systems in the wild, however, lack adaptive and effective solutions to overcome such thermal challenges. An adaptive thermal management solution must cope with various runtime thermal scenarios under a changing ambient temperature. An effective solution requires the understanding of the dynamic thermal behaviors of underlying hardware and application workloads to ensure thermal and application quality-of-service (QoS) requirements. This thesis proposes a suite of adaptive and effective thermal management solutions to address different aspects of real-world thermal challenges faced by modern embedded systems. First, we present BPM, a battery-aware power management framework for mobile devices to address the unexpected device shutoffs in cold environments. We develop BPM as a background service that characterizes and controls real-time battery behaviors to maintain operable conditions even in cold environments. We then propose eTEC, building on the thermoelectric cooling solution, which adaptively controls cooling and computational power to avoid mobile devices overheating. For the real-time embedded systems such as cars, we present RT-TRM, a thermal-aware resource management framework that monitors changing ambient temperatures and allocates system resources to individual tasks. Next, we target in-vehicle vision systems running on CPUs–GPU system-on-chips and develop CPU–GPU co-scheduling to tackle thermal imbalance across CPUs caused by GPU heat. We evaluate all of these solutions using representative mobile/automotive platforms and workloads, demonstrating their effectiveness in meeting thermal and QoS requirements.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/153350/1/ymoonlee_1.pd

Quasilinear Control Theory for Systems with Asymmetric Actuators and Sensors.

Quasilinear Control (QLC) theory provides a set of methods for analysis and design of systems with nonlinear actuators and sensors. In practice, actuators always saturate and sensors often have deadzone or quantization. One limitation of the current QLC theory is that it is applicable only to systems with symmetric nonlinearities. In many situations, however, nonlinearities are asymmetric. Examples of such systems abound: air-conditioning/heating systems, automotive torque and idle speed control, wind turbine control, etc. In this work, we provide an extension of the QLC theory to the asymmetric case. Similar to the symmetric case, the approach is based on the method of stochastic linearization, which replaces nonlinear systems by quasilinear ones. Unlike the symmetric case, however, stochastic linearization in the asymmetric case replaces each nonlinearity not only by an equivalent gain, but also by an equivalent bias. The latter leads to steady state errors incompatible with the usual error coefficients predicted by linear systems theory. For this reason, the extension to the asymmetric case is non-trivial. Specific problems addressed in this dissertation with regards to asymmetric systems are: (i) Introduction and investigation of the notion of asymmetry. (ii) Development of a formalism of stochastic linearization for systems at hand. (iii) Analysis of tracking and disturbance rejection performance. (iv) Introduction and investigation of performance loci, i.e., root locus and tracking error locus. (v) Utilization of the performance loci for random reference and step reference tracking controller design. (vi) Recovery of linear performance in nonlinear systems. (vii) Disturbance rejection controller design using an LQR-type approach. (viii) Application of the methods developed to a wind farm controller design. In addition, a Matlab-based toolbox that implements most of the QLC methods has been developed and is available at www.QuasilinearControl.com.PhDElectrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/99805/1/hamido_1.pd