82 research outputs found

    Lifetime reliability of multi-core systems: modeling and applications.

    Get PDF
    Huang, Lin.Thesis (M.Phil.)--Chinese University of Hong Kong, 2011.Includes bibliographical references (leaves 218-232).Abstracts in English and Chinese.Abstract --- p.iAcknowledgement --- p.ivChapter 1 --- Introduction --- p.1Chapter 1.1 --- Preface --- p.1Chapter 1.2 --- Background --- p.5Chapter 1.3 --- Contributions --- p.6Chapter 1.3.1 --- Lifetime Reliability Modeling --- p.6Chapter 1.3.2 --- Simulation Framework --- p.7Chapter 1.3.3 --- Applications --- p.9Chapter 1.4 --- Thesis Outline --- p.10Chapter I --- Modeling --- p.12Chapter 2 --- Lifetime Reliability Modeling --- p.13Chapter 2.1 --- Notation --- p.13Chapter 2.2 --- Assumption --- p.16Chapter 2.3 --- Introduction --- p.16Chapter 2.4 --- Related Work --- p.19Chapter 2.5 --- System Model --- p.21Chapter 2.5.1 --- Reliability of A Surviving Component --- p.22Chapter 2.5.2 --- Reliability of a Hybrid k-out-of-n:G System --- p.26Chapter 2.6 --- Special Cases --- p.31Chapter 2.6.1 --- Case I: Gracefully Degrading System --- p.31Chapter 2.6.2 --- Case II: Standby Redundant System --- p.33Chapter 2.6.3 --- Case III: l-out-of-3:G System with --- p.34Chapter 2.7 --- Numerical Results --- p.37Chapter 2.7.1 --- Experimental Setup --- p.37Chapter 2.7.2 --- Experimental Results and Discussion --- p.40Chapter 2.8 --- Conclusion --- p.43Chapter 2.9 --- Appendix --- p.44Chapter II --- Simulation Framework --- p.47Chapter 3 --- AgeSim: A Simulation Framework --- p.48Chapter 3.1 --- Introduction --- p.48Chapter 3.2 --- Preliminaries and Motivation --- p.51Chapter 3.2.1 --- Prior Work on Lifetime Reliability Analysis of Processor- Based Systems --- p.51Chapter 3.2.2 --- Motivation of This Work --- p.53Chapter 3.3 --- The Proposed Framework --- p.54Chapter 3.4 --- Aging Rate Calculation --- p.57Chapter 3.4.1 --- Lifetime Reliability Calculation --- p.58Chapter 3.4.2 --- Aging Rate Extraction --- p.60Chapter 3.4.3 --- Discussion on Representative Workload --- p.63Chapter 3.4.4 --- Numerical Validation --- p.65Chapter 3.4.5 --- Miscellaneous --- p.66Chapter 3.5 --- Lifetime Reliability Model for MPSoCs with Redundancy --- p.68Chapter 3.6 --- Case Studies --- p.70Chapter 3.6.1 --- Dynamic Voltage and Frequency Scaling --- p.71Chapter 3.6.2 --- Burst Task Arrival --- p.75Chapter 3.6.3 --- Task Allocation on Multi-Core Processors --- p.77Chapter 3.6.4 --- Timeout Policy on Multi-Core Processors with Gracefully Degrading Redundancy --- p.78Chapter 3.7 --- Conclusion --- p.79Chapter 4 --- Evaluating Redundancy Schemes --- p.83Chapter 4.1 --- Introduction --- p.83Chapter 4.2 --- Preliminaries and Motivation --- p.85Chapter 4.2.1 --- Failure Mechanisms --- p.85Chapter 4.2.2 --- Related Work and Motivation --- p.86Chapter 4.3 --- Proposed Analytical Model for the Lifetime Reliability of Proces- sor Cores --- p.88Chapter 4.3.1 --- "Impact of Temperature, Voltage, and Frequency" --- p.88Chapter 4.3.2 --- Impact of Workloads --- p.92Chapter 4.4 --- Lifetime Reliability Analysis for Multi-core Processors with Vari- ous Redundancy Schemes --- p.95Chapter 4.4.1 --- Gracefully Degrading System (GDS) --- p.95Chapter 4.4.2 --- Processor Rotation System (PRS) --- p.97Chapter 4.4.3 --- Standby Redundant System (SRS) --- p.98Chapter 4.4.4 --- Extension to Heterogeneous System --- p.99Chapter 4.5 --- Experimental Methodology --- p.101Chapter 4.5.1 --- Workload Description --- p.102Chapter 4.5.2 --- Temperature Distribution Extraction --- p.102Chapter 4.5.3 --- Reliability Factors --- p.103Chapter 4.6 --- Results and Discussions --- p.103Chapter 4.6.1 --- Wear-out Rate Computation --- p.103Chapter 4.6.2 --- Comparison on Lifetime Reliability --- p.105Chapter 4.6.3 --- Comparison on Performance --- p.110Chapter 4.6.4 --- Comparison on Expected Computation Amount --- p.112Chapter 4.7 --- Conclusion --- p.118Chapter III --- Applications --- p.119Chapter 5 --- Task Allocation and Scheduling for MPSoCs --- p.120Chapter 5.1 --- Introduction --- p.120Chapter 5.2 --- Prior Work and Motivation --- p.122Chapter 5.2.1 --- IC Lifetime Reliability --- p.122Chapter 5.2.2 --- Task Allocation and Scheduling for MPSoC Designs --- p.124Chapter 5.3 --- Proposed Task Allocation and Scheduling Strategy --- p.126Chapter 5.3.1 --- Problem Definition --- p.126Chapter 5.3.2 --- Solution Representation --- p.128Chapter 5.3.3 --- Cost Function --- p.129Chapter 5.3.4 --- Simulated Annealing Process --- p.130Chapter 5.4 --- Lifetime Reliability Computation for MPSoC Embedded Systems --- p.133Chapter 5.5 --- Efficient MPSoC Lifetime Approximation --- p.138Chapter 5.5.1 --- Speedup Technique I - Multiple Periods --- p.139Chapter 5.5.2 --- Speedup Technique II - Steady Temperature --- p.139Chapter 5.5.3 --- Speedup Technique III - Temperature Pre- calculation --- p.140Chapter 5.5.4 --- Speedup Technique IV - Time Slot Quantity Control --- p.144Chapter 5.6 --- Experimental Results --- p.144Chapter 5.6.1 --- Experimental Setup --- p.144Chapter 5.6.2 --- Results and Discussion --- p.146Chapter 5.7 --- Conclusion and Future Work --- p.152Chapter 6 --- Energy-Efficient Task Allocation and Scheduling --- p.154Chapter 6.1 --- Introduction --- p.154Chapter 6.2 --- Preliminaries and Problem Formulation --- p.157Chapter 6.2.1 --- Related Work --- p.157Chapter 6.2.2 --- Problem Formulation --- p.159Chapter 6.3 --- Analytical Models --- p.160Chapter 6.3.1 --- Performance and Energy Models for DVS-Enabled Pro- cessors --- p.160Chapter 6.3.2 --- Lifetime Reliability Model --- p.163Chapter 6.4 --- Proposed Algorithm for Single-Mode Embedded Systems --- p.165Chapter 6.4.1 --- Task Allocation and Scheduling --- p.165Chapter 6.4.2 --- Voltage Assignment for DVS-Enabled Processors --- p.168Chapter 6.5 --- Proposed Algorithm for Multi-Mode Embedded Systems --- p.169Chapter 6.5.1 --- Feasible Solution Set --- p.169Chapter 6.5.2 --- Searching Procedure for a Single Mode --- p.171Chapter 6.5.3 --- Feasible Solution Set Identification --- p.171Chapter 6.5.4 --- Multi-Mode Combination --- p.177Chapter 6.6 --- Experimental Results --- p.178Chapter 6.6.1 --- Experimental Setup --- p.178Chapter 6.6.2 --- Case Study --- p.180Chapter 6.6.3 --- Sensitivity Analysis --- p.181Chapter 6.6.4 --- Extensive Results --- p.183Chapter 6.7 --- Conclusion --- p.185Chapter 7 --- Customer-Aware Task Allocation and Scheduling --- p.186Chapter 7.1 --- Introduction --- p.186Chapter 7.2 --- Prior Work and Problem Formulation --- p.188Chapter 7.2.1 --- Related Work and Motivation --- p.188Chapter 7.2.2 --- Problem Formulation --- p.191Chapter 7.3 --- Proposed Design-Stage Task Allocation and Scheduling --- p.192Chapter 7.3.1 --- Solution Representation and Moves --- p.193Chapter 7.3.2 --- Cost Function --- p.196Chapter 7.3.3 --- Impact of DVFS --- p.198Chapter 7.4 --- Proposed Algorithm for Online Adjustment --- p.200Chapter 7.4.1 --- Reliability Requirement for Online Adjustment --- p.201Chapter 7.4.2 --- Analytical Model --- p.203Chapter 7.4.3 --- Overall Flow --- p.204Chapter 7.5 --- Experimental Results --- p.205Chapter 7.5.1 --- Experimental Setup --- p.205Chapter 7.5.2 --- Results and Discussion --- p.207Chapter 7.6 --- Conclusion --- p.211Chapter 7.7 --- Appendix --- p.211Chapter 8 --- Conclusion and Future Work --- p.214Chapter 8.1 --- Conclusion --- p.214Chapter 8.2 --- Future Work --- p.215Bibliography --- p.23

    Self-adaptivity of applications on network on chip multiprocessors: the case of fault-tolerant Kahn process networks

    Get PDF
    Technology scaling accompanied with higher operating frequencies and the ability to integrate more functionality in the same chip has been the driving force behind delivering higher performance computing systems at lower costs. Embedded computing systems, which have been riding the same wave of success, have evolved into complex architectures encompassing a high number of cores interconnected by an on-chip network (usually identified as Multiprocessor System-on-Chip). However these trends are hindered by issues that arise as technology scaling continues towards deep submicron scales. Firstly, growing complexity of these systems and the variability introduced by process technologies make it ever harder to perform a thorough optimization of the system at design time. Secondly, designers are faced with a reliability wall that emerges as age-related degradation reduces the lifetime of transistors, and as the probability of defects escaping post-manufacturing testing is increased. In this thesis, we take on these challenges within the context of streaming applications running in network-on-chip based parallel (not necessarily homogeneous) systems-on-chip that adopt the no-remote memory access model. In particular, this thesis tackles two main problems: (1) fault-aware online task remapping, (2) application-level self-adaptation for quality management. For the former, by viewing fault tolerance as a self-adaptation aspect, we adopt a cross-layer approach that aims at graceful performance degradation by addressing permanent faults in processing elements mostly at system-level, in particular by exploiting redundancy available in multi-core platforms. We propose an optimal solution based on an integer linear programming formulation (suitable for design time adoption) as well as heuristic-based solutions to be used at run-time. We assess the impact of our approach on the lifetime reliability. We propose two recovery schemes based on a checkpoint-and-rollback and a rollforward technique. For the latter, we propose two variants of a monitor-controller- adapter loop that adapts application-level parameters to meet performance goals. We demonstrate not only that fault tolerance and self-adaptivity can be achieved in embedded platforms, but also that it can be done without incurring large overheads. In addressing these problems, we present techniques which have been realized (depending on their characteristics) in the form of a design tool, a run-time library or a hardware core to be added to the basic architecture

    Predictable multi-processor system on chip design for multimedia applications

    Get PDF
    The design of multimedia systems has become increasingly complex due to consumer requirements. Consumers demand the functionalities offered by a huge desktop from these systems. Many of these systems are mobile. Therefore, power consumption and size of these devices should be small. These systems are increasingly becoming multi-processor based (MPSoCs) for the reasons of power and performance. Applications execute on these systems in different combinations also known as use-cases. Applications may have different performance requirements in each use-case. Currently, verification of all these use-cases takes bulk of the design effort. There is a need for analysis based techniques so that the platforms have a predictable behaviour and in turn provide guarantees on performance without expending precious man hours on verification. In this dissertation, techniques and architectures have been developed to design and manage these multi-processor based systems efficiently. The dissertation presents predictable architectural components for MPSoCs, a Predictable MPSoC design strategy, automatic platform synthesis tool, a run-time system and an MPSoC simulation technique. The introduction of predictability helps in rapid design of MPSoC platforms. Chapter 1 of the thesis studies the trends in modern multimedia applications and processor architectures. The chapter further highlights the problems in the design of MPSoC platforms and emphasizes the need of predictable design techniques. Predictable design techniques require predictable application and architectural components. The chapter further elaborates on Synchronous Data Flow Graphs which are used to model the applications throughout this thesis. The chapter presents the architecture template used in this thesis and enlists the contributions of the thesis. One of the contributions of this thesis is the design of a predictable component called communication assist. Chapter 2 of the thesis describes the architecture of this communication assist. The communication assist presented in this thesis not only decouples the communication from computation but also provides timing guarantees. Based on this communication assist, an MPSoC platform generation technique has been presented that can design MPSoC platforms capable of satisfying the throughput constraints of multiple applications in all use-cases. The technique is presented in Chapter 3. The design strategy uses three simple steps for platform design. In the first step it finds the required number of processors. The second step minimizes the communication interconnect between the processors and the third step minimizes the communication memory requirement of the platform. Further in Chapter 4, a tool has been developed to generate CA-based platforms for FPGAs. The output of this tool can be used to synthesize platforms on real hardware with the help of FPGA synthesis tools. The applications executing on these platforms often exhibit dynamism e.g. variation in task execution times and change in application throughput requirements. Further, new applications may often be added by consumers at run-time. Resource managers have been presented in literature to handle such dynamic situations. However, the scalability of these resource managers becomes an issue with the increase in number of processors and applications. Chapter 5 presents distributed run-time resource management techniques. Two versions of distributed resource managers have been presented which are scalable with the number of applications and processors. MPSoC platforms for real-time applications are designed assuming worst-case task execution times. It is known that the difference between average-case and worst-case behaviour can be quite large. Therefore, knowing the average case performance is also important for the system designer, and software simulation is often employed to estimate this. However, simulation in software is slow and does not scale with the number of applications and processing elements. In Chapter 6, a fast and scalable simulation methodology is introduced that can simulate the execution of multiple applications on an MPSoC platform. It is based on parallel execution of SDF (Synchronous Data Flow) models of applications. The simulation methodology uses Parallel Discrete Event Simulation (PDES) primitives and it is termed as "Smart Conservative PDES". The methodology generates a parallel simulator which is synthesizable on FPGAs. The framework can also be used to model dynamic arbitration policies which are difficult to analyse using models. The generated platform is also useful in carrying out Design Space Exploration as shown in the thesis. Finally, Chapter 7 summarizes the main findings and (practical) implications of the studies described in previous chapters of this dissertation. Using the contributions mentioned in the thesis, a designer can design and implement predictable multiprocessor based systems capable of satisfying throughput constraints of multiple applications in given set of use-cases, and employ resource management strategies to deal with dynamism in the applications. The chapter also describes the main limitations of this dissertation and makes suggestions for future research

    Efficient Power Management for Heterogeneous Multi-Core Architectures

    Get PDF
    Ph.DDOCTOR OF PHILOSOPH

    Dependable Embedded Systems

    Get PDF
    This Open Access book introduces readers to many new techniques for enhancing and optimizing reliability in embedded systems, which have emerged particularly within the last five years. This book introduces the most prominent reliability concerns from todayโ€™s points of view and roughly recapitulates the progress in the community so far. Unlike other books that focus on a single abstraction level such circuit level or system level alone, the focus of this book is to deal with the different reliability challenges across different levels starting from the physical level all the way to the system level (cross-layer approaches). The book aims at demonstrating how new hardware/software co-design solution can be proposed to ef-fectively mitigate reliability degradation such as transistor aging, processor variation, temperature effects, soft errors, etc. Provides readers with latest insights into novel, cross-layer methods and models with respect to dependability of embedded systems; Describes cross-layer approaches that can leverage reliability through techniques that are pro-actively designed with respect to techniques at other layers; Explains run-time adaptation and concepts/means of self-organization, in order to achieve error resiliency in complex, future many core systems

    Embedded System Design

    Get PDF
    A unique feature of this open access textbook is to provide a comprehensive introduction to the fundamental knowledge in embedded systems, with applications in cyber-physical systems and the Internet of things. It starts with an introduction to the field and a survey of specification models and languages for embedded and cyber-physical systems. It provides a brief overview of hardware devices used for such systems and presents the essentials of system software for embedded systems, including real-time operating systems. The author also discusses evaluation and validation techniques for embedded systems and provides an overview of techniques for mapping applications to execution platforms, including multi-core platforms. Embedded systems have to operate under tight constraints and, hence, the book also contains a selected set of optimization techniques, including software optimization techniques. The book closes with a brief survey on testing. This fourth edition has been updated and revised to reflect new trends and technologies, such as the importance of cyber-physical systems (CPS) and the Internet of things (IoT), the evolution of single-core processors to multi-core processors, and the increased importance of energy efficiency and thermal issues

    ํ˜‘์—… ๋กœ๋ด‡์„ ์œ„ํ•œ ์„œ๋น„์Šค ๊ธฐ๋ฐ˜๊ณผ ๋ชจ๋ธ ๊ธฐ๋ฐ˜์˜ ์†Œํ”„ํŠธ์›จ์–ด ๊ฐœ๋ฐœ ๋ฐฉ๋ฒ•๋ก 

    Get PDF
    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :๊ณต๊ณผ๋Œ€ํ•™ ์ „๊ธฐยท์ปดํ“จํ„ฐ๊ณตํ•™๋ถ€,2020. 2. ํ•˜์ˆœํšŒ.๊ฐ€๊นŒ์šด ๋ฏธ๋ž˜์—๋Š” ๋‹ค์–‘ํ•œ ๋กœ๋ด‡์ด ๋‹ค์–‘ํ•œ ๋ถ„์•ผ์—์„œ ํ•˜๋‚˜์˜ ์ž„๋ฌด๋ฅผ ํ˜‘๋ ฅํ•˜์—ฌ ์ˆ˜ํ–‰ํ•˜๋Š” ๋ชจ์Šต์€ ํ”ํžˆ ๋ณผ ์ˆ˜ ์žˆ๊ฒŒ ๋  ๊ฒƒ์ด๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์‹ค์ œ๋กœ ์ด๋Ÿฌํ•œ ๋ชจ์Šต์ด ์‹คํ˜„๋˜๊ธฐ์—๋Š” ๋‘ ๊ฐ€์ง€์˜ ์–ด๋ ค์›€์ด ์žˆ๋‹ค. ๋จผ์ € ๋กœ๋ด‡์„ ์šด์šฉํ•˜๊ธฐ ์œ„ํ•œ ์†Œํ”„ํŠธ์›จ์–ด๋ฅผ ๋ช…์„ธํ•˜๋Š” ๊ธฐ์กด ์—ฐ๊ตฌ๋“ค์€ ๋Œ€๋ถ€๋ถ„ ๊ฐœ๋ฐœ์ž๊ฐ€ ๋กœ๋ด‡์˜ ํ•˜๋“œ์›จ์–ด์™€ ์†Œํ”„ํŠธ์›จ์–ด์— ๋Œ€ํ•œ ์ง€์‹์„ ์•Œ๊ณ  ์žˆ๋Š” ๊ฒƒ์„ ๊ฐ€์ •ํ•˜๊ณ  ์žˆ๋‹ค. ๊ทธ๋ž˜์„œ ๋กœ๋ด‡์ด๋‚˜ ์ปดํ“จํ„ฐ์— ๋Œ€ํ•œ ์ง€์‹์ด ์—†๋Š” ์‚ฌ์šฉ์ž๋“ค์ด ์—ฌ๋Ÿฌ ๋Œ€์˜ ๋กœ๋ด‡์ด ํ˜‘๋ ฅํ•˜๋Š” ์‹œ๋‚˜๋ฆฌ์˜ค๋ฅผ ์ž‘์„ฑํ•˜๊ธฐ๋Š” ์‰ฝ์ง€ ์•Š๋‹ค. ๋˜ํ•œ, ๋กœ๋ด‡์˜ ์†Œํ”„ํŠธ์›จ์–ด๋ฅผ ๊ฐœ๋ฐœํ•  ๋•Œ ๋กœ๋ด‡์˜ ํ•˜๋“œ์›จ์–ด์˜ ํŠน์„ฑ๊ณผ ๊ด€๋ จ์ด ๊นŠ์–ด์„œ, ๋‹ค์–‘ํ•œ ๋กœ๋ด‡์˜ ์†Œํ”„ํŠธ์›จ์–ด๋ฅผ ๊ฐœ๋ฐœํ•˜๋Š” ๊ฒƒ๋„ ๊ฐ„๋‹จํ•˜์ง€ ์•Š๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์ƒ์œ„ ์ˆ˜์ค€์˜ ๋ฏธ์…˜ ๋ช…์„ธ์™€ ๋กœ๋ด‡์˜ ํ–‰์œ„ ํ”„๋กœ๊ทธ๋ž˜๋ฐ์œผ๋กœ ๋‚˜๋ˆ„์–ด ์ƒˆ๋กœ์šด ์†Œํ”„ํŠธ์›จ์–ด ๊ฐœ๋ฐœ ํ”„๋ ˆ์ž„์›Œํฌ๋ฅผ ์ œ์•ˆํ•œ๋‹ค. ๋˜ํ•œ, ๋ณธ ํ”„๋ ˆ์ž„์›Œํฌ๋Š” ํฌ๊ธฐ๊ฐ€ ์ž‘์€ ๋กœ๋ด‡๋ถ€ํ„ฐ ๊ณ„์‚ฐ ๋Šฅ๋ ฅ์ด ์ถฉ๋ถ„ํ•œ ๋กœ๋ด‡๋“ค์ด ์„œ๋กœ ๊ตฐ์ง‘์„ ์ด๋ฃจ์–ด ๋ฏธ์…˜์„ ์ˆ˜ํ–‰ํ•  ์ˆ˜ ์žˆ๋„๋ก ์ง€์›ํ•œ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๋กœ๋ด‡์˜ ํ•˜๋“œ์›จ์–ด๋‚˜ ์†Œํ”„ํŠธ์›จ์–ด์— ๋Œ€ํ•œ ์ง€์‹์ด ๋ถ€์กฑํ•œ ์‚ฌ์šฉ์ž๋„ ๋กœ๋ด‡์˜ ๋™์ž‘์„ ์ƒ์œ„ ์ˆ˜์ค€์—์„œ ๋ช…์„ธํ•  ์ˆ˜ ์žˆ๋Š” ์Šคํฌ๋ฆฝํŠธ ์–ธ์–ด๋ฅผ ์ œ์•ˆํ•œ๋‹ค. ์ œ์•ˆํ•˜๋Š” ์–ธ์–ด๋Š” ๊ธฐ์กด์˜ ์Šคํฌ๋ฆฝํŠธ ์–ธ์–ด์—์„œ๋Š” ์ง€์›ํ•˜์ง€ ์•Š๋Š” ๋„ค ๊ฐ€์ง€์˜ ๊ธฐ๋Šฅ์ธ ํŒ€์˜ ๊ตฌ์„ฑ, ๊ฐ ํŒ€์˜ ์„œ๋น„์Šค ๊ธฐ๋ฐ˜ ํ”„๋กœ๊ทธ๋ž˜๋ฐ, ๋™์ ์œผ๋กœ ๋ชจ๋“œ ๋ณ€๊ฒฝ, ๋‹ค์ค‘ ์ž‘์—…(๋ฉ€ํ‹ฐ ํƒœ์Šคํ‚น)์„ ์ง€์›ํ•œ๋‹ค. ์šฐ์„  ๋กœ๋ด‡์€ ํŒ€์œผ๋กœ ๊ทธ๋ฃน ์ง€์„ ์ˆ˜ ์žˆ๊ณ , ๋กœ๋ด‡์ด ์ˆ˜ํ–‰ํ•  ์ˆ˜ ์žˆ๋Š” ๊ธฐ๋Šฅ์„ ์„œ๋น„์Šค ๋‹จ์œ„๋กœ ์ถ”์ƒํ™”ํ•˜์—ฌ ์ƒˆ๋กœ์šด ๋ณตํ•ฉ ์„œ๋น„์Šค๋ฅผ ๋ช…์„ธํ•  ์ˆ˜ ์žˆ๋‹ค. ๋˜ํ•œ ๋กœ๋ด‡์˜ ๋ฉ€ํ‹ฐ ํƒœ์Šคํ‚น์„ ์œ„ํ•ด 'ํ”Œ๋žœ' ์ด๋ผ๋Š” ๊ฐœ๋…์„ ๋„์ž…ํ•˜์˜€๊ณ , ๋ณตํ•ฉ ์„œ๋น„์Šค ๋‚ด์—์„œ ์ด๋ฒคํŠธ๋ฅผ ๋ฐœ์ƒ์‹œ์ผœ์„œ ๋™์ ์œผ๋กœ ๋ชจ๋“œ๊ฐ€ ๋ณ€ํ™˜ํ•  ์ˆ˜ ์žˆ๋„๋ก ํ•˜์˜€๋‹ค. ๋‚˜์•„๊ฐ€ ์—ฌ๋Ÿฌ ๋กœ๋ด‡์˜ ํ˜‘๋ ฅ์ด ๋”์šฑ ๊ฒฌ๊ณ ํ•˜๊ณ , ์œ ์—ฐํ•˜๊ณ , ํ™•์žฅ์„ฑ์„ ๋†’์ด๊ธฐ ์œ„ํ•ด, ๊ตฐ์ง‘ ๋กœ๋ด‡์„ ์šด์šฉํ•  ๋•Œ ๋กœ๋ด‡์ด ์ž„๋ฌด๋ฅผ ์ˆ˜ํ–‰ํ•˜๋Š” ๋„์ค‘์— ๋ฌธ์ œ๊ฐ€ ์ƒ๊ธธ ์ˆ˜ ์žˆ์œผ๋ฉฐ, ์ƒํ™ฉ์— ๋”ฐ๋ผ ๋กœ๋ด‡์„ ๋™์ ์œผ๋กœ ๋‹ค๋ฅธ ํ–‰์œ„๋ฅผ ์ˆ˜ํ–‰ํ•  ์ˆ˜ ์žˆ๋‹ค๊ณ  ๊ฐ€์ •ํ•œ๋‹ค. ์ด๋ฅผ ์œ„ํ•ด ๋™์ ์œผ๋กœ๋„ ํŒ€์„ ๊ตฌ์„ฑํ•  ์ˆ˜ ์žˆ๊ณ , ์—ฌ๋Ÿฌ ๋Œ€์˜ ๋กœ๋ด‡์ด ํ•˜๋‚˜์˜ ์„œ๋น„์Šค๋ฅผ ์ˆ˜ํ–‰ํ•˜๋Š” ๊ทธ๋ฃน ์„œ๋น„์Šค๋ฅผ ์ง€์›ํ•˜๊ณ , ์ผ๋Œ€ ๋‹ค ํ†ต์‹ ๊ณผ ๊ฐ™์€ ์ƒˆ๋กœ์šด ๊ธฐ๋Šฅ์„ ์Šคํฌ๋ฆฝํŠธ ์–ธ์–ด์— ๋ฐ˜์˜ํ•˜์˜€๋‹ค. ๋”ฐ๋ผ์„œ ํ™•์žฅ๋œ ์ƒ์œ„ ์ˆ˜์ค€์˜ ์Šคํฌ๋ฆฝํŠธ ์–ธ์–ด๋Š” ๋น„์ „๋ฌธ๊ฐ€๋„ ๋‹ค์–‘ํ•œ ์œ ํ˜•์˜ ํ˜‘๋ ฅ ์ž„๋ฌด๋ฅผ ์‰ฝ๊ฒŒ ๋ช…์„ธํ•  ์ˆ˜ ์žˆ๋‹ค. ๋กœ๋ด‡์˜ ํ–‰์œ„๋ฅผ ํ”„๋กœ๊ทธ๋ž˜๋ฐํ•˜๊ธฐ ์œ„ํ•ด ๋‹ค์–‘ํ•œ ์†Œํ”„ํŠธ์›จ์–ด ๊ฐœ๋ฐœ ํ”„๋ ˆ์ž„์›Œํฌ๊ฐ€ ์—ฐ๊ตฌ๋˜๊ณ  ์žˆ๋‹ค. ํŠนํžˆ ์žฌ์‚ฌ์šฉ์„ฑ๊ณผ ํ™•์žฅ์„ฑ์„ ์ค‘์ ์œผ๋กœ ๋‘” ์—ฐ๊ตฌ๋“ค์ด ์ตœ๊ทผ ๋งŽ์ด ์‚ฌ์šฉ๋˜๊ณ  ์žˆ์ง€๋งŒ, ๋Œ€๋ถ€๋ถ„์˜ ์ด๋“ค ์—ฐ๊ตฌ๋Š” ๋ฆฌ๋ˆ…์Šค ์šด์˜์ฒด์ œ์™€ ๊ฐ™์ด ๋งŽ์€ ํ•˜๋“œ์›จ์–ด ์ž์›์„ ํ•„์š”๋กœ ํ•˜๋Š” ์šด์˜์ฒด์ œ๋ฅผ ๊ฐ€์ •ํ•˜๊ณ  ์žˆ๋‹ค. ๋˜ํ•œ, ํ”„๋กœ๊ทธ๋žจ์˜ ๋ถ„์„ ๋ฐ ์„ฑ๋Šฅ ์˜ˆ์ธก ๋“ฑ์„ ๊ณ ๋ คํ•˜์ง€ ์•Š๊ธฐ ๋•Œ๋ฌธ์—, ์ž์› ์ œ์•ฝ์ด ์‹ฌํ•œ ํฌ๊ธฐ๊ฐ€ ์ž‘์€ ๋กœ๋ด‡์˜ ์†Œํ”„ํŠธ์›จ์–ด๋ฅผ ๊ฐœ๋ฐœํ•˜๊ธฐ์—๋Š” ์–ด๋ ต๋‹ค. ๊ทธ๋ž˜์„œ ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ž„๋ฒ ๋””๋“œ ์†Œํ”„ํŠธ์›จ์–ด๋ฅผ ์„ค๊ณ„ํ•  ๋•Œ ์“ฐ์ด๋Š” ์ •ํ˜•์ ์ธ ๋ชจ๋ธ์„ ์ด์šฉํ•œ๋‹ค. ์ด ๋ชจ๋ธ์€ ์ •์  ๋ถ„์„๊ณผ ์„ฑ๋Šฅ ์˜ˆ์ธก์ด ๊ฐ€๋Šฅํ•˜์ง€๋งŒ, ๋กœ๋ด‡์˜ ํ–‰์œ„๋ฅผ ํ‘œํ˜„ํ•˜๊ธฐ์—๋Š” ์ œ์•ฝ์ด ์žˆ๋‹ค. ๊ทธ๋ž˜์„œ ๋ณธ ๋…ผ๋ฌธ์—์„œ ์™ธ๋ถ€์˜ ์ด๋ฒคํŠธ์— ์˜ํ•ด ์ˆ˜ํ–‰ ์ค‘๊ฐ„์— ํ–‰์œ„๋ฅผ ๋ณ€๊ฒฝํ•˜๋Š” ๋กœ๋ด‡์„ ์œ„ํ•ด ์œ ํ•œ ์ƒํƒœ ๋จธ์‹  ๋ชจ๋ธ๊ณผ ๋ฐ์ดํ„ฐ ํ”Œ๋กœ์šฐ ๋ชจ๋ธ์ด ๊ฒฐํ•ฉํ•˜์—ฌ ๋™์  ํ–‰์œ„๋ฅผ ๋ช…์„ธํ•  ์ˆ˜ ์žˆ๋Š” ํ™•์žฅ๋œ ๋ชจ๋ธ์„ ์ ์šฉํ•œ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ๋”ฅ๋Ÿฌ๋‹๊ณผ ๊ฐ™์ด ๊ณ„์‚ฐ๋Ÿ‰์„ ๋งŽ์ด ํ•„์š”๋กœ ํ•˜๋Š” ์‘์šฉ์„ ๋ถ„์„ํ•˜๊ธฐ ์œ„ํ•ด, ๋ฃจํ”„ ๊ตฌ์กฐ๋ฅผ ๋ช…์‹œ์ ์œผ๋กœ ํ‘œํ˜„ํ•  ์ˆ˜ ์žˆ๋Š” ๋ชจ๋ธ์„ ์ œ์•ˆํ•œ๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ ์—ฌ๋Ÿฌ ๋กœ๋ด‡์˜ ํ˜‘์—… ์šด์šฉ์„ ์œ„ํ•ด ๋กœ๋ด‡ ์‚ฌ์ด์— ๊ณต์œ ๋˜๋Š” ์ •๋ณด๋ฅผ ๋‚˜ํƒ€๋‚ด๊ธฐ ์œ„ํ•ด ๋‘ ๊ฐ€์ง€ ๋ชจ๋ธ์„ ์‚ฌ์šฉํ•œ๋‹ค. ๋จผ์ € ์ค‘์•™์—์„œ ๊ณต์œ  ์ •๋ณด๋ฅผ ๊ด€๋ฆฌํ•˜๊ธฐ ์œ„ํ•ด ๋ผ์ด๋ธŒ๋Ÿฌ๋ฆฌ ํƒœ์Šคํฌ๋ผ๋Š” ํŠน๋ณ„ํ•œ ํƒœ์Šคํฌ๋ฅผ ํ†ตํ•ด ๊ณต์œ  ์ •๋ณด๋ฅผ ๋‚˜ํƒ€๋‚ธ๋‹ค. ๋˜ํ•œ, ๋กœ๋ด‡์ด ์ž์‹ ์˜ ์ •๋ณด๋ฅผ ๊ฐ€๊นŒ์šด ๋กœ๋ด‡๋“ค๊ณผ ๊ณต์œ ํ•˜๊ธฐ ์œ„ํ•ด ๋ฉ€ํ‹ฐ์บ์ŠคํŒ…์„ ์œ„ํ•œ ์ƒˆ๋กœ์šด ํฌํŠธ๋ฅผ ์ถ”๊ฐ€ํ•œ๋‹ค. ์ด๋ ‡๊ฒŒ ํ™•์žฅ๋œ ์ •ํ˜•์ ์ธ ๋ชจ๋ธ์€ ์‹ค์ œ ๋กœ๋ด‡ ์ฝ”๋“œ๋กœ ์ž๋™ ์ƒ์„ฑ๋˜์–ด, ์†Œํ”„ํŠธ์›จ์–ด ์„ค๊ณ„ ์ƒ์‚ฐ์„ฑ ๋ฐ ๊ฐœ๋ฐœ ํšจ์œจ์„ฑ์— ์ด์ ์„ ๊ฐ€์ง„๋‹ค. ๋น„์ „๋ฌธ๊ฐ€๊ฐ€ ๋ช…์„ธํ•œ ์Šคํฌ๋ฆฝํŠธ ์–ธ์–ด๋Š” ์ •ํ˜•์ ์ธ ํƒœ์Šคํฌ ๋ชจ๋ธ๋กœ ๋ณ€ํ™˜ํ•˜๊ธฐ ์œ„ํ•ด ์ค‘๊ฐ„ ๋‹จ๊ณ„์ธ ์ „๋žต ๋‹จ๊ณ„๋ฅผ ์ถ”๊ฐ€ํ•˜์˜€๋‹ค. ์ œ์•ˆํ•˜๋Š” ๋ฐฉ๋ฒ•๋ก ์˜ ํƒ€๋‹น์„ฑ์„ ๊ฒ€์ฆํ•˜๊ธฐ ์œ„ํ•ด, ์‹œ๋ฎฌ๋ ˆ์ด์…˜๊ณผ ์—ฌ๋Ÿฌ ๋Œ€์˜ ์‹ค์ œ ๋กœ๋ด‡์„ ์ด์šฉํ•œ ํ˜‘์—…ํ•˜๋Š” ์‹œ๋‚˜๋ฆฌ์˜ค์— ๋Œ€ํ•ด ์‹คํ—˜์„ ์ง„ํ–‰ํ•˜์˜€๋‹ค.In the near future, it will be common that a variety of robots are cooperating to perform a mission in various fields. There are two software challenges when deploying collaborative robots: how to specify a cooperative mission and how to program each robot to accomplish its mission. In this paper, we propose a novel software development framework that separates mission specification and robot behavior programming, which is called service-oriented and model-based (SeMo) framework. Also, it can support distributed robot systems, swarm robots, and their hybrid. For mission specification, a novel scripting language is proposed with the expression capability. It involves team composition and service-oriented behavior specification of each team, allowing dynamic mode change of operation and multi-tasking. Robots are grouped into teams, and the behavior of each team is defined with a composite service. The internal behavior of a composite service is defined by a sequence of services that the robots will perform. The notion of plan is applied to express multi-tasking. And the robot may have various operating modes, so mode change is triggered by events generated in a composite service. Moreover, to improve the robustness, scalability, and flexibility of robot collaboration, the high-level mission scripting language is extended with new features such as team hierarchy, group service, one-to-many communication. We assume that any robot fails during the execution of scenarios, and the grouping of robots can be made at run-time dynamically. Therefore, the extended mission specification enables a casual user to specify various types of cooperative missions easily. For robot behavior programming, an extended dataflow model is used for task-level behavior specification that does not depend on the robot hardware platform. To specify the dynamic behavior of the robot, we apply an extended task model that supports a hybrid specification of dataflow and finite state machine models. Furthermore, we propose a novel extension to allow the explicit specification of loop structures. This extension helps the compute-intensive application, which contains a lot of loop structures, to specify explicitly and analyze at compile time. Two types of information sharing, global information sharing and local knowledge sharing, are supported for robot collaboration in the dataflow graph. For global information, we use the library task, which supports shared resource management and server-client interaction. On the other hand, to share information locally with near robots, we add another type of port for multicasting and use the knowledge sharing technique. The actual robot code per robot is automatically generated from the associated task graph, which minimizes the human efforts in low-level robot programming and improves the software design productivity significantly. By abstracting the tasks or algorithms as services and adding the strategy description layer in the design flow, the mission specification is refined into task-graph specification automatically. The viability of the proposed methodology is verified with preliminary experiments with three cooperative mission scenarios with heterogeneous robot platforms and robot simulator.Chapter 1. Introduction 1 1.1 Motivation 1 1.2 Contribution 7 1.3 Dissertation Organization 9 Chapter 2. Background and Existing Research 11 2.1 Terminologies 11 2.2 Robot Software Development Frameworks 25 2.3 Parallel Embedded Software Development Framework 31 Chapter 3. Overview of the SeMo Framework 41 3.1 Motivational Examples 45 Chapter 4. Robot Behavior Programming 47 4.1 Related works 48 4.2 Model-based Task Graph Specification for Individual Robots 56 4.3 Model-based Task Graph Specification for Cooperating Robots 70 4.4 Automatic Code Generation 74 4.5 Experiments 78 Chapter 5. High-level Mission Specification 81 5.1 Service-oriented Mission Specification 82 5.2 Strategy Description 93 5.3 Automatic Task Graph Generation 96 5.4 Related works 99 5.5 Experiments 104 Chapter 6. Conclusion 114 6.1 Future Research 116 Bibliography 118 Appendices 133 ์š”์•ฝ 158Docto

    Embedded System Design

    Get PDF
    A unique feature of this open access textbook is to provide a comprehensive introduction to the fundamental knowledge in embedded systems, with applications in cyber-physical systems and the Internet of things. It starts with an introduction to the field and a survey of specification models and languages for embedded and cyber-physical systems. It provides a brief overview of hardware devices used for such systems and presents the essentials of system software for embedded systems, including real-time operating systems. The author also discusses evaluation and validation techniques for embedded systems and provides an overview of techniques for mapping applications to execution platforms, including multi-core platforms. Embedded systems have to operate under tight constraints and, hence, the book also contains a selected set of optimization techniques, including software optimization techniques. The book closes with a brief survey on testing. This fourth edition has been updated and revised to reflect new trends and technologies, such as the importance of cyber-physical systems (CPS) and the Internet of things (IoT), the evolution of single-core processors to multi-core processors, and the increased importance of energy efficiency and thermal issues
    • โ€ฆ
    corecore