National Institute of Standards and Technology における超伝導研究及び生活

The most visible use of computers and software is processing information for human consumption. The vast majority of computers in use, however, are much less visible. They run the engine, brakes, seatbelts, airbag, and audio system in your car. They digitally encode your voice and construct a radio signal to send it from your cell phone to a base station. They command robots on a factory floor, power generation in a power plant, processes in a chemical plant, and traffic lights in a city. These less visible computers are called embedded systems, and the software they run is called embedded software. The principal challenges in designing and analyzing embedded systems stem from their interaction with physical processes. This book takes a cyber-physical approach to embedded systems, introducing the engineering concepts underlying embedded systems as a technology and as a subject of study. The focus is on modeling, design, and analysis of cyber-physical systems, which integrate computation, networking, and physical processes. The second edition offers two new chapters, several new exercises, and other improvements. The book can be used as a textbook at the advanced undergraduate or introductory graduate level and as a professional reference for practicing engineers and computer scientists. Readers should have some familiarity with machine structures, computer programming, basic discrete mathematics and algorithms, and signals and systems.

Introduction to Embedded Systems - A Cyber-Physical Systems Approach

This survey covers hard real-time scheduling algorithms and schedulability analysis techniques for homogeneous multiprocessor systems. It reviews the key results in this field from its origins in the late 1960s to the latest research published in late 2009. The survey outlines fundamental results about multiprocessor real-time scheduling that hold independent of the scheduling algorithms employed. It provides a taxonomy of the different scheduling methods, and considers the various performance metrics that can be used for comparison purposes. A detailed review is provided covering partitioned, global, and hybrid scheduling algorithms, approaches to resource sharing, and the latest results from empirical investigations. The survey identifies open issues, key research challenges, and likely productive research directions.

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A survey of hard real-time scheduling for multiprocessor systems

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[서평]「Computer Organization and Design, The Hardware/Software Interface」

A survey on networked control systems (NCSs), published in a previous paper, is updated and extended. A simple framework and some general formulations for the study of NCSs are proposed. In addition to the survey on NCSs, the impact of NCSs on traditional large-scale system control methodologies with a related application is also reviewed.

Networked control system: a brief survey

We present an optimal real-time scheduling algorithm for multiprocessors -- one that satisfies all task deadlines, when the total utilization demand does not exceed the utilization capacity of the processors. The algorithm called LLREF, is designed based on a novel abstraction for reasoning about task execution behavior on multiprocessors: the Time and Local Execution Time Domain Plane (or TL plane). LLREF is based on the fluid scheduling model and the fairness notion, and uses the T-L plane to describe fluid schedules without using time quanta, unlike the optimal Pfair algorithm (which uses time quanta). We show that scheduling for multiprocessors can be viewed as repeatedly occurring T-L planes, and feasibly scheduling on a single T-L plane results in the optimal schedule. We analytically establish the optimality of LLREF. Further, we establish that the algorithm has bounded overhead, and this bound is independent of time quanta (unlike Pfair). Our simulation results validate our analysis on the algorithm overhead.

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An Optimal Real-Time Scheduling Algorithm for Multiprocessors

A surveillance system, which tracks mobile targets, is one of the most important applications of wireless sensor networks. When nodes operate in a duty cycling mode, tracking performance can be improved if the target motion can be predicted and nodes along the trajectory can be proactively awakened. However, this will negatively influence the energy efficiency and constrain the benefits of duty cycling. In this paper, we present a Probability-based Prediction and Sleep Scheduling protocol (PPSS) to improve energy efficiency of proactive wake up. We start with designing a target prediction method based on both kinematics and probability. Based on the prediction results, PPSS then precisely selects the nodes to awaken and reduces their active time, so as to enhance energy efficiency with limited tracking performance loss. We evaluated the efficiency of PPSS with both simulation-based and implementation-based experiments. The experimental results show that compared to MCTA algorithm, PPSS improves energy efficiency by 25-45 percent (simulation based) and 16.9 percent (implementation based), only at the expense of an increase of 5-15 percent on the detection delay (simulation based) and 4.1 percent on the escape distance percentage (implementation based), respectively.

Probability-Based Prediction and Sleep Scheduling for Energy-Efficient Target Tracking in Sensor Networks

We argue that the key underpinning of the current state-of-the real-time practice - the priority artifact - and that of the current state-of-the real-time art - deadline-based timeliness optimality - are entirely inadequate for specifying timeliness objectives, for reasoning about timeliness behavior, and for performing resource management that can dependably satisfy timeliness objectives in many dynamic real-time systems. We argue that time/utility functions and the utility accrual scheduling paradigm provide a more generalized, adaptive, and flexible approach. Recent research in the utility accrual paradigm has significantly advanced the state-of-the-art of that paradigm. We survey these advances.

On recent advances in time/utility function real-time scheduling and resource management

We present a MAC-layer, soft real-time packet scheduling algorithm called UPA. UPA considers a message model where message packets have end-to-end timeliness requirements that are specified using Jensen's time-utility functions (TUFs). The algorithm seeks to maximize system-wide, aggregate packet utility. Since this scheduling problem is NP-hard, UPA heuristically computes schedules with a quadratic worst-case cost, faster than the previously best CMA algorithm. Our simulation studies show that UPA performs the same as or significantly better than CMA for a broad set of TUFs. Furthermore, we implement UPA and prototype a TUF-driven switched Ethernet system. The performance measurements of UPA from the implementation reveal its strong effectiveness. Finally, we derive timeliness feasibility conditions of TUF-driven switched Ethernet systems that use the UPA algorithm.

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Time-utility function-driven switched Ethernet: packet scheduling algorithm, implementation, and feasibility analysis

The recent possibility of integrating multiple-OS-capable, high-core-count, heterogeneous-ISA processors in the same platform poses a question: given the tight integration between system components, can a shared memory programming model be adopted, enhancing programmability? If this can be done, an enormous amount of existing code written for shared memory architectures would not have to be rewritten to use a new programming paradigm (e.g., code offloading) that is often very expensive and error prone. We propose a new software architecture that is composed of an operating system and a compiler framework to run ordinary shared memory applications, written for homogeneous machines, on OS-capable heterogeneous-ISA machines. Applications run transparently amongst different ISA processors while exploiting the most optimized instruction set for each code block. We have implemented and tested our system, called Popcorn, on a multi-core Intel Xeon machine with a PCIe Intel Xeon Phi to demonstrate the viability of our approach. Application execution on Popcorn demonstrates to be up to 52% faster than the most performant native execution on Linux, on either Xeon or Xeon Phi, while removing the burden of the programmer having to adopt a different programming model than shared memory on a heterogeneous system. When compared to an offloading programming model, Popcorn is shown to be up to 6.2 times faster.

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Binoy Ravindran

Papers

An Optimal Real-Time Scheduling Algorithm for Multiprocessors

Probability-Based Prediction and Sleep Scheduling for Energy-Efficient Target Tracking in Sensor Networks

On recent advances in time/utility function real-time scheduling and resource management

Time-utility function-driven switched Ethernet: packet scheduling algorithm, implementation, and feasibility analysis

Popcorn: bridging the programmability gap in heterogeneous-ISA platforms