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Information Aggregation for Constrained Online Control

proceedings of the acm on measurement and analysis of computing systems 2021年第2期5卷 1–35页

作者： Li, Tongxin Chen, Yue Sun, Bo Wierman, Adam Low, Steven H. CALTECH Pasadena CA 91125 USA Tsinghua Univ Beijing Peoples R China Hong Kong Univ Sci & Technol Hong Kong Peoples R China

This paper considers an online control problem involving two controllers. A central controller chooses an action from a feasible set that is determined by time-varying and coupling constraints, which depend on all past actions and states. The central controller's goal is to minimize the cumulative cost;however, the controller has access to neither the feasible set nor the dynamics directly, which are determined by a remote local controller. Instead, the central controller receives only an aggregate summary of the feasibility information from the local controller, which does not know the system costs. We show that it is possible for an online algorithm using feasibility information to nearly match the dynamic regret of an online algorithm using perfect information whenever the feasible sets satisfy a causal invariance criterion and there is a sufficiently large prediction window size. To do so, we use a form of feasibility aggregation based on entropic maximization in combination with a novel online algorithm, named Penalized Predictive Control (PPC) and demonstrate that aggregated information can be efficiently learned using reinforcement learning algorithms. The effectiveness of our approach for closed-loop coordination between central and local controllers is validated via an electric vehicle charging application in power systems.

关键词： online control closed-loop control model predictive control regret analysis electric vehicle charging

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Privacy Design Strategies for Home Energy Management systems (HEMS) 22

Privacy Design Strategies for Home Energy Management Systems...

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CHI Conference on Human Factors in computing systems (CHI)

作者： Ramokapane, Kopo M. Bird, Caroline Rashid, Awais Chitchyan, Ruzanna Univ Bristol Bristol Avon England

ISBN: (纸本)9781450391573

Home energy management systems (HEMS) offer control and the ability to manage energy, generating and collecting energy consumption data at the most detailed level. However, data at this level poses various privacy concerns, including, for instance, profiling consumer behaviors and large-scale surveillance. The question of how utility providers can get value from such data without infringing consumers' privacy has remained under-investigated. We address this gap by exploring the pro-sharing attitudes and privacy perceptions of 30 HEMS users and non-users through an interview study. While participants are concerned about data misuse and stigmatization, our analysis also reveals that incentives, altruism, trust, security and privacy, transparency and accountability encourage data sharing. From this analysis, we derive privacy design strategies for HEMS that can both improve privacy and engender adoption.

关键词： Energy Data Smart Home Energy Management systems User Perceptions Smart Home Security and Privacy protections

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The Application of Autoencoder In IMU Data Process 3

The Application of Autoencoder In IMU Data Process

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3rd International Conference on Innovations and Development of Information Technologies and Robotics, IDITR 2024

作者： Zhao, Zihao Chongqing Jiaotong University Chongqing China

ISBN: (数字)9798350385694

ISBN: (纸本)9798350385694

Inertial Navigation System (INS) and Inertial measurement Unit (IMU) are commonly used technologies in modern navigation and attitude control fields. INS is a navigation system based on the principle of inertial sensors, which calculates the position, velocity, and attitude of an object in real-time by measuring its acceleration and angular velocity and using initial attitude information. IMU is the core component of INS and usually contains three-axis accelerometers and three-axis gyroscopes. Accelerometers are used to measure linear acceleration, and gyroscopes are used to measure angular velocity. In INS and IMU, sensors usually collect the measurement values of multiple accelerometers and gyroscopes at high frequency. These measurement values contain a large amount of information, including object acceleration, angular velocity, and attitude changes. However, due to the large number of multi-axis sensors and high-frequency sampling, processing and analyzing these data may become complex and time-consuming. At this time, data dimensionality reduction techniques can be applied[1]. The main idea of this article is to add residual blocks to the traditional dimensionality reduction technique autoencoder to improve the model's ability to extract important features. This approach can transform high-dimensional sensor data into lower-dimensional representations while retaining essential motion features. This simplifies subsequent data processing, analysis, and storage processes, improves computing efficiency, and saves resources. © 2024 IEEE.

关键词： Inertial navigation systems

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On Exploiting Patterns For Robust FPGA-based Multi-accelerator Edge computing systems

On Exploiting Patterns For Robust FPGA-based Multi-accelerat...

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25th Design, Automation and Test in Europe Conference and Exhibition (DATE)

作者： Razavi, Seyyed Ahmad Ting, Hsin-Yu Giyahchi, Thotiya Bozorgzadeh, Eli Univ Calif Irvine Irvine CA 92697 USA

ISBN: (纸本)9783981926361

Edge computing plays a key role in providing services for emerging compute-intensive applications while bringing computation close to end devices. FPGAs have been deployed to provide custom acceleration services due to their reconfigurability and support for multi-tenancy in sharing the computing resource. This paper explores an FPGA-based Multi-Accelerator Edge computing System, that serves various DNN applications from multiple end devices simultaneously. To dynamically maximize the responsiveness to end devices, we propose a system framework that exploits the characteristic of applications in patterns and employs a staggering module coupled with a mixed offline/online multi-queue scheduling method to alleviate resource contention, and uncertain delay caused by network delay variation. Our evaluation shows the framework can significantly improve responsiveness and robustness in serving multiple end devices.

关键词： Schedules Runtime Processor scheduling Time measurement Robustness Delays Time factors

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On the Viability of Decision Trees for Learning Models of systems 22

On the Viability of Decision Trees for Learning Models of Sy...

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27th Asia and South Pacific Design Automation Conference (ASP-DAC)

作者： Plambeck, Swantje Schammer, Lutz Fey, Goerschwin Hamburg Univ Technol Inst Embedded Syst D-21073 Hamburg Germany

ISBN: (纸本)9781665421355

.Abstract models of embedded systems are useful for various tasks, ranging from diagnosis, through testing to monitoring at run-time. However, deriving a model for an unknown system is difficult. Generic learners like decision trees can identify specific properties of systems and have been applied successfully, e.g., for anomaly detection and test case identification. We consider Decision Tree Learning (DTL) to derive a new type of model from given observations with bounded history for systems that have a Mealy machine representation. We prove theoretical limitations and evaluate the practical characteristics in an experimental validation.

关键词： Embedded systems Design automation Asia Distance measurement Decision trees History Task analysis

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More-than-Human Storytelling: Designing Longitudinal Narrative Engagements with Generative AI

More-than-Human Storytelling: Designing Longitudinal Narrati...

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2025 CHI Conference on Human Factors in computing systems, CHI EA 2025

作者： Fabre, Émilie Seaborn, Katie Koiwai, Shuta Watanabe, Mizuki Riesch, Paul The University of Tokyo Tokyo Japan Department of Industrial Engineering and Economics Institute of Science Tokyo Tokyo Japan Stuttgart Media University Stuttgart Germany Aspirational Computing Lab. Institute of Science Tokyo Tokyo Japan

ISBN: (纸本)9798400713958

Longitudinal engagement with generative AI (GenAI) storytelling agents is a timely but less charted domain. We explored multigenerational experiences with "Dreamsmithy," a daily dream-crafting app, where participants (N = 28) co-created stories with AI narrator "Makoto" every day. Reflections and interactions were captured through a two-week diary study. Reflexive thematic analysis revealed themes likes "oscillating ambivalence" and "socio-chronological bonding," highlighting the complex dynamics that emerged between individuals and the AI narrator over time. Findings suggest that while people appreciated the personal notes, opportunities for reflection, and AI creativity, limitations in narrative coherence and control occasionally caused frustration. The results underscore the potential of GenAI for longitudinal storytelling, but also raise critical questions about user agency and ethics. We contribute initial empirical insights and design considerations for developing adaptive, more-than-human storytelling systems. © 2025 Copyright held by the owner/author(s).

关键词： ChatGPT Field Study Generative AI Large Language Models Longitudinal Study Storytelling User Experience Voice Agent

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Parallelism or Fairness? How to Be Friendly for SSDs in Cloud Environments

Parallelism or Fairness? How to Be Friendly for SSDs in Clou...

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2024 IEEE International Conference on Cluster computing, CLUSTER 2024

作者： Zhou, Yang Wang, Fang Shi, Zhan Feng, Dan Engineering Research Center of Data Storage Systems and Technology Ministry of Education of China Wuhan National Laboratory for Optoelectronics Key Laboratory of Information Storage System Wuhan China School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9798350358711

Modern SSDs achieve low latency and high throughput by utilizing multiple levels of SSD parallelism. Fairness is also a critical design consideration in cloud environments and has inspired great interest in recent years to study it. However, we find that excessive striving for SSD parallelism can inadvertently harm the SSD fairness due to the striped data layout. We observe from our experimental analysis that some common access patterns in cloud loads (e.g., high-intensity I/O) are not addressed by SSD parallelism, which can affect both SSD parallelism and fairness. In this paper, we analyze two address mapping policies with orthogonal characteristics from SSD parallelism and fairness perspectives. Based on extensive experiments and observations, we schedule a hybrid address mapping policy to achieve fairness of SSDs in cloud environments by distinguishing different I/O access modes and cold/hot data, while ensuring SSD performance. Experimental results on the latest block-level I/O traces show that our approach significantly improves performance and fairness by up to 77.3% and 62.8%, respectively, over the previous schemes with negligible cost. Meanwhile, it can also reduce the write amplification by 23.5% to 33.5%. © 2024 IEEE.

关键词： Cloud platforms

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NG-Scope: Fine-Grained Telemetry for NextG Cellular Networks

NG-Scope: Fine-Grained Telemetry for NextG Cellular Networks

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作者： Xie, Yaxiong Jamieson, Kyle Princeton University PrincetonNJ United States

Accurate and highly-granular channel capacity telemetry of the cellular last hop is crucial for the effective operation of transport layer protocols and cutting edge applications, such as video on demand and video telephony. This paper presents the design, implementation, and experimental performance evaluation of NG-Scope, the first such telemetry tool able to fuse physical-layer channel occupancy readings from the cellular control channel with higher-layer packet arrival statistics and make accurate capacity estimates. NG-Scope handles the latest cellular innovations, such as when multiple base stations aggregate their signals together to serve mobile users. End-to-end experiments in a commercial cellular network demonstrate that wireless capacity varies significantly with channel quality, mobility, competing traffic within each cell, and the number of aggregated cells. Our experiments demonstrate significantly improved cell load estimation accuracy, missing the detection of less than 1% of data capacity overall, a reduction of 82% compared to OWL, the state-of-the-art in cellular monitoring. Further experiments show that MobileInsight-based CLAW has a root-mean-squared capacity error of 30.5 Mbit/s, which is 3.3× larger than NG-Scope (9.2 Mbit/s). © 2022 acm.

关键词： Mobile telecommunication systems

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People Counting System Using OpenCV Algorithms and Edge computing for Safety Management

People Counting System Using OpenCV Algorithms and Edge Comp...

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2023 IEEE International Conference on Smart Information systems and Technologies, SIST 2023

作者： Seitbattalov, Zhexen Y. Canbolat, Huseyin Atanov, Sabyrzhan K. Moldabayeva, Zhanar S. Kyzyrkanov, Abzal E. Maidanov, Adil K. L. N. Gumilyov Eurasian National University Department of Computer and Software Engineering Astana Kazakhstan Ankara Yildirim Beyazit University Department of Electrical and Electronics Engineering Ankara Turkey

ISBN: (纸本)9798350335040

The necessity of ensuring people's safety in urban conditions during gathering in a certain indoor or outdoor area, as well as during the operation of technical equipment, requires measurement of their number, weights, the distance between them, density and many other parameters. The collection of those parameters and analysis allows you to ensure the optimal numerical value of people per area and not exceed the critical peak value, ensuring the safety of people's health and life. However, automating those processes requires stable network bandwidth and enormous computing resources for data transferring to the data center and its processing, as well as applying artificial intelligence algorithms to the data and sending the results back to the end-user. In this paper, to avoid the disadvantages of cloud computing, we consider Raspberry Pi with a camera module as an edge device to develop an automated people-counting system based on using OpenCV algorithms and Edge computing for Safety Management. The proposed system can be used for indoor or outdoor areas, during scaffolding works and lift's operation for controlling an optimal number of people. As a result of the application the edge computing, network bandwidth and computing resources of the data center have been optimized. © 2023 IEEE.

关键词： Image processing

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Fine-grained Policy-driven I/O Sharing for Burst Buffers 23

Fine-grained Policy-driven I/O Sharing for Burst Buffers

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2023 International Conference for High Performance computing, Networking, Storage and analysis, SC 2023

作者： Karrels, Ed Huang, Lei Kan, Yuhong Arora, Ishank Wang, Yinzhi Katz, Daniel S. Gropp, William Zhang, Zhao University of Illinois Urbana Champaign Champaign United States Texas Advanced Computing Center Austin United States University of Texas at Austin Austin United States Department of Electrical and Computer Engineering Rutgers University Piscataway United States

ISBN: (纸本)9798400701092

A burst buffer is a common method to bridge the performance gap between the I/O needs of modern supercomputing applications and the performance of the shared file system on large-scale supercomputers. However, existing I/O sharing methods require resource isolation, offline profiling, or repeated execution that significantly limit the utilization and applicability of these systems. Here we present ThemisIO, a policy-driven I/O sharing framework for a remote-shared burst buffer: a dedicated group of I/O nodes, each with a local storage device. ThemisIO preserves high utilization by implementing opportunity fairness so that it can reallocate unused I/O resources to other applications. ThemisIO accurately and efficiently allocates I/O cycles among applications, purely based on real-time I/O behavior without requiring user-supplied information or offline-profiled application characteristics. ThemisIO supports a variety of fair sharing policies, such as user-fair, size-fair, as well as composite policies, e.g., group-then-user-fair. All these features are enabled by its statistical token design. ThemisIO can alter the execution order of incoming I/O requests based on assigned tokens to precisely balance I/O cycles between applications via time slicing, thereby enforcing processing isolation. Experiments using I/O benchmarks show that ThemisIO sustains 13.5 - 13.7% higher I/O throughput and 19.5 - 40.4% lower performance variation than existing algorithms. For real applications, ThemisIO significantly reduces the slowdown by 59.1 - 99.8% caused by I/O interference. © 2023 Owner/Author(s).

关键词： Virtual storage

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