2020 ACM/IEEE 11th International Conference on Cyber-Physical Systems (ICCPS)最新文献_第2页

ICCPS 2020 Breaker Page ICCPS 2020断路器页面

2020 ACM/IEEE 11th International Conference on Cyber-Physical Systems (ICCPS) Pub Date : 2020-04-01 DOI: 10.1109/iccps48487.2020.00003

引用次数: 0

ICCPS 2020 Committees

2020 ACM/IEEE 11th International Conference on Cyber-Physical Systems (ICCPS) Pub Date : 2020-04-01 DOI: 10.1109/iccps48487.2020.00006

引用次数: 0

Semantics-Directed Hardware Generation of Hybrid Systems 语义导向的混合系统硬件生成

2020 ACM/IEEE 11th International Conference on Cyber-Physical Systems (ICCPS) Pub Date : 2020-04-01 DOI: 10.1109/ICCPS48487.2020.00037

Nathan Allen, P. Roop

{"title":"Semantics-Directed Hardware Generation of Hybrid Systems","authors":"Nathan Allen, P. Roop","doi":"10.1109/ICCPS48487.2020.00037","DOIUrl":"https://doi.org/10.1109/ICCPS48487.2020.00037","url":null,"abstract":"Cyber-Physical Systems are being used in \"safety-critical\" domains and have strict timing constraints, meaning that time predictability of the implementations is highly important. In the event that these timing constraints are violated, the correct operation of the system is no longer guaranteed, and serious consequences may occur. Typically, such systems are implemented in software and executed on processors optimised for average-case performance leading to implementations that are difficult, if not impossible, to analyse for their worst case.We propose an approach which is capable of generating hardware implementations of such systems in a semantics-directed manner, ensuring predictability of the final design. Additionally, we present a schema which is used in the description of such Hybrid Systems, captured as Hybrid Input-Output Automata, which is used in this process. Through the example of a grid of cardiac cells and other industrial examples, we show that this approach generates implementations which are almost 15 times faster than an 800MHz ARM Cortex A-9 in the average case, while maintaining timing predictability and having a Worst Case Reaction Time which is over 3,000 times smaller.","PeriodicalId":158690,"journal":{"name":"2020 ACM/IEEE 11th International Conference on Cyber-Physical Systems (ICCPS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114091336","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Investigating Controller Evolution and Divergence through Mining and Mutation* 基于挖掘和突变的控制器演化和发散研究*

2020 ACM/IEEE 11th International Conference on Cyber-Physical Systems (ICCPS) Pub Date : 2020-04-01 DOI: 10.1109/ICCPS48487.2020.00022

Balaji Balasubramaniam, H. Bagheri, Sebastian G. Elbaum, Justin M. Bradley

{"title":"Investigating Controller Evolution and Divergence through Mining and Mutation*","authors":"Balaji Balasubramaniam, H. Bagheri, Sebastian G. Elbaum, Justin M. Bradley","doi":"10.1109/ICCPS48487.2020.00022","DOIUrl":"https://doi.org/10.1109/ICCPS48487.2020.00022","url":null,"abstract":"Successful cyber-physical system controllers evolve as they are refined, extended, and adapted to new systems and contexts. This evolution occurs in the controller design and also in its software implementation. Model-based design and controller synthesis can help to synchronize this evolution of design and software, but such synchronization is rarely complete as software tends to also evolve in response to elements rarely present in a control model, leading to mismatches between the control design and the software. In this paper we perform a first-of-it-skind study on the evolution of two popular open-source safety-critical autopilot control software – ArduPilot, and Paparazzi, to better understand how controllers evolve and the space of potential mismatches between control design and their software implementation. We then use that understanding to prototype a technique that can generate mutated versions of code to mimic evolution to assess its impact on a controller’s behavior.We find that 1) control software evolves quickly and controllers are rewritten in their entirety over their lifetime, implying that the design, synthesis, and implementation of controllers should also support incremental evolution, 2) many software changes stem from an inherent mismatch between continuous physical models and their corresponding discrete software implementation, but also from the mishandling of exceptional conditions, and limitations and distinct data representation of the underlying computing architecture, 3) small code changes can have a dramatic effect in a controller’s behavior, implying that further support is needed to bridge these mismatches as carefully verified model properties may not necessarily translate to its software implementation.","PeriodicalId":158690,"journal":{"name":"2020 ACM/IEEE 11th International Conference on Cyber-Physical Systems (ICCPS)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123203390","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

Mining Environment Assumptions for Cyber-Physical System Models 网络-物理系统模型的挖掘环境假设

2020 ACM/IEEE 11th International Conference on Cyber-Physical Systems (ICCPS) Pub Date : 2020-04-01 DOI: 10.1109/ICCPS48487.2020.00016

Sara Mohammadinejad, Jyotirmoy V. Deshmukh, Aniruddh Gopinath Puranic

{"title":"Mining Environment Assumptions for Cyber-Physical System Models","authors":"Sara Mohammadinejad, Jyotirmoy V. Deshmukh, Aniruddh Gopinath Puranic","doi":"10.1109/ICCPS48487.2020.00016","DOIUrl":"https://doi.org/10.1109/ICCPS48487.2020.00016","url":null,"abstract":"Many complex cyber-physical systems can be modeled as heterogeneous components interacting with each other in real-time. We assume that the correctness of each component can be specified as a requirement satisfied by the output signals produced by the component, and that such an output guarantee is expressed in a real-time temporal logic such as Signal Temporal Logic (STL). In this paper, we hypothesize that a large subset of input signals for which the corresponding output signals satisfy the output requirement can also be compactly described using an STL formula that we call the environment assumption. We propose an algorithm to mine such an environment assumption using a supervised learning technique. Essentially, our algorithm treats the environment assumption as a classifier that labels input signals as good if the corresponding output signal satisfies the output requirement, and as bad otherwise. Our learning method simultaneously learns the structure of the STL formula as well as the values of the numeric constants appearing in the formula.1 To achieve this, we combine a procedure to systematically enumerate candidate Parametric STL (PSTL) formulas, with a decision-tree based approach to learn parameter values. We demonstrate experimental results on real world data from several domains including transportation and health care.","PeriodicalId":158690,"journal":{"name":"2020 ACM/IEEE 11th International Conference on Cyber-Physical Systems (ICCPS)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116688137","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Reputation-Based Fair Power Allocation to Plug-in Electric Vehicles in the Smart Grid 智能电网中基于声誉的插电式电动汽车电力公平分配

2020 ACM/IEEE 11th International Conference on Cyber-Physical Systems (ICCPS) Pub Date : 2020-04-01 DOI: 10.1109/ICCPS48487.2020.00014

Abdullah Al Zishan, Moosa Moghimi Haji, Omid Ardakanian

{"title":"Reputation-Based Fair Power Allocation to Plug-in Electric Vehicles in the Smart Grid","authors":"Abdullah Al Zishan, Moosa Moghimi Haji, Omid Ardakanian","doi":"10.1109/ICCPS48487.2020.00014","DOIUrl":"https://doi.org/10.1109/ICCPS48487.2020.00014","url":null,"abstract":"We present a reputation-based framework for allocating power to plug-in electric vehicles (EVs) in the smart grid. In this framework, the available capacity of the distribution network measured by distribution-level phasor measurement units is divided in a proportionally fair manner among connected EVs, considering their demands and self-declared deadlines. To encourage users to estimate their deadlines more precisely and conservatively, a weight is assigned to a each deadline based on the user’s reputation, which comprises two kinds of evidence: deadlines declared before and after the actual departure times in the recent past. Assuming reliable communication between sensors installed in the network and charging stations, we design a decentralized algorithm which allows the users to independently compute their fair share based on signals received from upstream sensors without sharing their private information, e.g., their deadline, with a central scheduler. We prove that this algorithm achieves quadratic convergence under specific conditions and evaluate it empirically on a test distribution network by comparing it with a centralized algorithm which solves the same optimization problem, a decentralized gradient-projection algorithm with linear convergence, and earliest-deadline-first and least-laxity-first scheduling policies. Our results corroborate that the proposed algorithm can track the available capacity of the network despite changes in the demands of homes and other inelastic loads, improves a fairness metric, and increases the overall allocation to users who have a better reputation.","PeriodicalId":158690,"journal":{"name":"2020 ACM/IEEE 11th International Conference on Cyber-Physical Systems (ICCPS)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114675951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Hierarchical Temporal Memory Based Machine Learning for Real-Time, Unsupervised Anomaly Detection in Smart Grid: WiP Abstract 基于分层时间记忆的机器学习在智能电网中的实时无监督异常检测:WiP

2020 ACM/IEEE 11th International Conference on Cyber-Physical Systems (ICCPS) Pub Date : 2020-04-01 DOI: 10.1109/ICCPS48487.2020.00027

Anomadarshi Barua, Deepan Muthirayan, P. Khargonekar, M. A. Faruque

引用次数: 13

Foreword to the ICCPS 2020 Proceedings: Message from the Chairs ICCPS 2020会议录前言:主席的信息

2020 ACM/IEEE 11th International Conference on Cyber-Physical Systems (ICCPS) Pub Date : 2020-04-01 DOI: 10.1109/iccps48487.2020.00005

引用次数: 0

ICCPS 2020 TOC

2020 ACM/IEEE 11th International Conference on Cyber-Physical Systems (ICCPS) Pub Date : 2020-04-01 DOI: 10.1109/iccps48487.2020.00004

John Stankovic

引用次数: 0

Work-in-Progress Abstract: A Reliable Wireless Smart Vehicle Highway On-Ramp Merging Protocol with Constant Time Headway Safety Guarantee 摘要:一种可靠的、具有恒时距安全保证的无线智能汽车公路入匝道合流协议

2020 ACM/IEEE 11th International Conference on Cyber-Physical Systems (ICCPS) Pub Date : 2020-04-01 DOI: 10.1109/ICCPS48487.2020.00025

Xueli Fan, Qixin Wang, Jie Liu

引用次数: 2