ACM Transactions on Cyber-Physical Systems最新文献

{"title":"Offline and Online Learning of Signal Temporal Logic Formulae Using Decision Trees","authors":"Giuseppe Bombara, C. Belta","doi":"10.1145/3433994","DOIUrl":"https://doi.org/10.1145/3433994","url":null,"abstract":"In this article, we focus on inferring high-level descriptions of a system from its execution traces. Specifically, we consider a classification problem where system behaviors are described using formulae of Signal Temporal Logic (STL). Given a finite set of pairs of system traces and labels, where each label indicates whether the corresponding trace exhibits some system property, we devised a decision-tree-based framework that outputs an STL formula that can distinguish the traces. We also extend this approach to the online learning scenario. In this setting, it is assumed that new signals may arrive over time and the previously inferred formula should be updated to accommodate the new data. The proposed approach presents some advantages over traditional machine learning classifiers. In particular, the produced formulae are interpretable and can be used in other phases of the system’s operation, such as monitoring and control. We present two case studies to illustrate the effectiveness of the proposed algorithms: (1) a fault detection problem in an automotive system and (2) an anomaly detection problem in a maritime environment.","PeriodicalId":7055,"journal":{"name":"ACM Transactions on Cyber-Physical Systems","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3433994","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43707011","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}

{"title":"Introduction to the Special Issue on Time for CPS (TCPS)","authors":"Aviral Shrivastava, P. Derler","doi":"10.1145/3433948","DOIUrl":"https://doi.org/10.1145/3433948","url":null,"abstract":"For many Cyber-Physical Systems (CPS), timing is crucial for safety, security, and responsiveness of the system behavior. Time is key to enabling coordinated actions among the many, often heavily distributed, components of a CPS. For example, in power systems, the time of all phasor measurement units (PMUs) is synchronized via GPS signals, because otherwise aligning data from various distributed PMUs will become impossible, rendering state estimates wrong and unusable. With the increasing connectivity in modern CPS, requirements on timing accuracy and synchronization are evolving, ranging from tight, picosecond synchronization accuracy in power systems to high precision and accuracy requirements for wireless and low-power networks. Smart cities and connected vehicles pose new technological challenges and timing properties play an important role for coordination and security. Despite the importance of time in CPS, there are significant gaps in specifying, reasoning about, verifying, and testing the timing behavior of systems. In practice, timing in CPS is often an afterthought in the development process. While experienced domain experts might understand the desired timing behavior of the CPS, they often do not have a standardized, formal way of describing the timing requirements, let alone incorporating timing properties as part of the design. Even if a design is accompanied with well-defined timing requirements, it is difficult to verify whether a given design satisfies those requirements. The article in this special issue address challenges ranging from specifying, modeling, and verifying time in CPS in various application domains, including automotive control, communication, and manufacturing. • In their work on “Composable Finite State Machine–based Modeling for Quality-ofInformation-Aware Cyber-physical Systems,” Rafael Rosales and Michael Paulitsch present a model-based design methodology and introduce composable design patterns to address the following Quality-of-Information properties: timeliness, correctness, completeness, consistency, and accuracy. By specifying and composing behaviors using extended finite state machines, reuse and robustness are increased and dynamic validation and optimization of functional and nonfunctional properties is enabled. • The article “System-level Logical Execution Time: Augmenting the Logical Execution Time Paradigm for Distributed Real-time Automotive Software,” by Kai-Björn Gemlau, Leonie Köhler, Rolf Ernst, and Sophie Quinton, apply the well-known logical execution time paradigm, which abstracts away notoriously hard-to-characterize and often non-deterministic physical execution times, not just to a single component but also in a systemwide context. By explicitly acknowledging the fact that communication times are not negligible and cannot be abstracted way, the work addresses challenges in the design and verification of complex automotive systems, such as predictability, synchronization, composability,","PeriodicalId":7055,"journal":{"name":"ACM Transactions on Cyber-Physical Systems","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3433948","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47093143","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}

{"title":"Planning for Automated Vehicles with Human Trust","authors":"Shili Sheng, Erfan Pakdamanian, Kyungtae Han, Ziran Wang, John K. Lenneman, David Parker, Lu Feng","doi":"10.1145/3561059","DOIUrl":"https://doi.org/10.1145/3561059","url":null,"abstract":"Recent work has considered personalized route planning based on user profiles, but none of it accounts for human trust. We argue that human trust is an important factor to consider when planning routes for automated vehicles. This article presents a trust-based route-planning approach for automated vehicles. We formalize the human-vehicle interaction as a partially observable Markov decision process (POMDP) and model trust as a partially observable state variable of the POMDP, representing the human’s hidden mental state. We build data-driven models of human trust dynamics and takeover decisions, which are incorporated in the POMDP framework, using data collected from an online user study with 100 participants on the Amazon Mechanical Turk platform. We compute optimal routes for automated vehicles by solving optimal policies in the POMDP planning and evaluate the resulting routes via human subject experiments with 22 participants on a driving simulator. The experimental results show that participants taking the trust-based route generally reported more positive responses in the after-driving survey than those taking the baseline (trust-free) route. In addition, we analyze the trade-offs between multiple planning objectives (e.g., trust, distance, energy consumption) via multi-objective optimization of the POMDP. We also identify a set of open issues and implications for real-world deployment of the proposed approach in automated vehicles.","PeriodicalId":7055,"journal":{"name":"ACM Transactions on Cyber-Physical Systems","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49015243","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}

{"title":"Utilizing Game Theory to Optimize In-motion Wireless Charging Service Efficiency for Electric Vehicles","authors":"Li Yan, Haiying Shen","doi":"10.1145/3430194","DOIUrl":"https://doi.org/10.1145/3430194","url":null,"abstract":"Charger lanes, which are road segments equipped with in-motion wireless chargers, are expected to keep Electric Vehicles (EVs) continuously driving without recharging downtime. To maximize the service efficiency of the in-motion wireless chargers, we must properly coordinate the traffic of the EVs to avoid the generation of congestion at the charger lanes and on the road segments to them. In this article, we propose WPT-Opt, a game-theoretic approach for optimizing in-motion wireless charging efficiency, minimizing EVs’ driving time to the charger, and avoiding traffic congestion at the charger lanes to fulfill this task. We studied a metropolitan-scale dataset of public transportation EVs and observed the EVs’ spatial and temporal preference in selecting chargers, competition for chargers during busy charging times, the relationship between vehicle density and driving velocity on a road segment, the normal distribution of travel time of road segments, and the fact that vehicles have similar frequently driven trajectories. Based on the observations, a central controller estimates the vehicle density of the road segments by measuring the vehicles’ trajectory travel time, the friendship among the vehicles, and the vehicles’ routing choice given the presence of charger lanes. Then, we formulate a non-cooperative Stackelberg game between all the EVs and the central controller, in which each EV aims at minimizing its charging time cost to its selected target charger, while the central controller tries to maximally avoid the generation of congestion on the way through the in-motion wireless chargers. Our trace-driven experiments on SUMO demonstrate that WPT-Opt can maximally reduce the average charging time cost of the EVs by approximately 200% during different hours of a day.","PeriodicalId":7055,"journal":{"name":"ACM Transactions on Cyber-Physical Systems","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3430194","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44809492","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}

{"title":"Data-driven Distributionally Robust Optimization For Vehicle Balancing of Mobility-on-Demand Systems","authors":"Fei Miao, Sihong He, Lynn Pepin, Shuo Han, Abdeltawab M. Hendawi, Mohamed E. Khalefa, J. Stankovic, G. Pappas","doi":"10.1145/3418287","DOIUrl":"https://doi.org/10.1145/3418287","url":null,"abstract":"With the transformation to smarter cities and the development of technologies, a large amount of data is collected from sensors in real time. Services provided by ride-sharing systems such as taxis, mobility-on-demand autonomous vehicles, and bike sharing systems are popular. This paradigm provides opportunities for improving transportation systems’ performance by allocating ride-sharing vehicles toward predicted demand proactively. However, how to deal with uncertainties in the predicted demand probability distribution for improving the average system performance is still a challenging and unsolved task. Considering this problem, in this work, we develop a data-driven distributionally robust vehicle balancing method to minimize the worst-case expected cost. We design efficient algorithms for constructing uncertainty sets of demand probability distributions for different prediction methods and leverage a quad-tree dynamic region partition method for better capturing the dynamic spatial-temporal properties of the uncertain demand. We then derive an equivalent computationally tractable form for numerically solving the distributionally robust problem. We evaluate the performance of the data-driven vehicle balancing algorithm under different demand prediction and region partition methods based on four years of taxi trip data for New York City (NYC). We show that the average total idle driving distance is reduced by 30% with the distributionally robust vehicle balancing method using quad-tree dynamic region partitions, compared with vehicle balancing methods based on static region partitions without considering demand uncertainties. This is about a 60-million-mile or a 8-million-dollar cost reduction annually in NYC.","PeriodicalId":7055,"journal":{"name":"ACM Transactions on Cyber-Physical Systems","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3418287","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41555488","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}

{"title":"Taming the State-space Explosion in the Makespan Optimization of Flexible Manufacturing Systems","authors":"J. Bastos, J. Voeten, S. Stuijk, R. Schiffelers, H. Corporaal","doi":"10.1145/3426194","DOIUrl":"https://doi.org/10.1145/3426194","url":null,"abstract":"This article presents a modular automaton-based framework to specify flexible manufacturing systems and to optimize the makespan of product batches. The Batch Makespan Optimization (BMO) problem is NP-Hard and optimization can therefore take prohibitively long, depending on the size of the state-space induced by the specification. To tame the state-space explosion problem, we develop an algebra based on automata equivalence and inclusion relations that consider both behavior and structure. The algebra allows us to systematically relate the languages induced by the automata, their state-space sizes, and their solutions to the BMO problem. Further, we introduce a novel constraint-based approach to systematically prune the state-space based on the the notions of nonpermutation-repulsiveness and permutation-attractiveness. We prove that constraining a nonpermutation-repulsing automaton with a permutation-attracting constraint always reduces the state-space. This approach allows us to (i) compute optimal solutions of the BMO problem when the (additional) constraints are taken into account and (ii) compute bounds for the (original) BMO problem (without using the constraints). We demonstrate the effectiveness of our approach by optimizing an industrial wafer handling controller.","PeriodicalId":7055,"journal":{"name":"ACM Transactions on Cyber-Physical Systems","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3426194","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43644889","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}

{"title":"User Placement and Optimal Cooling Energy for Co-working Building Spaces","authors":"S. Nagarathinam, Arunchandar Vasan, V. Sarangan, Rajesh Jayaprakash, A. Sivasubramaniam","doi":"10.1145/3432818","DOIUrl":"https://doi.org/10.1145/3432818","url":null,"abstract":"Increasing real estate and other infrastructure costs have resulted in the trend of co-working offices where users pay as they use for individual desks. Co-working offices that provide personalized comfort need to address users with potentially widely varying thermal comfort preferences. Providing personalized comfort in cabins separated by physical partitions with neighboring thermal zones or open-plan offices with a single actuator has received attention in the literature. In this article, the problem of minimizing user discomfort in open-plan co-working offices with multiple actuators while being cognizant of the energy consumed is considered. Specifically, the decision problems of assigning users to desks based on their thermal preferences and jointly controlling the multiple actuators are addressed. The non-linearities in the underlying thermodynamic constraints and the seating decision together make the problem computationally hard. A two-step heuristic that addresses these issues is presented. First, using a model that accounts for spatio-temporal thermodynamics, a one-time assignment of users to desks is performed that reduces the thermal resistance faced by the HVAC systems to provide the preferred comfort levels. Next, the setpoints are decided for all actuators to jointly minimize user discomfort by optimization and model-predictive control. Further, scalability is addressed by clustering user preferences and the associated HVAC actuators’ setpoints for the cases where a large number of actuators may be present in the room.","PeriodicalId":7055,"journal":{"name":"ACM Transactions on Cyber-Physical Systems","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3432818","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44250507","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}

{"title":"VIoLET: An Emulation Environment for Validating IoT Deployments at Large Scales","authors":"Shrey Baheti, Shreyas Badiger, Yogesh L. Simmhan","doi":"10.1145/3446346","DOIUrl":"https://doi.org/10.1145/3446346","url":null,"abstract":"Internet of Things (IoT) deployments have been growing manifold, encompassing sensors, networks, edge, fog, and cloud resources. Despite the intense interest from researchers and practitioners, most do not have access to large-scale IoT testbeds for validation. Simulation environments that allow analytical modeling are a poor substitute for evaluating software platforms or application workloads in realistic computing environments. Here, we propose a virtual environment for validating Internet of Things at large scales (VIoLET), an emulator for defining and launching large-scale IoT deployments within cloud VMs. It allows users to declaratively specify container-based compute resources that match the performance of native IoT compute devices using Docker. These can be inter-connected by complex topologies on which bandwidth and latency rules are enforced. Users can configure synthetic sensors for data generation as well. We also incorporate models for CPU resource dynamism, and for failure and recovery of the underlying devices. We offer a detailed comparison of VIoLET’s compute and network performance between the virtual and physical deployments, evaluate its scaling with deployments with up to 1,000 devices and 4, 000 device-cores, and validate its ability to model resource dynamism. Our extensive experiments show that the performance of the virtual IoT environment accurately matches the expected behavior, with deviations levels within what is seen in actual physical devices. It also scales to 1, 000s of devices and at a modest cloud computing costs of under 0.15% of the actual hardware cost, per hour of use, with minimal management effort. This IoT emulation environment fills an essential gap between IoT simulators and real deployments.","PeriodicalId":7055,"journal":{"name":"ACM Transactions on Cyber-Physical Systems","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3446346","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"64037409","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}

{"title":"TangleCV: A Distributed Ledger Technique for Secure Message Sharing in Connected Vehicles","authors":"Heena Rathore, A. Samant, Murtuza Jadliwala","doi":"10.1145/3404500","DOIUrl":"https://doi.org/10.1145/3404500","url":null,"abstract":"ing with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from permissions@acm.org. © 2020 Association for Computing Machinery. 2378-962X/2020/12-ART6 $15.00 https://doi.org/10.1145/3404500 ACM Transactions on Cyber-Physical Systems, Vol. 5, No. 1, Article 6. Publication date: December 2020. 6:2 H. Rathore et al. ACM Reference format: Heena Rathore, Abhay Samant, and Murtuza Jadliwala. 2020. TangleCV: A Distributed Ledger Technique for Secure Message Sharing in Connected Vehicles. ACM Trans. Cyber-Phys. Syst. 5, 1, Article 6 (December 2020), 25 pages. https://doi.org/10.1145/3404500","PeriodicalId":7055,"journal":{"name":"ACM Transactions on Cyber-Physical Systems","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3404500","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"64029788","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}

{"title":"Assessing the Severity of Smart Attacks in Industrial Cyber-Physical Systems","authors":"Abdelaziz Khaled, Samir Ouchani, Z. Tari, K. Drira","doi":"10.1145/3422369","DOIUrl":"https://doi.org/10.1145/3422369","url":null,"abstract":"Industrial cyber-physical systems (ICPS) are heterogeneous inter-operating parts that can be physical, technical, networking, and even social like agent operators. Incrementally, they perform a central role in critical and industrial infrastructures, governmental, and personal daily life. Especially with the Industry 4.0 revolution, they became more dependent on the connectivity by supporting novel communication and distance control functionalities, which expand their attack surfaces that result in a high risk for cyber-attacks. Furthermore, regarding physical and social constraints, they may push up new classes of security breaches that might result in serious economic damages. Thus, designing a secure ICPS is a complex task, since this needs to guarantee security and harmonize the functionalities between the various parts that interact with different technologies. This article highlights the significance of cyber-security infrastructure and shows how to evaluate, prevent, and mitigate ICPS-based cyber-attacks. We carried out this objective by establishing an adequate semantics for ICPS’s entities and their composition, which includes social actors that act differently than mobile robots and automated processes. This article also provides the feasible attacks generated by a reinforcement learning mechanism based on multiple criteria that selects both appropriate actions for each ICPS component and the possible countermeasures for mitigation. To efficiently analyze ICPS’s security, we proposed a model-checking-based framework that relies on a set of predefined attacks from where the security requirements are used to assess how well the model is secure. Finally, to show the effectiveness of the proposed solution, we model, analyze, and evaluate the ICPS security on two real use cases.","PeriodicalId":7055,"journal":{"name":"ACM Transactions on Cyber-Physical Systems","volume":null,"pages":null},"PeriodicalIF":2.3,"publicationDate":"2020-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3422369","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46231272","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}