R. Bhadani, Matt Bunting, Benjamin Seibold, Raphael E. Stern, Shumo Cui, J. Sprinkle, B. Piccoli, D. Work
In this paper we describe an experience report and field deployment of real-time filtering algorithms used with a robotic vehicle to smooth emergent traffic waves. When smoothing these waves in simulation, a common approach is to implement controllers that utilize space gap, relative velocity and even acceleration from smooth ground truth information, rather than from realistic data. As a result, many results may be limited in their impact when considering the dynamics of the vehicle under control and the discretized nature of the laser data as well as its periodic arrival. Our approach discusses trade-offs in estimation accuracy to provide both distance and velocity estimates, with ground-truth hardware-in-the-loop tests with a robotic car. The contribution of the work enabled an experiment with 21 vehicles, including the robotic car closing the loop at up to 8.0 m/s with the filtered estimates, stressing the importance of an algorithm that can deliver real-time results with acceptable accuracy for the safety of the drivers in the experiment.
{"title":"Real-time distance estimation and filtering of vehicle headways for smoothing of traffic waves","authors":"R. Bhadani, Matt Bunting, Benjamin Seibold, Raphael E. Stern, Shumo Cui, J. Sprinkle, B. Piccoli, D. Work","doi":"10.1145/3302509.3314026","DOIUrl":"https://doi.org/10.1145/3302509.3314026","url":null,"abstract":"In this paper we describe an experience report and field deployment of real-time filtering algorithms used with a robotic vehicle to smooth emergent traffic waves. When smoothing these waves in simulation, a common approach is to implement controllers that utilize space gap, relative velocity and even acceleration from smooth ground truth information, rather than from realistic data. As a result, many results may be limited in their impact when considering the dynamics of the vehicle under control and the discretized nature of the laser data as well as its periodic arrival. Our approach discusses trade-offs in estimation accuracy to provide both distance and velocity estimates, with ground-truth hardware-in-the-loop tests with a robotic car. The contribution of the work enabled an experiment with 21 vehicles, including the robotic car closing the loop at up to 8.0 m/s with the filtered estimates, stressing the importance of an algorithm that can deliver real-time results with acceptable accuracy for the safety of the drivers in the experiment.","PeriodicalId":413733,"journal":{"name":"Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125658407","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}
Praveen Venkateswaran, M. Suresh, N. Venkatasubramanian
Instrumenting water distribution networks with sensors for monitoring is critical to maintain adequate levels of water quality and quantity. Existing efforts to detect and localize adverse events in the network have explored either installing in-situ sensors on junctions or deploying a number of mobile sensors through pipes. These approaches have high costs, low sensing accuracy, lack sufficient coverage or provide intermittent monitoring. In this paper, we combine the benefits of in-situ and mobile sensing with various geosocial factors to develop a cost-effective hybrid monitoring architecture that minimizes the impact of adverse water events on the community. The architecture can adaptively adjust sensing resolutions on-demand within the network, determine required sensing capabilities based on the event, and respond to varying event severities. We propose a two-phase planning and deployment approach that first integrates network structure, event, and community information with simulation based analytics to determine locations to install in-situ sensors and mobile sensor insertion infrastructure. We then incorporate network flow information to determine mobile sensor deployment locations and volume to quickly localize detected events to minimize their impact. We evaluate our approach using multiple real-world water networks for adverse water quality and loss events and compare it to existing approaches. Our results show that our proposed approach can achieve upto 79% reduction in impact with upto 68% greater cost efficiency compared to approaches using traditional coverage heuristics, and upto 30% reduction in impact while being upto 52% more cost efficient compared to approaches that attempt to minimize impact.
{"title":"Augmenting in-situ with mobile sensing for adaptive monitoring of water distribution networks","authors":"Praveen Venkateswaran, M. Suresh, N. Venkatasubramanian","doi":"10.1145/3302509.3311048","DOIUrl":"https://doi.org/10.1145/3302509.3311048","url":null,"abstract":"Instrumenting water distribution networks with sensors for monitoring is critical to maintain adequate levels of water quality and quantity. Existing efforts to detect and localize adverse events in the network have explored either installing in-situ sensors on junctions or deploying a number of mobile sensors through pipes. These approaches have high costs, low sensing accuracy, lack sufficient coverage or provide intermittent monitoring. In this paper, we combine the benefits of in-situ and mobile sensing with various geosocial factors to develop a cost-effective hybrid monitoring architecture that minimizes the impact of adverse water events on the community. The architecture can adaptively adjust sensing resolutions on-demand within the network, determine required sensing capabilities based on the event, and respond to varying event severities. We propose a two-phase planning and deployment approach that first integrates network structure, event, and community information with simulation based analytics to determine locations to install in-situ sensors and mobile sensor insertion infrastructure. We then incorporate network flow information to determine mobile sensor deployment locations and volume to quickly localize detected events to minimize their impact. We evaluate our approach using multiple real-world water networks for adverse water quality and loss events and compare it to existing approaches. Our results show that our proposed approach can achieve upto 79% reduction in impact with upto 68% greater cost efficiency compared to approaches using traditional coverage heuristics, and upto 30% reduction in impact while being upto 52% more cost efficient compared to approaches that attempt to minimize impact.","PeriodicalId":413733,"journal":{"name":"Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126157362","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}
We propose to demonstrate the open source implementation of nfer (http://nfer.io), a language and system for abstracting event streams. The tool is applicable to a wide variety of cyber-physical systems, and supports both manual and mined specifications. In addition to basic operation, we will demonstrate standalone monitor generation and integration with the popular R and Python languages. The demonstration will use real-world data captured from applications such as an autonomous vehicle and a hexacopter.
{"title":"Event stream abstraction using nfer: demo abstract","authors":"S. Kauffman, S. Fischmeister","doi":"10.1145/3302509.3313327","DOIUrl":"https://doi.org/10.1145/3302509.3313327","url":null,"abstract":"We propose to demonstrate the open source implementation of nfer (http://nfer.io), a language and system for abstracting event streams. The tool is applicable to a wide variety of cyber-physical systems, and supports both manual and mined specifications. In addition to basic operation, we will demonstrate standalone monitor generation and integration with the popular R and Python languages. The demonstration will use real-world data captured from applications such as an autonomous vehicle and a hexacopter.","PeriodicalId":413733,"journal":{"name":"Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems","volume":"26 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131726490","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}
Losses stemming from energy theft and system faults are a major challenge to providing reliable electrical service in developing areas of the world. Managing these losses is a vital part of ensuring energy distribution system stability and maintaining a functioning microgrid. Despite this, even losses that are detected are often not addressed by microgrid operators due to the difficulty of locating unauthorized loads, especially in deployments serving hundreds or thousands of households. In this paper, we propose a method for the localization of unauthorized loads based on the fine-grained sensing of voltage phase across a microgrid. Unlike other approaches, the proposed method utilizes synchronous voltage sensing at smart meters and does not rely on expensive inline power metering. Voltage phase measurements feed a graphical model of a power distribution network, which yields the locations of loads as they connect to the system. We evaluate our method using a circuit-based approach in SPICE by simulating loads on a real-world microgrid topology. We then validate our simulation results on a laboratory microgrid testbed using real loads, showing that fine-grained voltage sensing can be effectively leveraged to localize unauthorized loads in microgrids.
{"title":"Localizing loads in microgrids using high-precision voltage phase","authors":"Maxim Buevich, Anthony G. Rowe","doi":"10.1145/3302509.3311037","DOIUrl":"https://doi.org/10.1145/3302509.3311037","url":null,"abstract":"Losses stemming from energy theft and system faults are a major challenge to providing reliable electrical service in developing areas of the world. Managing these losses is a vital part of ensuring energy distribution system stability and maintaining a functioning microgrid. Despite this, even losses that are detected are often not addressed by microgrid operators due to the difficulty of locating unauthorized loads, especially in deployments serving hundreds or thousands of households. In this paper, we propose a method for the localization of unauthorized loads based on the fine-grained sensing of voltage phase across a microgrid. Unlike other approaches, the proposed method utilizes synchronous voltage sensing at smart meters and does not rely on expensive inline power metering. Voltage phase measurements feed a graphical model of a power distribution network, which yields the locations of loads as they connect to the system. We evaluate our method using a circuit-based approach in SPICE by simulating loads on a real-world microgrid topology. We then validate our simulation results on a laboratory microgrid testbed using real loads, showing that fine-grained voltage sensing can be effectively leveraged to localize unauthorized loads in microgrids.","PeriodicalId":413733,"journal":{"name":"Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems","volume":"28 7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125689937","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}
The status quo of control in water distribution networks (WDN) relies on simple, rule-based control strategies to operate pumps and valves. For example, pumps are switched on/off if a tank's water level---a local measurement---is below/above a certain threshold. As an alternative to localized, rule-based control, network-driven control that utilize WDN topology and measurements can be beneficial. Unfortunately, network-driven control of WDNs is very difficult as hydraulic models are nonconvex, valve and pump models form non-trivial, combinatorial logic, and water demand patterns are uncertain. Prior research on control of WDNs addressed major research challenges, yet mostly adopted simplified hydraulic models, WDN topologies, and rudimentary valve/pump modeling. This Work-in-Progress showcases the potential of network-driven control of WDNs. The proposed approach amounts to solving a series of convex optimization problems that graciously scale to large networks. Simple case studies are included showcasing early results, and applications of the proposed optimization methods to other WDN applications are discussed.
{"title":"Control of water distribution networks using convex approximations: WIP abstract","authors":"Shen Wang, A. Taha, Nikolaos Gatsis, M. Giacomoni","doi":"10.1145/3302509.3313311","DOIUrl":"https://doi.org/10.1145/3302509.3313311","url":null,"abstract":"The status quo of control in water distribution networks (WDN) relies on simple, rule-based control strategies to operate pumps and valves. For example, pumps are switched on/off if a tank's water level---a local measurement---is below/above a certain threshold. As an alternative to localized, rule-based control, network-driven control that utilize WDN topology and measurements can be beneficial. Unfortunately, network-driven control of WDNs is very difficult as hydraulic models are nonconvex, valve and pump models form non-trivial, combinatorial logic, and water demand patterns are uncertain. Prior research on control of WDNs addressed major research challenges, yet mostly adopted simplified hydraulic models, WDN topologies, and rudimentary valve/pump modeling. This Work-in-Progress showcases the potential of network-driven control of WDNs. The proposed approach amounts to solving a series of convex optimization problems that graciously scale to large networks. Simple case studies are included showcasing early results, and applications of the proposed optimization methods to other WDN applications are discussed.","PeriodicalId":413733,"journal":{"name":"Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121602364","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}
This paper proposes a first-principle model of GPS receivers, that allows us to exploit the trade-off between battery consumption and positioning accuracy. We present the model and propose a GPS sampling strategy that uses both the current positioning confidence, and information about the GPS status. We complement the GPS sensor with internal measurement units and show how the given model exposes the battery-accuracy trade-off in the context of sensor fusion. We demonstrate the usefulness of the proposed sampling strategy using both simulation and real data.
{"title":"Modeling of energy consumption in GPS receivers for power aware localization systems","authors":"C. Mandrioli, A. Leva, B. Bernhardsson, M. Maggio","doi":"10.1145/3302509.3311043","DOIUrl":"https://doi.org/10.1145/3302509.3311043","url":null,"abstract":"This paper proposes a first-principle model of GPS receivers, that allows us to exploit the trade-off between battery consumption and positioning accuracy. We present the model and propose a GPS sampling strategy that uses both the current positioning confidence, and information about the GPS status. We complement the GPS sensor with internal measurement units and show how the given model exposes the battery-accuracy trade-off in the context of sensor fusion. We demonstrate the usefulness of the proposed sampling strategy using both simulation and real data.","PeriodicalId":413733,"journal":{"name":"Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122130403","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}
S. Rimer, Abhiram Mullapudi, Sara C. Troutman, B. Kerkez
As storm events in cities are becoming more regular and more intense, urban watersheds and their stormwater networks are becoming stressed beyond their design capacities leading to more frequent and destructive urban flooding events. However, traditional engineering interventions to improve upon these systems are unfavorable as they entail large-scale and cost-prohibitive infrastructure construction, and are a static solution to a dynamic and evolving problem. Recent accessibility of low-cost sensors, microcontrollers, and wireless communication technology has made it possible for the existing stormwater networks to be retrofitted with an assortment of cyber-physical technologies that allow for inexpensive, versatile, minimally-invasive, and fully-automated stormwater control interventions (e.g. hydraulic valve operated by cellularly-connected actuator) [4] [9] [12]. To give an example demonstrating the impact of this automation, one sub-system of a stormwater network that was retrofitted with sensor-actuators demonstrated a performance enhancement of 80% when compared with traditional passive systems [5], with other studies demonstrating similar enhancements [3] [1] [10] [6] [7] [8]. With the demonstrated success of automating individual components of a stormwater network, there now exists the possibility for these individual components to be strategically coordinated and operated to achieve system-level automated control [2] [11] [10], potentially leading to dramatic changes in how entire urban watersheds are able to dynamically respond to storm events. However, given the emerging nature of the smart stormwater networks field, there currently does not exist a framework to (i) objectively compare the performance of the control algorithms behind these smart stormwater interventions, and (ii) assess the generalizability of the control algorithms across a diverse set of stormwater networks and weather events. We have developed a benchmarking framework which provides a means to systematically and objectively compare performance of control algorithms for a variety of stormwater networks. This framework includes the following: (1) A collection of anonymized stormwater networks (based on actual networks) used as case studies for control algorithms to be directly compared, (2) Corresponding storm inputs to these stormwater networks to evaluate the performance of control algorithms across diverse types of storm events, (3) A set of scoring metrics for analyzing the performance of network control and optimization interventions. This benchmarking framework is an effort to make smart stormwater network control problems accessible to control experts outside of the field of water resources engineering. Creating this framework will facilitate future research to focus on the development and implementation of control algorithms, minimizing the prior need to first master stormwater simulation. The framework will be hosted online such that the testing and comparis
{"title":"A benchmarking framework for control and optimization of smart stormwater networks: demo abstract","authors":"S. Rimer, Abhiram Mullapudi, Sara C. Troutman, B. Kerkez","doi":"10.1145/3302509.3313336","DOIUrl":"https://doi.org/10.1145/3302509.3313336","url":null,"abstract":"As storm events in cities are becoming more regular and more intense, urban watersheds and their stormwater networks are becoming stressed beyond their design capacities leading to more frequent and destructive urban flooding events. However, traditional engineering interventions to improve upon these systems are unfavorable as they entail large-scale and cost-prohibitive infrastructure construction, and are a static solution to a dynamic and evolving problem. Recent accessibility of low-cost sensors, microcontrollers, and wireless communication technology has made it possible for the existing stormwater networks to be retrofitted with an assortment of cyber-physical technologies that allow for inexpensive, versatile, minimally-invasive, and fully-automated stormwater control interventions (e.g. hydraulic valve operated by cellularly-connected actuator) [4] [9] [12]. To give an example demonstrating the impact of this automation, one sub-system of a stormwater network that was retrofitted with sensor-actuators demonstrated a performance enhancement of 80% when compared with traditional passive systems [5], with other studies demonstrating similar enhancements [3] [1] [10] [6] [7] [8]. With the demonstrated success of automating individual components of a stormwater network, there now exists the possibility for these individual components to be strategically coordinated and operated to achieve system-level automated control [2] [11] [10], potentially leading to dramatic changes in how entire urban watersheds are able to dynamically respond to storm events. However, given the emerging nature of the smart stormwater networks field, there currently does not exist a framework to (i) objectively compare the performance of the control algorithms behind these smart stormwater interventions, and (ii) assess the generalizability of the control algorithms across a diverse set of stormwater networks and weather events. We have developed a benchmarking framework which provides a means to systematically and objectively compare performance of control algorithms for a variety of stormwater networks. This framework includes the following: (1) A collection of anonymized stormwater networks (based on actual networks) used as case studies for control algorithms to be directly compared, (2) Corresponding storm inputs to these stormwater networks to evaluate the performance of control algorithms across diverse types of storm events, (3) A set of scoring metrics for analyzing the performance of network control and optimization interventions. This benchmarking framework is an effort to make smart stormwater network control problems accessible to control experts outside of the field of water resources engineering. Creating this framework will facilitate future research to focus on the development and implementation of control algorithms, minimizing the prior need to first master stormwater simulation. The framework will be hosted online such that the testing and comparis","PeriodicalId":413733,"journal":{"name":"Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121904813","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}
Charles Hartsell, N. Mahadevan, Shreyas Ramakrishna, A. Dubey, T. Bapty, G. Karsai
Cyber-Physical Systems (CPS) are expected to perform tasks with ever-increasing levels of autonomy, often in highly uncertain environments. Traditional design techniques based on domain knowledge and analytical models are often unable to cope with epistemic uncertainties present in these systems. This challenge, combined with recent advances in machine learning, has led to the emergence of Learning-Enabled Components (LECs) in CPS. However, very little tool support is available for design automation of these systems. In this demonstration, we introduce an integrated toolchain for the development of CPS with LECs with support for architectural modeling, data collection, system software deployment, and LEC training, evaluation, and verification. Additionally, the toolchain supports the modeling and analysis of safety cases - a critical part of the engineering process for mission and safety critical systems.
{"title":"A CPS toolchain for learning-based systems: demo abstract","authors":"Charles Hartsell, N. Mahadevan, Shreyas Ramakrishna, A. Dubey, T. Bapty, G. Karsai","doi":"10.1145/3302509.3313332","DOIUrl":"https://doi.org/10.1145/3302509.3313332","url":null,"abstract":"Cyber-Physical Systems (CPS) are expected to perform tasks with ever-increasing levels of autonomy, often in highly uncertain environments. Traditional design techniques based on domain knowledge and analytical models are often unable to cope with epistemic uncertainties present in these systems. This challenge, combined with recent advances in machine learning, has led to the emergence of Learning-Enabled Components (LECs) in CPS. However, very little tool support is available for design automation of these systems. In this demonstration, we introduce an integrated toolchain for the development of CPS with LECs with support for architectural modeling, data collection, system software deployment, and LEC training, evaluation, and verification. Additionally, the toolchain supports the modeling and analysis of safety cases - a critical part of the engineering process for mission and safety critical systems.","PeriodicalId":413733,"journal":{"name":"Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116227418","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}
Workflow technologies provide sophisticated concepts and tools for a simplified high-level programming of enterprise applications across individual systems and organizational borders. They are also useful to compose flexible and reusable workflows in cyber-physical systems (CPS) involving hardware devices, software applications, smart objects and humans. In this work, we discuss the concepts of Cyber-physical Consistency and Cyber-physical Synchronization for workflows in CPS. Consistency enables verification of the workflow execution by comparing the assumed virtual world outcome with the actual effects in the physical world. Synchronization is used for restoring a consistent state in case of deviations realized by the MAPE-K control loop for self-adaptive systems. We discuss these concepts based on example workflows in the smart home domain.
{"title":"Consistency and synchronization for workflows in cyber-physical systems: poster abstract","authors":"Ronny Seiger, U. Assmann","doi":"10.1145/3302509.3313317","DOIUrl":"https://doi.org/10.1145/3302509.3313317","url":null,"abstract":"Workflow technologies provide sophisticated concepts and tools for a simplified high-level programming of enterprise applications across individual systems and organizational borders. They are also useful to compose flexible and reusable workflows in cyber-physical systems (CPS) involving hardware devices, software applications, smart objects and humans. In this work, we discuss the concepts of Cyber-physical Consistency and Cyber-physical Synchronization for workflows in CPS. Consistency enables verification of the workflow execution by comparing the assumed virtual world outcome with the actual effects in the physical world. Synchronization is used for restoring a consistent state in case of deviations realized by the MAPE-K control loop for self-adaptive systems. We discuss these concepts based on example workflows in the smart home domain.","PeriodicalId":413733,"journal":{"name":"Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems","volume":"51 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126001925","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}
Takafumi Harada, Keita Hasegawa, Yu Dan, T. Washio, Yoshihito Oshima
Cooperative ITS (CITS) is expected to contribute to a safer and more efficient transportation society by using sensor data shared from connected vehicles. To ensure the safety of such systems, we are working on technology for detecting and responding to cyber attacks via malicious information transmission against CITS. In this demonstration, the following two scenarios are visualized based on the assumption that a service providing the optimum route using sensor-probe information will be implemented in the near future. In the first scenario, using simulations of the Tokyo Metropolitan Expressway traffic flow, we show the potential threats of false-data-injection attacks on transmitted sensor information. In the second scenario, we show that our new detect-and-respond technology can mitigate these threats.
{"title":"Security analysis for cits-soc using sensor data from connected vehicles: demo abstract","authors":"Takafumi Harada, Keita Hasegawa, Yu Dan, T. Washio, Yoshihito Oshima","doi":"10.1145/3302509.3313333","DOIUrl":"https://doi.org/10.1145/3302509.3313333","url":null,"abstract":"Cooperative ITS (CITS) is expected to contribute to a safer and more efficient transportation society by using sensor data shared from connected vehicles. To ensure the safety of such systems, we are working on technology for detecting and responding to cyber attacks via malicious information transmission against CITS. In this demonstration, the following two scenarios are visualized based on the assumption that a service providing the optimum route using sensor-probe information will be implemented in the near future. In the first scenario, using simulations of the Tokyo Metropolitan Expressway traffic flow, we show the potential threats of false-data-injection attacks on transmitted sensor information. In the second scenario, we show that our new detect-and-respond technology can mitigate these threats.","PeriodicalId":413733,"journal":{"name":"Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131234062","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}
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