Date: Thursday 30 March 2017
Time: 11:00 - 12:30
Location / Room: 3B
Chair:
Rolf Ernst, TU Braunschweig, DE
Co-Chair:
Paul PoP, Technical University of Denmark, DK
The session contains four regular papers and four IP papers addressing different aspects of adaptivity and resilience for Cyber-Physical Systems. The topic of the first paper is distributed architectures for deep neural networks executing on a set of mobile nodes. The second paper considers scheduling of imprecise computation tasks on MPSoC systems taking the uncertainty of harvested energy into account. The final two papers both considers resilience of CPS. The first presents a scheme for preventing GPS-based hijacking of drones and the last considers how to avoid adversaries from learning what is printed using a 3D printer. The four IP papers considers control and scheduling co-design, contract-based design, medical CPS, utility-driven data transmission strategies for CPS.
| Time | Label | Presentation Title Authors |
|---|---|---|
| 11:00 | 10.7.1 | (Best Paper Award Candidate) MODNN: LOCAL DISTRIBUTED MOBILE COMPUTING SYSTEM FOR DEEP NEURAL NETWORK Speaker: Kent W. Nixon, University of Pittsburgh, US Authors: Jiachen Mao1, Xiang Chen2, Kent W. Nixon1, Christopher Krieger3 and Yiran Chen1 1University of Pittsburgh, US; 2George Mason University, US; 3University of Maryland, Baltimore County, US Abstract Although Deep Neural Networks (DNN) are ubiquitously utilized in many applications, it is generally difficult to deploy DNNs on resource-constrained devices, e.g., mobile platforms. Some existing attempts mainly focus on client-server computing paradigm or DNN model compression, which require either infrastructure supports or special training phases, respectively. In this work, we propose MoDNN - a local distributed mobile computing system for DNN applications. MoDNN can partition DNN models onto several mobile devices to accelerate DNN computations by alleviating device-level computing cost and memory usage. Two model partition schemes are also designed to minimize non-parallel data delivery time, including both wakeup time and transmission time. Experimental results show that when the number of worker nodes increases from 2 to 4, MoDNN can accelerate the DNN computation by 2.17-4.28×. Besides the parallelled execution, the performance speedup also partially comes from the significant reduction of the data delivery time, e.g., 30.02% w.r.t. conventional 2D-grids partition. Download Paper (PDF; Only available from the DATE venue WiFi) |
| 11:30 | 10.7.2 | ENERGY-ADAPTIVE SCHEDULING OF IMPRECISE COMPUTATION TASKS FOR QOS OPTIMIZATION IN REAL-TIME MPSOC SYSTEMS Speaker: Tongquan Wei, East China Normal University, CN Authors: Junlong Zhou1, Jianming Yan1, Tongquan Wei1, Mingsong Chen1 and X, Sharon Hu2 1East China Normal University, CN; 2University of Notre Dame, US Abstract The key issue of renewable generations such as solar and wind in energy harvesting system is the uncertainty of energy availability. The characteristic of imprecise computation that accepts an approximate result when energy is limited and executes more computations yielding better results if more energy is available, can be exploited to intelligently handle the uncertainty. In this paper, we first propose a task allocation scheme that adaptively assigns real-time imprecise computation tasks to individual processors considering uncertainties in renewable energy sources. The proposed task allocation scheme enhances energy efficiency by minimizing system energy consumption followed by adapting the execution of imprecise computation tasks to the energy availability. We then present a QoS-aware task scheduling scheme that determines the optional execution cycles of tasks allocated to processors. The proposed task scheduling scheme maximizes system QoS under the energy budget constraint. Download Paper (PDF; Only available from the DATE venue WiFi) |
| 12:00 | 10.7.3 | FIX THE LEAK! AN INFORMATION LEAKAGE AWARE SECURED CYBER-PHYSICAL MANUFACTURING SYSTEM Speaker: Mohammad Al Faruque, UCI, US Authors: Sujit Rokka Chhetri1, Sina Faezi1 and Mohammad Al Faruque2 1University of California, Irvine, US; 2University of California Irvine, US Abstract Cyber-physical additive manufacturing systems consists of tight integration of cyber and physical domains. This results in new cross-domain vulnerabilities that poses unique security challenges. One of the challenges is preventing confidentiality breach due to physical-to-cyber domain attacks, where attackers can analyze various analog emissions from the side-channels to steal the cyber-domain information. This information theft is based on the idea that an attacker can accurately estimate the relation between the analog emissions (acoustics, power, electromagnetic emissions, etc.,) and the cyber-domain data (such as G-code). To obstruct this estimation process, it is crucial to quantize the relation between the analog emissions and the cyber-data, and use it as a metric to generate computer aided manufacturing tools, such as slicing and tool-path generation algorithms, that are aware of these information leakage through the side-channels. In this paper, we present a novel methodology that uses mutual information as a metric to quantize the information leakage from the side-channels, and demonstrates how various design variables (such as object orientation, nozzle velocity, etc.,) can be used in an optimization algorithm to minimize the information leakage. Our methodology integrates this leakage aware algorithms to the state-of-the-art slicing and tool-path generation algorithms and achieves 24.76% average drop in the information leakage through acoustic side-channel. To the best of our knowledge, this is the first work that demonstrates the idea of generating information leakage aware computer aided manufacturing tools for protecting the confidentiality of the manufacturing system. Download Paper (PDF; Only available from the DATE venue WiFi) |
| 12:15 | 10.7.4 | EFFICIENT DRONE HIJACKING DETECTION USING ONBOARD MOTION SENSORS Speaker: Zhiwei Feng, Northeastern University, China, CN Authors: Zhiwei Feng1, Nan Guan2, Mingsong Lv1, Weichen Liu3, Qingxu Deng1, Xue Liu4 and Wang Yi1 1Northeastern University, CN; 2Hong Kong Polytechnic University, HK; 3Chongqing University, CN; 4McGill University, CA Abstract The fast growth of civil drones raises significant security challenges. A legitimate drone may be hijacked by GPS spoofing for illegal activities, such as terrorist attacks. The target of this paper is to develop techniques to let drones detect whether they have been hijacked using onboard motion sensors (accelerometers and gyroscopes). Ideally, the linear acceleration and angular velocity measured by motion sensors can be used to estimate the position of a drone, which can be compared with the position reported by GPS to detect whether the drone has been hijacked. However, the position estimation by motion sensors is very inaccurate due to the significant error accumulation over time. In this paper, we propose a novel method to detect hijacking based on motion sensors measurements and GPS, which overcomes the accumulative error problem. The computational complexity of our method is very low, and thus is suitable to be implemented in the micro-controllers of drones. Experiments with a quad-rotor drone are conducted to show the effectiveness of the proposed method. Download Paper (PDF; Only available from the DATE venue WiFi) |
| 12:30 | IP5-3, 813 | ANOMALIES IN SCHEDULING CONTROL APPLICATIONS AND DESIGN COMPLEXITY Speaker: Amir Aminifar, Swiss Federal Institute of Technology in Lausanne, CH Authors: Amir Aminifar1 and Enrico Bini2 1Swiss Federal Institute of Technology in Lausanne (EPFL), CH; 2University of Turin, IT Abstract Today, many control applications in cyber-physical systems are implemented on shared platforms. Such resource sharing may lead to complex timing behaviors and, in turn, instability of control applications. This paper highlights a number of anomalies demonstrating complex timing behaviors caused as a result of resource sharing. Such anomalous scenarios, then, lead to a dramatic increase in design complexity, if not properly considered. Here, we demonstrate that these anomalies are, in fact, very improbable. Therefore, design methodologies for these systems should mainly be devised and tuned towards the majority of cases, as opposed to anomalies, but should also be able to handle such anomalous scenarios. Download Paper (PDF; Only available from the DATE venue WiFi) |
| 12:31 | IP5-4, 843 | CONTRACT-BASED INTEGRATION OF AUTOMOTIVE CONTROL SOFTWARE Speaker: Tobias Sehnke, IAV GmbH, DE Authors: Tobias Sehnke1, Matthias Schultalbers2 and Rolf Ernst3 1Control Engineering Excellence Cluster of IAV GmbH, DE; 2Gasoline Engines, IAV GmbH, DE; 3Inst. of Comput. & Network Eng, Tech. Univ. Braunschweig, DE Abstract The functionalities of automotive control are distributed over a large number of independently developed components that are interconnected by complex data dependencies. During integration it is critical to ensure the functional correctness of each component, due to the safety-critical nature of the automotive system. Thus existing integration processes ensure that interfaces are syntactically correct. Still in many cases communicated signals are semantically incompatible. This results in complicated errors that are hard to detect and fix. Moreover, existing component languages do not provide applicable means for the description and control of correspondent requirements. In this paper we present a novel methodology for an automated identification of integration errors in automotive control software. The key aspect of our approach are contracts, which are used to disclose domain level requirements. These contracts are then checked during integration supported by existing tools. A case study involving an existing engine control software shows the applicability of our approach by detecting a significant number of formerly unknown integration errors. Download Paper (PDF; Only available from the DATE venue WiFi) |
| 12:32 | IP5-5, 736 | MODELING AND INTEGRATING PHYSICAL ENVIRONMENT ASSUMPTIONS IN MEDICAL CYBER-PHYSICAL SYSTEM DESIGN Speaker: Chunhui Guo, Illinois Institute of Technology, US Authors: Zhicheng Fu1, Chunhui Guo1, Shangping Ren1, Yu Jiang2 and Lui Sha3 1Illinois Institute of Technology, US; 2Tsinghua University, CN; 3University of Illinois at Urbana-Champaign, US Abstract Implicit physical environment assumptions made by safety critical cyber-physical systems, such as medical cyber- physical systems (M-CPS), can lead to catastrophes. Several recent U.S. Food and Drug Administration (FDA) medical device recalls are due to implicit physical environment assumptions. In this paper, we develop a mathematical assumption model and composition rules that allow M-CPS engineers to explicitly and precisely specify assumptions about the physical environment in which the designed M-CPS operates. Algorithms are developed to integrate the mathematical assumption model with system model so that the safety of the system can be not only validated by both medical and engineering professionals but also formally verified by existing formal verification tools. We use an FDA recalled medical ventilator scenario as a case study to show how the mathematical assumption model and its integration in M-CPS design may improve the safety of the ventilator and M-CPS in general. Download Paper (PDF; Only available from the DATE venue WiFi) |
| 12:33 | IP5-6, 535 | A UTILITY-DRIVEN DATA TRANSMISSION OPTIMIZATION STRATEGY IN LARGE SCALE CYBER-PHYSICAL SYSTEMS Speaker: Bei Yu, The Chinese University of Hong Kong, HK Authors: Soumi Chattopadhyay1, Ansuman Banerjee1 and Bei Yu2 1Indian Statistical Institute, IN; 2The Chinese University of Hong Kong, HK Abstract In this paper, we examine the problem of data dissemination and optimization in the context of a large scale distributed cyber-physical system (CPS), and propose a novel rule-based mechanism for effective observation collection and transmission. Our work rests on the idea that all observations on all parameters are not required at all times, and thereby, selective data transmission can reduce sensor workload significantly. Experiments show the efficacy of our proposal. Download Paper (PDF; Only available from the DATE venue WiFi) |
| 12:30 | End of session Lunch Break in Garden Foyer Keynote Lecture session 11.0 in "Garden Foyer" 1320 - 1350 Lunch Break in the Garden Foyer |