ACM Transactions on Embedded Computing Systems最新文献_第6页

Improving Worst-case TSN Communication Times of Large Sensor Data Samples by Exploiting Synchronization 利用同步提高大传感器数据样本最坏情况下TSN通信时间

3区计算机科学

ACM Transactions on Embedded Computing Systems Pub Date : 2023-09-11 DOI: 10.1145/3609120

Jonas Peeck, Rolf Ernst

{"title":"Improving Worst-case TSN Communication Times of Large Sensor Data Samples by Exploiting Synchronization","authors":"Jonas Peeck, Rolf Ernst","doi":"10.1145/3609120","DOIUrl":"https://doi.org/10.1145/3609120","url":null,"abstract":"Higher levels of automated driving also require a more sophisticated environmental perception. Therefore, an increasing number of sensors transmit their data samples as frame bursts to other applications for further processing. As a vehicle has to react to its environment in time, such data is subject to safety-critical latency constraints. To keep up with the resulting data rates, there is an ongoing transition to a Time-Sensitive Networking (TSN)-based communication backbone. However, the use of TSN-related industry standards does not match the automotive requirements of large timely sensor data transmission, nor it offers benefits on time-critical transmissions of single control data packets. By using the full data rate of prioritized IEEE 802.1Q Ethernet, giving time guarantees on large data samples is possible, but with strongly degraded results due to data collision. Resolving such collisions with time-aware shaping comes with significant overhead. Hence, rather than optimizing the parameters of the existing protocol, we propose a system design that synchronizes the transmission times of sensor data samples. This limits network protocol complexity and hardware requirements by avoiding tight time synchronization and time-aware shaping. We demonstrate that individual sensor data samples are transmitted without significant interference, exclusively at full Ethernet data rate. We provide a synchronous event model together with a straightforward response time analysis for synchronous multi-frame sample transmissions. The results show that worst-case latencies of such sample communication, in contrast to non-synchronized approaches, are close to their theoretical minimum as well as to simulative results while keeping the overall network utilization high.","PeriodicalId":50914,"journal":{"name":"ACM Transactions on Embedded Computing Systems","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135981320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Protection Window Based Security-Aware Scheduling against Schedule-Based Attacks 基于保护窗口的安全感知调度防范基于调度的攻击

3区计算机科学

ACM Transactions on Embedded Computing Systems Pub Date : 2023-09-09 DOI: 10.1145/3609098

Jiankang Ren, Chunxiao Liu, Chi Lin, Ran Bi, Simeng Li, Zheng Wang, Yicheng Qian, Zhichao Zhao, Guozhen Tan

{"title":"Protection Window Based Security-Aware Scheduling against Schedule-Based Attacks","authors":"Jiankang Ren, Chunxiao Liu, Chi Lin, Ran Bi, Simeng Li, Zheng Wang, Yicheng Qian, Zhichao Zhao, Guozhen Tan","doi":"10.1145/3609098","DOIUrl":"https://doi.org/10.1145/3609098","url":null,"abstract":"With widespread use of common-off-the-shelf components and the drive towards connection with external environments, the real-time systems are facing more and more security problems. In particular, the real-time systems are vulnerable to the schedule-based attacks because of their predictable and deterministic nature in operation. In this paper, we present a security-aware real-time scheduling scheme to counteract the schedule-based attacks by preventing the untrusted tasks from executing during the attack effective window (AEW). In order to minimize the AEW untrusted coverage ratio for the system with uncertain AEW size, we introduce the protection window to characterize the system protection capability limit due to the system schedulability constraint. To increase the opportunity of the priority inversion for the security-aware scheduling, we design an online feasibility test method based on the busy interval analysis. In addition, to reduce the run-time overhead of the online feasibility test, we also propose an efficient online feasibility test method based on the priority inversion budget analysis to avoid online iterative calculation through the offline maximum slack analysis. Owing to the protection window and the online feasibility test, our proposed approach can efficiently provide best-effort protection to mitigate the schedule-based attack vulnerability while ensuring system schedulability. Experiments show the significant security capability improvement of our proposed approach over the state-of-the-art coverage oriented scheduling algorithm.","PeriodicalId":50914,"journal":{"name":"ACM Transactions on Embedded Computing Systems","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136192427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Modular DFR: Digital Delayed Feedback Reservoir Model for Enhancing Design Flexibility 模块化DFR:提高设计灵活性的数字延迟反馈储层模型

3区计算机科学

ACM Transactions on Embedded Computing Systems Pub Date : 2023-09-09 DOI: 10.1145/3609105

Sosei Ikeda, Hiromitsu Awano, Takashi Sato

引用次数: 0

CrossTalk : Making Low-Latency Fault Tolerance Cheap by Exploiting Redundant Networks 串扰:利用冗余网络降低低延迟容错成本

3区计算机科学

ACM Transactions on Embedded Computing Systems Pub Date : 2023-09-09 DOI: 10.1145/3609436

Andrew Loveless, Linh Thi Xuan Phan, Lisa Erickson, Ronald Dreslinski, Baris Kasikci

{"title":"<scp>CrossTalk</scp> : Making Low-Latency Fault Tolerance Cheap by Exploiting Redundant Networks","authors":"Andrew Loveless, Linh Thi Xuan Phan, Lisa Erickson, Ronald Dreslinski, Baris Kasikci","doi":"10.1145/3609436","DOIUrl":"https://doi.org/10.1145/3609436","url":null,"abstract":"Real-time embedded systems perform many important functions in the modern world. A standard way to tolerate faults in these systems is with Byzantine fault-tolerant (BFT) state machine replication (SMR), in which multiple replicas execute the same software and their outputs are compared by the actuators. Unfortunately, traditional BFT SMR protocols are slow, requiring replicas to exchange sensor data back and forth over multiple rounds in order to reach agreement before each execution. The state of the art in reducing the latency of BFT SMR is eager execution, in which replicas execute on data from different sensors simultaneously on different processor cores. However, this technique results in 3–5× higher computation overheads compared to traditional BFT SMR systems, significantly limiting schedulability. We present CrossTalk, a new BFT SMR protocol that leverages the prevalence of redundant switched networks in embedded systems to reduce latency without added computation. The key idea is to use specific algorithms to move messages between redundant network planes (which many systems already possess) as the messages travel from the sensors to the replicas. As a result, CrossTalk can ensure agreement automatically in the network, avoiding the need for any communication between replicas. Our evaluation shows that CrossTalk improves schedulability by 2.13–4.24× over the state of the art. Moreover, in a NASA simulation of a real spaceflight mission, CrossTalk tolerates more faults than the state of the art while using nearly 3× less processor time.","PeriodicalId":50914,"journal":{"name":"ACM Transactions on Embedded Computing Systems","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136192835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Formal Synthesis of Neural Barrier Certificates for Continuous Systems via Counterexample Guided Learning 通过反例引导学习的连续系统神经屏障证书的形式化合成

3区计算机科学

ACM Transactions on Embedded Computing Systems Pub Date : 2023-09-09 DOI: 10.1145/3609125

Hanrui Zhao, Niuniu Qi, Lydia Dehbi, Xia Zeng, Zhengfeng Yang

引用次数: 0

Probabilistic Reaction Time Analysis 概率反应时间分析

3区计算机科学

ACM Transactions on Embedded Computing Systems Pub Date : 2023-09-09 DOI: 10.1145/3609390

Mario Günzel, Niklas Ueter, Kuan-Hsun Chen, Georg von der Brüggen, Jian-Jia Chen

引用次数: 1

PReFeR : P hysically Re lated F unction bas e d R emote Attestation Protocol 优先级:P物理上相关的功能，R远程认证协议

3区计算机科学

ACM Transactions on Embedded Computing Systems Pub Date : 2023-09-09 DOI: 10.1145/3609104

Anupam Mondal, Shreya Gangopadhyay, Durba Chatterjee, Harishma Boyapally, Debdeep Mukhopadhyay

{"title":"PReFeR : P hysically Re lated F unction bas e d R emote Attestation Protocol","authors":"Anupam Mondal, Shreya Gangopadhyay, Durba Chatterjee, Harishma Boyapally, Debdeep Mukhopadhyay","doi":"10.1145/3609104","DOIUrl":"https://doi.org/10.1145/3609104","url":null,"abstract":"Remote attestation is a request-response based security service that permits a trusted entity (verifier) to check the current state of an untrusted remote device (prover). The verifier initiates the attestation process by sending an attestation challenge to the prover; the prover responds with its current state, which establishes its trustworthiness. Physically Unclonable Function (PUF) offers an attractive choice for hybrid attestation schemes owing to its low overhead security guarantees. However, this comes with the limitation of secure storage of the PUF model or large challenge-response database on the verifier end. To address these issues, in this work, we propose a hybrid attestation framework, named PReFeR , that leverages a new class of hardware primitive known as Physically Related Function (PReF) to remotely attest low-end devices without the requirement of secure storage or heavy cryptographic operations. It comprises a static attestation scheme that validates the memory state of the remote device prior to code execution, followed by a dynamic run-time attestation scheme that asserts the correct code execution by evaluating the content of special registers present in embedded systems, known as hardware performance counters (HPC). The use of HPCs in the dynamic attestation scheme mitigates the popular class of attack known as the time-of-check-time-of-use (TOCTOU) attack, which has broken several state-of-the-art hybrid attestation schemes. We demonstrate our protocol and present our experimental results using a prototype implementation on Digilent Cora Z7 board, a low-cost embedded platform, specially designed for IoT applications.","PeriodicalId":50914,"journal":{"name":"ACM Transactions on Embedded Computing Systems","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136192832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

DaCapo: An On-Device Learning Scheme for Memory-Constrained Embedded Systems DaCapo:一种内存受限嵌入式系统的设备上学习方案

3区计算机科学

ACM Transactions on Embedded Computing Systems Pub Date : 2023-09-09 DOI: 10.1145/3609121

Osama Khan, Gwanjong Park, Euiseong Seo

{"title":"DaCapo: An On-Device Learning Scheme for Memory-Constrained Embedded Systems","authors":"Osama Khan, Gwanjong Park, Euiseong Seo","doi":"10.1145/3609121","DOIUrl":"https://doi.org/10.1145/3609121","url":null,"abstract":"The use of deep neural network (DNN) applications in microcontroller unit (MCU) embedded systems is getting popular. However, the DNN models in such systems frequently suffer from accuracy loss due to the dataset shift problem. On-device learning resolves this problem by updating the model parameters on-site with the real-world data, thus localizing the model to its surroundings. However, the backpropagation step during on-device learning requires the output of every layer computed during the forward pass to be stored in memory. This is usually infeasible in MCU devices as they are equipped only with a few KBs of SRAM. Given their energy limitation and the timeliness requirements, using flash memory to store the output of every layer is not practical either. Although there have been proposed a few research results to enable on-device learning under stringent memory conditions, they require the modification of the target models or the use of non-conventional gradient computation strategies. This paper proposes DaCapo, a backpropagation scheme that enables on-device learning in memory-constrained embedded systems. DaCapo stores only the output of certain layers, known as checkpoints, in SRAM, and discards the others. The discarded outputs are recomputed during backpropagation from the nearest checkpoint in front of them. In order to minimize the recomputation occurrences, DaCapo optimally plans the checkpoints to be stored in the SRAM area at a particular phase of the backpropagation and thus replaces the checkpoints stored in memory as the backpropagation progresses. We implemented the proposed scheme in an STM32F429ZI board and evaluated it with five representative DNN models. Our evaluation showed that DaCapo improved backpropagation time by up to 22% and saved energy consumption by up to 28% in comparison to AIfES, a machine learning platform optimized for MCU devices. In addition, our proposed approach enabled the training of MobileNet, which the MCU device had been previously unable to train.","PeriodicalId":50914,"journal":{"name":"ACM Transactions on Embedded Computing Systems","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136192273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Sound Mixed Fixed-Point Quantization of Neural Networks 神经网络的声音混合不动点量化

3区计算机科学

ACM Transactions on Embedded Computing Systems Pub Date : 2023-09-09 DOI: 10.1145/3609118

Debasmita Lohar, Clothilde Jeangoudoux, Anastasia Volkova, Eva Darulova

{"title":"Sound Mixed Fixed-Point Quantization of Neural Networks","authors":"Debasmita Lohar, Clothilde Jeangoudoux, Anastasia Volkova, Eva Darulova","doi":"10.1145/3609118","DOIUrl":"https://doi.org/10.1145/3609118","url":null,"abstract":"Neural networks are increasingly being used as components in safety-critical applications, for instance, as controllers in embedded systems. Their formal safety verification has made significant progress but typically considers only idealized real-valued networks. For practical applications, such neural networks have to be quantized, i.e., implemented in finite-precision arithmetic, which inevitably introduces roundoff errors. Choosing a suitable precision that is both guaranteed to satisfy a roundoff error bound to ensure safety and that is as small as possible to not waste resources is highly nontrivial to do manually. This task is especially challenging when quantizing a neural network in fixed-point arithmetic, where one can choose among a large number of precisions and has to ensure overflow-freedom explicitly. This paper presents the first sound and fully automated mixed-precision quantization approach that specifically targets deep feed-forward neural networks. Our quantization is based on mixed-integer linear programming (MILP) and leverages the unique structure of neural networks and effective over-approximations to make MILP optimization feasible. Our approach efficiently optimizes the number of bits needed to implement a network while guaranteeing a provided error bound. Our evaluation on existing embedded neural controller benchmarks shows that our optimization translates into precision assignments that mostly use fewer machine cycles when compiled to an FPGA with a commercial HLS compiler than code generated by (sound) state-of-the-art. Furthermore, our approach handles significantly more benchmarks substantially faster, especially for larger networks.","PeriodicalId":50914,"journal":{"name":"ACM Transactions on Embedded Computing Systems","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136192416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Probabilistic Black-Box Checking via Active MDP Learning 基于主动MDP学习的概率黑盒检验

3区计算机科学

ACM Transactions on Embedded Computing Systems Pub Date : 2023-09-09 DOI: 10.1145/3609127

Junya Shijubo, Masaki Waga, Kohei Suenaga

{"title":"Probabilistic Black-Box Checking via Active MDP Learning","authors":"Junya Shijubo, Masaki Waga, Kohei Suenaga","doi":"10.1145/3609127","DOIUrl":"https://doi.org/10.1145/3609127","url":null,"abstract":"We introduce a novel methodology for testing stochastic black-box systems, frequently encountered in embedded systems. Our approach enhances the established black-box checking (BBC) technique to address stochastic behavior. Traditional BBC primarily involves iteratively identifying an input that breaches the system’s specifications by executing the following three phases: the learning phase to construct an automaton approximating the black box’s behavior, the synthesis phase to identify a candidate counterexample from the learned automaton, and the validation phase to validate the obtained candidate counterexample and the learned automaton against the original black-box system. Our method, ProbBBC, refines the conventional BBC approach by (1) employing an active Markov Decision Process (MDP) learning method during the learning phase, (2) incorporating probabilistic model checking in the synthesis phase, and (3) applying statistical hypothesis testing in the validation phase. ProbBBC uniquely integrates these techniques rather than merely substituting each method in the traditional BBC; for instance, the statistical hypothesis testing and the MDP learning procedure exchange information regarding the black-box system’s observation with one another. The experiment results suggest that ProbBBC outperforms an existing method, especially for systems with limited observation.","PeriodicalId":50914,"journal":{"name":"ACM Transactions on Embedded Computing Systems","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136192831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0