2021 IEEE Real-Time Systems Symposium (RTSS)最新文献

{"title":"Work-in-Progress: Evaluating Task Dropping Strategies for Overloaded Real-Time Systems","authors":"Yiqin Gao, Guillaume Pallez, Y. Robert, F. Vivien","doi":"10.1109/rtss52674.2021.00057","DOIUrl":"https://doi.org/10.1109/rtss52674.2021.00057","url":null,"abstract":"This paper discusses evaluation criteria and scheduling strategies for the analysis of overloaded real-time systems. This work builds upon techniques from queueing theory and proposes a new approach for real-time systems.","PeriodicalId":102789,"journal":{"name":"2021 IEEE Real-Time Systems Symposium (RTSS)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124705397","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":"LAG-Based Analysis Techniques for Scheduling Multiprocessor Hard Real-Time Sporadic DAGs","authors":"Yaswanth Yadlapalli, Cong Liu","doi":"10.1109/rtss52674.2021.00037","DOIUrl":"https://doi.org/10.1109/rtss52674.2021.00037","url":null,"abstract":"Global scheduling of real time tasks with precedence constraints has received significant attention recently. Specifically, on multiprocessor systems, the directed acyclic graph (DAG) model well-represents parallelizable workloads with precedence constraints. Hence, many studies have recently been published analyzing DAG structures using decomposition and window-based analysis methods. We identified a set of schedulable DAG taskets that are hard-to-analyze using state-of-the-art window-based schedulability tests. Additionally, we observe that the window-based test solely depends on one structural feature of the DAG taskset, which raises concerns about its pessimism in many settings. In this paper, to address these concerns, for hard real-time sporadic implicit-deadline DAG tasksets, we perform LAG-based schedulability analysis, which offers a more holistic view of the taskset than the window-based analysis. We present a companion utilization-based schedulability test to the state-of-the-art, which considers additional structural features of DAGs. Our results show that by considering such features, our LAG-based test empirically dominates the state-of-the-art test on over 80% of the evaluated DAG tasksets. Moreover, combining our LAG-based test in conjunction with the window-based tests can achieve high schedulability in many cases.","PeriodicalId":102789,"journal":{"name":"2021 IEEE Real-Time Systems Symposium (RTSS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126852091","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":"Extending EDF for Soft Real-Time Scheduling on Unrelated Multiprocessors","authors":"Stephen Tang, S. Voronov, James H. Anderson","doi":"10.1109/rtss52674.2021.00032","DOIUrl":"https://doi.org/10.1109/rtss52674.2021.00032","url":null,"abstract":"Though recent work has established the soft real-time (SRT)-optimality of Earliest-Deadline-First (EDF) variants on multiprocessor models with limited heterogeneity (e.g., uniform speeds or affinity masks), such models are insufficient to describe modern multiprocessors, which have grown increasingly heterogeneous. This fact highlights the need to extend theoretical results to more asymmetric models, such as the unrelated multiprocessor model. This paper presents an EDF variant tailored for this model and proves that it is at least nearly SRT-optimal. Simulation results for random task systems are also presented that suggest that the proposed EDF variant may actually be SRT-optimal.","PeriodicalId":102789,"journal":{"name":"2021 IEEE Real-Time Systems Symposium (RTSS)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126463682","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":"Work-in-Progress: Automatically Generated Response-Time Proofs as Evidence of Timeliness","authors":"Marco Maida, S. Bozhko, Björn B. Brandenburg","doi":"10.1109/rtss52674.2021.00053","DOIUrl":"https://doi.org/10.1109/rtss52674.2021.00053","url":null,"abstract":"In this paper, we report on the ongoing development of POET, the first foundational and automated response-time analysis tool. The certificates produced by POET are short, readable, and fully commented Coq files that can be machine-checked in (usually) minutes.","PeriodicalId":102789,"journal":{"name":"2021 IEEE Real-Time Systems Symposium (RTSS)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128987425","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":"A ROS 2 Response-Time Analysis Exploiting Starvation Freedom and Execution-Time Variance","authors":"Tobias Blass, Daniel Casini, S. Bozhko, Björn B. Brandenburg","doi":"10.1109/rtss52674.2021.00016","DOIUrl":"https://doi.org/10.1109/rtss52674.2021.00016","url":null,"abstract":"Robots are commonly subject to real-time constraints. To ensure that such constraints are met, recent work has analyzed the response times of processing chains under ROS 2, a popular robotics framework. However, prior work supports only scalar worst-case execution time bounds and does not exploit that the ROS 2 scheduling mechanism is starvation-free. This paper proposes a novel response-time analysis for ROS 2 processing chains that accounts for both the high execution-time variance typically encountered in robotics workloads and the starvation freedom of the default ROS 2 callback scheduler. Experimental results from both synthetic callback graphs and a real ROS 2 workload empirically show the proposed analysis to be much more accurate (often by a factor of 2x or more).","PeriodicalId":102789,"journal":{"name":"2021 IEEE Real-Time Systems Symposium (RTSS)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133097014","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":"Speculative Execution and Timing Predictability in an Open Source RISC-V Core","authors":"Alban Gruin, Thomas Carle, H. Cassé, Christine Rochange","doi":"10.1109/rtss52674.2021.00043","DOIUrl":"https://doi.org/10.1109/rtss52674.2021.00043","url":null,"abstract":"We present MINOTAuR, a timing predictable open source RISC-V core based on the Ariane core [28]. We first modify Ariane in order to make it timing predictable following the approach used to design the SIC processor [11]. We prove that the instruction parallelism in the Ariane core does not prevent from enforcing timing predictability. We further relax restrictions by enabling a limited amount of speculative execution and we are still able to formally prove that the core is timing predictable. Experimental results show that the performance is reduced by only 10% on average compared to the original Ariane core.","PeriodicalId":102789,"journal":{"name":"2021 IEEE Real-Time Systems Symposium (RTSS)","volume":"2020 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131781340","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":"Work-in-Progress: Reinforcement Learning-Based DAG Scheduling Algorithm in Clustered Many-Core Platform","authors":"Atsushi Yano, Takuya Azumi","doi":"10.1109/rtss52674.2021.00062","DOIUrl":"https://doi.org/10.1109/rtss52674.2021.00062","url":null,"abstract":"Embedded systems have become extensive, complex, and automated; thus, increasingly, computing platforms for such systems are being transformed into multi-/many-core platforms. Typically, self-driving systems, involve various applications that run simultaneously, and such systems require low power consumption and large-scale computation. A many-core processor with instructions, multiple data architecture can satisfy these requirements. Shortening the time required to execute all tasks (i.e., makespan) is an important objective in task scheduling for parallel real-time systems, such as self-driving system. Machine learning algorithms have been introduced to solve this kind of problem. This paper proposes a reinforcement learning-based scheduling algorithm for parallel real-time systems represented by a directed acyclic graph (DAG), and Kalray's MPPA3-80 is used as a target many-core processor.","PeriodicalId":102789,"journal":{"name":"2021 IEEE Real-Time Systems Symposium (RTSS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131781786","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":"Enumeration and Deduction Driven Co-Synthesis of CCSL Specifications using Reinforcement Learning","authors":"Ming Hu, Jiepin Ding, M. Zhang, F. Mallet, Mingsong Chen","doi":"10.1109/rtss52674.2021.00030","DOIUrl":"https://doi.org/10.1109/rtss52674.2021.00030","url":null,"abstract":"The Clock Constraint Specification Language (CCSL) has become popular for modeling and analyzing timing behaviors of real-time embedded systems. However, it is difficult for requirement engineers to accurately figure out CCSL specifications from natural language-based requirement descriptions. This is mainly because: i) most requirement engineers lack expertise in formal modeling; and ii) few existing tools can be used to facilitate the generation of CCSL specifications. To address these issues, this paper presents a novel approach that combines the merits of both Reinforcement Learning (RL) and deductive techniques in logical reasoning for efficient co-synthesis of CCSL specifications. Specifically, our method leverages RL to enumerate all the feasible solutions to fill the holes of incomplete specifications and deductive techniques to judge the quality of each trial. Our proposed deductive mechanisms are useful for not only pruning enumeration space, but also guiding the enumeration process to reach an optimal solution quickly. Comprehensive experimental results on both well-known benchmarks and complex industrial examples demonstrate the performance and scalability of our method. Compared with the state-of-the-art, our approach can drastically reduce the synthesis time by several orders of magnitude while the accuracy of synthesis can be guaranteed.","PeriodicalId":102789,"journal":{"name":"2021 IEEE Real-Time Systems Symposium (RTSS)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121324873","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":"AI Meets Real-Time: Addressing Real-World Complexities in Graph Response-Time Analysis","authors":"Sergey Voronov, Stephen Tang, Tanya Amert, James H. Anderson","doi":"10.1109/rtss52674.2021.00019","DOIUrl":"https://doi.org/10.1109/rtss52674.2021.00019","url":null,"abstract":"Artificial-intelligence algorithms are enabling ever more sophisticated autonomous features in safety-critical application domains. These algorithms can be quite complex — consisting of many tasks interconnected in processing graphs — and often must execute on complex heterogeneous hardware — typically multicore machines augmented with one or more hardware accelerators. To further complicate matters, these processing graphs often must be supported in contexts where a large system is broken into smaller components. With this confluence of factors, existing response-time analysis for processing graphs is not applicable. In this paper, such analysis is extended to address these complexities in systems where components are isolated via time partitioning. Additionally, graph restructuring methods are presented that enable response-time bounds to be reduced.","PeriodicalId":102789,"journal":{"name":"2021 IEEE Real-Time Systems Symposium (RTSS)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126494665","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":"Concurrent Order Dispatch for Instant Delivery with Time-Constrained Actor-Critic Reinforcement Learning","authors":"Baoshen Guo, Shuai Wang, Yi Ding, Guang Wang, Suining He, Desheng Zhang, Tian He","doi":"10.1109/rtss52674.2021.00026","DOIUrl":"https://doi.org/10.1109/rtss52674.2021.00026","url":null,"abstract":"Instant delivery has developed rapidly in recent years and significantly changed the lifestyle of people due to its timeliness and convenience. In instant delivery, the order dispatch process is concurrent. Couriers take new orders continuously and deliver multiple orders in a delivery trip (i.e., a batch). The delivery time of orders in a batch is often overlapped and interlinked with each other. The pickup and delivery sequence of the existing orders in a batch changes dynamically due to time constraints and real-time overdue possibility (i.e., the rate of deliveries that are not finished in promised time). Most of existing order dispatch mechanisms are designed for independent order dispatch or concurrent delivery without strict time constraints, hence are incapable of handling real-time concurrent dispatch with strict time constraints in on-demand instant delivery.To address the challenge, we propose a Time-Constrained Actor-Critic Reinforcement learning based concurrent dispatch system called TCAC-Dispatch to enhance the long-term overall revenue and reduce the overdue rate. Specifically, we design a deep matching network (DMN) with a variable action space, which integrates the state embedding (including route behaviors encoding) and actions embedding features into a long-term matching value. Then the Actor-Critic model tackles the concurrent order dispatch problem considering strict time constraints and stochastic demand-supply in instant delivery. An estimated-time based action pruning module is designed to ensure time constraints guarantee and accelerate the training as well as dispatching processes. We evaluate the TCAC-Dispatch with one-month data involved with 36.48 million orders and 42,000 couriers collected from one of the largest instant delivery companies in China, i.e., Eleme. Empirical experiments are conducted on a data-driven emulator deployed on the development environment of Eleme and results show that our method achieves 22% of the increase in total revenue and reduces the overdue rate by 21.6%.","PeriodicalId":102789,"journal":{"name":"2021 IEEE Real-Time Systems Symposium (RTSS)","volume":"9 12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113959861","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}