{"title":"Work-in-Progress: Non-preemptive Scheduling of Sporadic Gang Tasks on Multiprocessors","authors":"Zheng Dong, Cong Liu","doi":"10.1109/RTSS46320.2019.00052","DOIUrl":"https://doi.org/10.1109/RTSS46320.2019.00052","url":null,"abstract":"Existing works on gang task scheduling mainly focus on the preemptive scheduling case, which contradicts a bit with the non-preemptive executing nature of applying gang scheduling techniques in practice. In this paper, we present a set of non-trivial techniques that can analyze the schedulability of scheduling a hard real-time sporadic gang task system under non-preemptive GEDF on multiprocessors and a utilization-based schedulability test (first-of-its-kind) is derived.","PeriodicalId":102892,"journal":{"name":"2019 IEEE Real-Time Systems Symposium (RTSS)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122004021","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}
Saranya Natarajan, M. Nasri, David Broman, Björn B. Brandenburg, Geoffrey Nelissen
{"title":"From Code to Weakly Hard Constraints: A Pragmatic End-to-End Toolchain for Timed C","authors":"Saranya Natarajan, M. Nasri, David Broman, Björn B. Brandenburg, Geoffrey Nelissen","doi":"10.1109/RTSS46320.2019.00025","DOIUrl":"https://doi.org/10.1109/RTSS46320.2019.00025","url":null,"abstract":"Complex real-time systems are traditionally developed in several disjoint steps: (i) decomposition of applications into sets of recurrent tasks, (ii) worst-case execution time estimation, and (iii) schedulability analysis. Each step is already in itself complex and error-prone, and the composition of all three poses a nontrivial integration problem. In particular, it is challenging to obtain an end-to-end analysis of timing properties of the whole system due to practical differences between the interfaces of tools for extracting task models, execution time analysis, and schedulability tests. To address this problem, we propose a seamless and pragmatic end-to-end compilation and timing analysis toolchain, where source programs are written in a real-time extension of C, called Timed C. The toolchain automatically translates timing primitives into executable code, measures execution times, and verifies temporal correctness using an extended schedulability test for non-preemptive generalized multiframe task sets. Novel aspects of our approach are: (i) both soft and firm tasks can be expressed at the programming language level and stated timing requirements are automatically verified by the schedulability test, and (ii) the schedulability test outputs per-job response-time information that enables a new approach to sensitivity analysis. Specifically, we perform a weakly hard sensitivity analysis that determines the worst-case execution time margins for the strongest still-satisfied (M,K) constraint, where M = m1 +...+ mN denotes the number of deadline misses across the entire task set, and K = {k1,..., kN} is the set of windows of interest of the different tasks. The toolchain is implemented as a source-to-source compiler, freely available as open source, and conveniently distributed as a Docker container.","PeriodicalId":102892,"journal":{"name":"2019 IEEE Real-Time Systems Symposium (RTSS)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127920978","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: Formal Analysis of Hybrid-Dynamic Timing Behaviors in Cyber-Physical Systems","authors":"Li Huang, E. Kang","doi":"10.1109/RTSS46320.2019.00069","DOIUrl":"https://doi.org/10.1109/RTSS46320.2019.00069","url":null,"abstract":"Ensuring correctness of timed behaviors in cyber-physical systems (CPS) using closed-loop verification is challenging due to the hybrid dynamics in both systems and environments. Simulink and Stateflow are tools for model-based design that support a variety of mechanisms for modeling and analyzing hybrid dynamics of real-time embedded systems. In this paper, we present an SMT-based approach for formal analysis of the hybrid-dynamic timing behaviors of CPS modeled in Simulink blocks and Stateflow states (S/S). The hierarchically interconnected S/S are flattened and translated into the input language of SMT solver for formal verification. A translation algorithm is provided to facilitate the translation. Formal verification of timing constraints against the S/S models is reduced to the validity checking of the resulting SMT encodings. The applicability of our approach is demonstrated on an unmanned surface vessel case study.","PeriodicalId":102892,"journal":{"name":"2019 IEEE Real-Time Systems Symposium (RTSS)","volume":"819 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125748396","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}
Jinchao Chen, Chenglie Du, Pengcheng Han, Xiaoyan Du
{"title":"Work-in-Progress: Non-preemptive Scheduling of Periodic Tasks with Data Dependency Upon Heterogeneous Multiprocessor Platforms","authors":"Jinchao Chen, Chenglie Du, Pengcheng Han, Xiaoyan Du","doi":"10.1109/RTSS46320.2019.00059","DOIUrl":"https://doi.org/10.1109/RTSS46320.2019.00059","url":null,"abstract":"Heterogeneous multiprocessor platforms have been widely adopted as an efficient approach to providing high instruction throughput while keeping power and complexity under control. Although this approach can achieve improved performance for large-scale real-time systems, it results in a complex task scheduling problem. All tasks should be scheduled according to a proper strategy such that their deadlines will be met even in the worst case situations. In this work, we study the non-preemptive scheduling problem of periodic tasks with data dependency upon heterogeneous multiprocessor platforms. We first analyze the space, time and precedence constraints of tasks, and propose an exact formulation to determine the schedulability of tasks. Then, inspired from the Heterogeneous Earliest Finish Time (HEFT) algorithm, we present a list-based scheduling heuristic to schedule the jobs generated by the periodic tasks and minimize the jobs' finish time. The proposed approach is efficient and can help in guiding the design of heterogeneous multiprocessor systems.","PeriodicalId":102892,"journal":{"name":"2019 IEEE Real-Time Systems Symposium (RTSS)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131346693","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}
Yunkai Yu, Zhihong Yang, Peiyao Li, Zhicheng Yang, Yuyang You
{"title":"Work-in-Progress: On the Feasibility of Lightweight Scheme of Real-Time Atrial Fibrillation Detection Using Deep Learning","authors":"Yunkai Yu, Zhihong Yang, Peiyao Li, Zhicheng Yang, Yuyang You","doi":"10.1109/RTSS46320.2019.00062","DOIUrl":"https://doi.org/10.1109/RTSS46320.2019.00062","url":null,"abstract":"Atrial Fibrillation (AF) is considered to strongly correlate with stroke. Deep Neural Networks (DNNs) improve the accuracy in real-time atrial fibrillation detection. However, the deployment of DNNs on embedded systems is challenging due to hardware resources. To reduce computation loads, we study the feasibility to eliminate the redundant information in the AF detection task by downsampling. It is compatible with kernel-level optimization, quantization optimization, and model compression methods. A state-of-the-art deep learning model is used to estimate the amount of AF detection information among different sampling rates. This work considers both fixed-length and variable-length time intervals of an Electrocardiograph (ECG) segment. Experiment results demonstrate that model performance can be retained perfectly in AF detection. Ablation study experiments demonstrate the robustness with downsampled signals. Using a large time interval, the AF detection accuracy with 60 Hz signals can be compared to that with 300 Hz signals. Our on-going work includes designing lightweight DNN models with downsampled signals, further exploring the robustness of downsampled signals and model compression.","PeriodicalId":102892,"journal":{"name":"2019 IEEE Real-Time Systems Symposium (RTSS)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131301307","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}
Gaoqi He, Zhifu Chai, Xingjian Lu, Fanxin Kong, Bin Sheng
{"title":"ADMM-Based Decentralized Electric Vehicle Charging with Trip Duration Limits","authors":"Gaoqi He, Zhifu Chai, Xingjian Lu, Fanxin Kong, Bin Sheng","doi":"10.1109/RTSS46320.2019.00020","DOIUrl":"https://doi.org/10.1109/RTSS46320.2019.00020","url":null,"abstract":"With the large-scale deployment of Electric Vehicles (EVs), the unbalanced distribution of charging needs and random charging behaviors cause charging stations (CSs) congestion. This degrades EV drivers' quality of experience by extending charging waiting time and increasing charging fee. Thus, EV owners are facing a critical issue on how to decrease the cost of charging, which consists of two parts: charging duration and charging fee. A great deal of existing work is confined to finding CSs to optimize the two parts individually. However, it still remains unexplored how to jointly minimize charging duration and charging fee under an overall time limit (i.e., deadline) of a scheduled trip. The problem is the focus of this paper. First, we formulate this problem as a 0-1 Integer Linear Programming problem and show its NP-Hardness. Then, we propose an efficient distributed algorithm based on the Alternating Direction Method of Multipliers (ADMM). The algorithm decomposes the original problem into sub-problems that can be solved locally and in parallel between charging stations and the global coordinator. Finally, we carry out extensive simulations based on real-life transport network data, and the results show that the proposed approach brings significant cost savings over existing ones.","PeriodicalId":102892,"journal":{"name":"2019 IEEE Real-Time Systems Symposium (RTSS)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133683930","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}
Cédric Courtaud, Julien Sopena, Gilles Muller, D. G. Pérez
{"title":"Improving Prediction Accuracy of Memory Interferences for Multicore Platforms","authors":"Cédric Courtaud, Julien Sopena, Gilles Muller, D. G. Pérez","doi":"10.1109/RTSS46320.2019.00031","DOIUrl":"https://doi.org/10.1109/RTSS46320.2019.00031","url":null,"abstract":"Memory interferences may introduce important slowdowns in applications running on COTS multi-core processors. They are caused by concurrent accesses to shared hardware resources of the memory system. The induced delays are difficult to predict, making memory interferences a major obstacle to the adoption of COTS multi-core processors in real-time systems. In this article, we propose an experimental characterization of applications' memory consumption to determine their sensitivity to memory interferences. Thanks to a new set of microbenchmarks, we show the lack of precision of a purely quantitative characterization. To improve accuracy, we define new metrics quantifying qualitative aspects of memory consumption and implement a profiling tool using the V ALGRIND framework. In addition, our profiling tool produces high resolution profiles allowing us to clearly distinguish the various phases in applications' behavior. Using our microbenchmarks and our new characterization, we train a state-of-the-art regressor. The validation on applications from the M I B ENCH and the PARSEC suites indicates significant gain in prediction accuracy compared to a purely quantitative characterization.","PeriodicalId":102892,"journal":{"name":"2019 IEEE Real-Time Systems Symposium (RTSS)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134060165","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}
Jaeheon Kwak, Kilho Lee, Taehee Kim, Jinkyu Lee, I. Shin
{"title":"Battery Aging Deceleration for Power-Consuming Real-Time Systems","authors":"Jaeheon Kwak, Kilho Lee, Taehee Kim, Jinkyu Lee, I. Shin","doi":"10.1109/RTSS46320.2019.00039","DOIUrl":"https://doi.org/10.1109/RTSS46320.2019.00039","url":null,"abstract":"Battery aging is one of the critical issues in battery-powered electric systems. However, this issue has not received much attention in the real-time systems community. In this paper, we present the first attempt to translate the problem of minimizing battery aging subject to timing requirements into a real-time scheduling problem, addressing the following issues. (i) Can scheduling make a systematic impact on battery aging? If so, which scheduling principles are favorable to minimizing battery aging? (ii) If there exists any, how can we build upon the scheduling principle to guarantee real-time requirements? For (i), we first illuminate the connection between task scheduling and battery aging minimization and then derive a principle for task scheduling from abstracting the complicated dynamics of battery aging, which is to minimize the variance of total power consumption over time. In addition, we implement a battery aging simulator and use it to verify the effectiveness of the proposed principle in minimizing battery aging and its impact on quantitative improvement. For (ii), we propose a scheduling framework that separates control for timing guarantees from that for battery aging minimization. Such a separation allows reducing the complexity significantly such that we can employ existing scheduling algorithm and schedulability analysis for real-time guarantee and tailor the proposed scheduling principle to decelerate battery aging without taking real-time guarantees into accounts. Our simulation results show that the proposed framework can extend the battery lifespan by up to 144.4%.","PeriodicalId":102892,"journal":{"name":"2019 IEEE Real-Time Systems Symposium (RTSS)","volume":"349 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133427364","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: Routing of Delivery Drones with Load-Dependent Flight Speed","authors":"Yusuke Funabashi, Ittetsu Taniguchi, H. Tomiyama","doi":"10.1109/RTSS46320.2019.00054","DOIUrl":"https://doi.org/10.1109/RTSS46320.2019.00054","url":null,"abstract":"Drones draws increasing attention as vehicles for home delivery services. Delivery time is one of the most critical concerns of both customers and delivery service providers. The delivery time depends not only on the flight distance but also on the flight speed, and the flight speed depends on the payload. This paper studies a routing problem for delivery drones considering load-dependent flight speed. This paper formally defines Flight Speed-aware Vehicle Routing Problem (FSVRP) and proposes a dynamic programming algorithm to efficiently solve the problem. Experiments show the effectiveness of the proposed algorithm in terms of quality of results and algorithm runtime.","PeriodicalId":102892,"journal":{"name":"2019 IEEE Real-Time Systems Symposium (RTSS)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133453576","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":"Optimizing the Functional Deployment on Multicore Platforms with Logical Execution Time","authors":"P. Pazzaglia, Alessandro Biondi, M. Natale","doi":"10.1109/RTSS46320.2019.00028","DOIUrl":"https://doi.org/10.1109/RTSS46320.2019.00028","url":null,"abstract":"The move to multicore systems requires methods and tools to support the designer in the partitioning of functions among the available cores and the definition of the task model. In this paper we present the formulation of a functional partitioning for real-time systems and we provide an optimization method for an efficient implementation of the Logical Execution Time (LET) paradigm, to enforce causality and determinism in the development of time-and safety-critical applications. A novel schedulability analysis for partitioned tasks executing according to the LET paradigm is also provided. Our methods are applied to the industry-size model of the WATERS challenge and compute solutions that easily outperform the initial solution provided.","PeriodicalId":102892,"journal":{"name":"2019 IEEE Real-Time Systems Symposium (RTSS)","volume":"2010 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131589851","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}