An EVT-based worst-case Response Time Analysis of complex real-time systems

A number of methods have been proposed for the response-time analysis (RTA) of controller area networks (CANs), which are the industry standard for in-vehicle network protocols. However, most of these methods are unsuitable for analyzing nonperiodically transmitted messages because they assume a constant transmission period for each message. Moreover, the calculated evaluation criteria are limited and comprise many over-pessimistic estimations, such as the worst-case response time (WCRT). To tackle these problems, this paper proposes an RTA method for CANs with randomly occurring messages, which replaces the constant transmission period with the average number of transmission instances per unit time. This approach finds the approximate probability distribution of the response time to any message in a CAN, providing a more general measure than the WCRT. To this end, a mathematical model based on M/G/1 queueing theory is developed. The model accurately emulates the behavior of nonperiodic CAN messages and enables RTA with minimal pessimistic estimations. When tested against the benchmarks, the proposed method accurately obtained response time distributions within several seconds to several tens of seconds.

MPS-CAN analyzer: Integrated implementation of response-time analyses for Controller Area Network

This paper presents Rapid RT, a novel statistical approach to Worst-Case Response-Time (WCRT) analysis targeting complex embedded real-time systems. The proposed algorithm combines Extreme Value Theory (EVT) and other statistical methods in order to produce a probabilistic WCRT estimate. This estimate is calculated using response time data from either Monte Carlo simulations of a detailed model of the system, or from response-time measurements of the real system. The method could be considered as a pragmatic approach intended for complex industrial systems with real-time requirements. The target systems contain tasks with many intricate dependencies in their temporal behavior, which violates the assumptions of traditional analytical methods for response time analysis and thereby makes them overly pessimistic. An evaluation is presented using two simulation models, inspired by an industrial robotic control system, and five other methods as reference.

In scheduling algorithms based on the Rate Monotonic (RM) method which are widely used in development of real-time systems, tasks with shorter periods have higher priorities. In contrast, ones with longer periods are likely to suffer from increased response times and jitter due to their lower priorities. We propose an Execution Right Delegation (ERD) method based on RM where a high-priority server for particular (or important) task is introduced to shorten response time and jitter of the task. In the evaluation, it is confirmed that response times and jitter of a particular (important) task are reduced. We also show Response Time Analysis (RTA), which assures worst-case response time of the task. This paper shows the algorithm and RTA of ERD and evaluates it by comparing it to a Deadline Monotonic method. The evaluation by simulation shows that ERD can reduce the average worst-case response time by 13.45% at maximum compared to the Deadline Monotonic scheduling. In addition, we confirm that the RTA provides a worst-case response time close to the simulation results.

With the development of multiprocessor technology, multiple processors are increasingly used in embedded real-time systems. The parallelism of multiple processors makes the worst-case response time (WCRT) analysis of multiprocessor real-time systems complicated. In the widely used global fixed-priority (GFP) scheduling, some effective approximate WCRT analysis methods have been proposed. These methods mainly focus on optimizing overall procedure or carry-in workload and assume that the whole carry-out workload of a high-priority task cause interference on the analyzed job. However, through our careful observation of specific examples, the partial carry-out workload of a high-priority task and the analyzed job may be executed in parallel. In other words, the part of parallel carry-out workload of a high-priority task could not cause interference on the analyzed job. In this article, we propose an improved WCRT analysis method by optimizing carry-out interference estimation for GFP scheduling, resulting in a more accurate upper bound of WCRT than the recent advanced methods. Experimental results show that our proposed method is superior than the recent advanced methods in terms of the acceptance rate of the system.

The Controller Area Network (CAN) is widely employed in automotive control system networks. In the last few years, the amount of data has been increasing rapidly in these networks. With the purpose of improving CAN bandwidth efficiency, scheduling and analysis are considered to be particularly important. As an effective method, it has been known that assigning offsets to the CAN messages can reduce their worst case response time (WCRT). Meanwhile, the fact is that many commercial CAN controllers have been equipped with a priority or first-in-first-out (FIFO) queue to transmit messages to the CAN bus. However, previous researches for WCRT analysis of CAN messages either assumed a priority queue or did not consider the offset. For this reason, in this paper we propose a WCRT analysis method for CAN messages with assigned offset in the FIFO queue. We first present a critical instant theorem, then we propose two algorithms for WCRT calculation based on the given theorem. Experimental results on generated message sets and a real message set have validated the effectiveness of the proposed algorithms.

A probabilistic approach to determine response-time distribution for messages in Controller Area Network (CAN) is presented here. CAN is a field bus level communication network for exchanging short real-time messages. CAN is mostly used to carry periodic messages for control and automation systems. Traditional response-time analysis of CAN messages only gives worst-case response-times. This introduces pessimism in analysis, resulting in over designing and under utilization of resources. Response-time distribution is a probabilistic function. Response-time distribution provides a complete characterization of CAN message response-time. It can provide probability of meeting/missing any specified response-time limit. This probability is useful for system reliability and performance modeling. In this paper response-time model of CAN messages is discussed. Technique to derive probabilistic parameters of response-time model, for periodic CAN messages with deterministic transmission times is given. The method has been applied to a standard data set, results are compared with that of worst-case analysis and reasons for deviations are discussed.

Despite the potential of quantum computing for drastically accelerating suitable real-time applications, response time analysis is still required to guarantee that quantum programs running on quantum computers satisfy application-specific timing requirements. This paper describes an inaugural project to determine whether a quantum program running on a quantum computer satisfies the timing constraints of a realtime application, that is, is quantum computing punctual and reliable in this time-sensitive application domain? Can this timing guarantee be formally verified? We leverage the existing work on the functional reactive programming (FRP) model to predict the worst-case response time (WCRT) of fault-tolerant classical computing systems since the timing analysis of re-executions for fault recovery plus transient-faults-induced wasted execution times is similar to determining the response time of FRP tasks. Ongoing work shows that accounting for wasted execution times due to errors in quantum computers resulting from quantum decoherence and state fidelity can be treated similarly and develops a mapping from quantum programs to FRP programs for efficient timing analysis.

Priority-based Functional Reactive Programming (P-FRP) is a new variant of FRP to model reactive applications in real-time systems. In P-FRP, when the currently running task is preempted by an arriving higher-priority task, the lower-priority running task is aborted and the higher-priority task will execute. The lower-priority task restarts when the higher-priority one completes. However, unlike the preemptive model, when a task aborts, all the changes made by this task are discarded. That is to say, when an aborted ask restarts, it should execute from the beginning. In order to provide a realistic Worst-Case Response Time (WCRT) of the tasks in P-FRP, it is therefore mandatory to derive a realistic Worst Case Execution Time (WCET) of each task. Previous studies have ignored memory latency in the derivation of the WCRT, making the resulting estimate inaccurate and unrealistic. Furthermore, these studies have also assumed that the WCET of each task is known a priori. In this paper, we introduce a scratchpad memory (SPM)-based platform for executing P-FRP tasks and an approach to determine the WCET of the tasks by considering the memory cost of the aborted tasks. We first compute the WCET of a task in a P-FRP system, and then calculate the memory penalty caused by preemption. In the next step, we derive the WCRT of the task sets in P-FRP by considering memory latency in the proposed platform. Experimental results from the derivations of the WCET and WCRT using task sets from the SNU real-time benchmarks and randomly generated tasks are presented to validate this approach.

Traditional methods rely on Static Timing Analysis techniques to compute the Worst Case Response Time for tasks in real-time systems. Multi-Core real-time systems are faced up with concurrent task executions, semaphore accesses, and task migrations where it may be difficult to obtain the worst case upper bound. A new three staged probabilistic estimation concept is presented. Worst Case Response Times are estimated for tasksets which consist of tasks with multiple time bases. The concept involves data generation with sample classification and sample size equalization, model fit and Worst Case Response Time estimation on the basis of extreme value distribution models. A Generalized Pareto Distribution model fit method which includes threshold detection and parameter estimation is also presented. Sample classification in combination with the new Generalized Pareto Distribution model fit method allows to estimate Worst Case Response Times with low pessimism ranges compared to estimation methods that uses the Generalized Pareto or the Gumbel max distribution without sample classification.

The Controller Area Network (CAN) is widely used in in-vehicle networks. As increasing the number of Electronic Control Units (ECUs) in an in-vehicle system, the delay of the CAN message is critical issues to achieve high accuracy of the control applications. This protocol employs an arbitration mechanism for priority-based transmission, therefore, although it is easy to estimate the worst-case response time (WCRT) of each message by using real-time scheduling theory, there is no way to know the delay time at which each CAN message was generated in the run-time environment. To address this issue, in this paper, we propose a method is to notify the real delay time of each message without synchronizing to global time between each node in the run-time environment. Our proposed method can provide the delay time of each CAN message with a small improvement so it can be applied for the existing in-vehicle systems.

The well-known model of Vestal aims to avoid excessive pessimism in the quantification of the processing requirements of mixed-criticality systems, while still guaranteeing the timeliness of higher-criticality functions. This can bring important savings in system costs, and indirectly help meet size, weight and power constraints. This efficiency is promoted via the use of multiple worst-case execution time (WCET) estimates for the same task, with each such estimate characterised by a confidence associated with a different criticality level. However, even this approach can be very pessimistic when the WCET of successive instances of the same task can vary greatly according to a known pattern, as in MP3 and MPEG codecs or the processing of ADVB video streams. In this paper, we present a schedulability analysis for the multiframe mixed-criticality model, which allows tasks to have multiple, periodically repeating, WCETs in the same mode of operation. Our work extends both the analysis techniques for Static Mixed-Cricality scheduling (SMC) and Adaptive Mixed-Criticality scheduling (AMC), on one hand, and the schedulability analysis for multiframe task systems on the other. Our proposed worst-case response time (WCRT) analysis for multiframe mixed-criticality systems is considerably less pessimistic than applying the SMC, AMC-rtb and AMC-max tests obliviously to the WCET variation patterns. Experimental evaluation with synthetic task sets demonstrates up to 63.8% higher scheduling success ratio (in absolute terms) compared to the best of the frame-oblivious tests.

The Controller Area Network (CAN) dominates in-vehicle networking systems in modern vehicles. CAN was designed with low-latency and reliability as key features. Authenticity of a CAN frame was not considered in the design, thus, most in-vehicle network nodes inherently trust received messages as coming from a legitimate source. As a result, it is trivial to program (or hack) a network node to spoof traffic. Authentication is challenging for CAN and related protocols, such as SAE J1939, due to limited frame sizes and high bus utilization. Adding a message authentication code (MAC) as a separate message can unduly stress the real-time delivery of safety-critical messages. Although this stressor is well-known, the impact of authentication protocols on real-time message delivery in CAN has not yet been thoroughly examined. In this paper, we provide the first comprehensive analysis of realtime schedulability analysis applied to authentication schemes for CAN, CAN Flexible Data-rate (CAN FD), and CAN extra long payload (CAN XL). We formulate the response time analysis for addition of MACs and periodic transmission of MACs, and we examine their impact on two case studies and through evaluation with randomized schedulability experiments over a wide range of message sets.

The most vehicle manufacturers have been using the CAN (Controller Area Network) in order to communicate among ECUs in vehicle systems for a long time. However, CAN has a disadvantage in that it cannot send and receive large amounts of data quickly due to its limited speed and short data transmission size. The CAN FD (Controller Area Network with Flexible Data rate) was developed to compensate for this disadvantage, and it has the advantage of being able to communicate at more fast speed and eight times the data transmission size compared to CAN. These CAN and CAN FD are vulnerable to message replay attacks because they do not provide data authentication. In this paper, secure communication is implemented by applying CMAC (Cipher based Message Authentication Code) based on CAN and CAN FD. Also, the performance of the two secure communications is compared and analyzed. To implement CMAC, HW-based AES-128 (Advanced Encryption Standard) CBC (Cipher Block Chaining) algorithm is used. This paper compares the performance of Secure CAN and CAN FD communication based on CMAC and can help to check communication traffic of ECU (Electronic Control Unit) in advance when applying the function in the real vehicle system.

Controller Area Network (CAN) is used extensively in automotive applications, with in excess of 400 million CAN enabled microcontrollers manufactured each year. In 1994 schedulability analysis was developed for CAN, showing how worst-case response times of CAN messages could be calculated and hence guarantees provided that message response times would not exceed their deadlines. This seminal research has been cited in over 200 subsequent papers and transferred to industry in the form of commercial CAN schedulability analysis tools. These tools have been used by a large number of major automotive manufacturers in the design of in-vehicle networks for a wide range of cars, millions of which have been manufactured during the last decade.This paper shows that the original schedulability analysis given for CAN messages is flawed. It may provide guarantees for messages that will in fact miss their deadlines in the worst-case. This paper provides revised analysis resolving the problems with the original approach. Further, it highlights that the priority assignment policy, previously claimed to be optimal for CAN, is not in fact optimal and cites a method of obtaining an optimal priority ordering that is applicable to CAN. The paper discusses the possible impact on commercial CAN systems designed and developed using flawed schedulability analysis and makes recommendations for the revision of CAN schedulability analysis tools.