Towards Probabilistic Modeling and Analysis of Real-Time Systems

In multitasking real-time systems, the choice of scheduling algorithm is an important factor to ensure that response time requirements are met while maximising limited system resources. Two popular scheduling algorithms include fixed priority (FP) and earliest deadline first (EDF). While they have been studied in great detail before, they have not been compared when taking into account cache related pre-emption delays (CRPD). Memory and cache are split into a number of blocks containing instructions and data. During a pre-emption, cache blocks from the pre-empting task can evict those of the pre-empted task. When the pre-empted task is resumed, if it then has to re-load the evicted blocks, CRPD are introduced which then affect the schedulability of the task. In this paper we compare FP and EDF scheduling algorithms in the presence of CRPD using the state-of-the-art CRPD analysis. We find that when CRPD is accounted for, the performance gains offered by EDF over FP, while still notable, are diminished. Furthermore, we find that under scenarios that cause relatively high CRPD, task layout optimisation techniques can be applied to allow FP to schedule tasksets at a similar processor utilisation to EDF. Thus making the choice of the task layout in memory as important as the choice of scheduling algorithm. This is very relevant for industry, as it is much cheaper and simpler to adjust the task layout through the linker than it is to switch the scheduling algorithm.

Scheduling tasks is an essential requirement in most real-time and embedded systems, but leads to unwanted central processing unit (CPU) overheads. The authors present a real-time schedulability algorithm for preemptable, asynchronous and periodic reconfigurable task systems with arbitrary relative deadlines, scheduled on a uniprocessor by an optimal scheduling algorithm based on the earliest deadline first (EDF) principles and on the dynamic reconfiguration. A reconfiguration scenario is assumed to be a dynamic automatic operation allowing addition, removal or update of operating system’s (OS) functional asynchronous tasks. When such a scenario is applied to save the system at the occurrence of hardware-software faults, or to improve its performance, some real-time properties can be violated. The authors propose an intelligent agent-based architecture where a software agent is used to satisfy the user requirements and to respect time constraints. The agent dynamically provides precious technical solutions for users when these constraints are not verified, by removing tasks according to predefined heuristic, or by modifying the worst case execution times (WCETs), periods, and deadlines of tasks in order to meet deadlines and to minimize their response time. They implement the agent to support these services which are applied to a Blackberry Bold 9700 and to a Volvo system and present and discuss the results of experiments.

Timing correctness of hard real-time systems is guaranteed by schedulability analysis and worst-case execution time (WCET) analysis of programs. Traditional WCET analysis mainly deals with application programs and has achieved success in industry. Timing analysis of application programs along cannot guarantee correctness of complete systems consisting RTOS. WCET tools designed for application program analysis have been applied to analyze RTOS routines by several research groups, but poor WCET estimations have been reported. Timing analysis of real-time systems considering both applications and RTOS has not been fully studied. So we intend to give a survey of related work on WCET analysis of RTOS. By summarizing previous work, challenges of WCET analysis of complete real-time systems are presented, and some possible further research potentials are unleashed.

Worst-case execution time (WCET) analysis of systems with data caches is one of the key challenges in real-time systems. Caches exploit the inherent reuse properties of programs by temporarily storing certain memory contents near the processor, in order that further accesses to such contents do not require costly memory transfers. Current worst-case data cache analysis methods focus on specific cache organizations (set-associative LRU, locked, ACDC, etc.), most of the times adapting techniques designed to analyze instruction caches. On the other hand, there are methodologies to analyze the data reuse of a program, independently of the data cache. In this paper we propose a generic WCET analysis framework to analyze data caches taking profit of such reuse information. It includes the categorization of data references and their integration in an IPET model. We apply it to a conventional LRU cache, an ACDC, and other baseline systems, and compare them using the TACLeBench benchmark suite. Our results show that persistence-based LRU analyses dismiss essential information on data, and a reuse-based analysis improves the WCET bound around 17% in average. In general, the best WCET estimations are obtained with optimization level 2, where the ACDC cache performs 39% better than a set-associative LRU.

In this paper we show how to extend classical real time feasibility conditions to take into account kernel overheads for mixed preemptive and non- preemptive periodic tasks with Earliest Deadline First (EDF) scheduling policy. The EDF algorithm allows us to schedule some tasks sets which are not valid with FP/FIFO scheduling policy, the classical scheduling implemented for OSEK. That is why we have improved our OSEK by implementing EDF algorithm. First of all, we identify the sources of overheads that influence the response time of the tasks: the context switching, the mechanisms used to activates/terminates and reschedules tasks, and the granularity of the periodic timer used to implement the periodic task model. We then show how to take into account those overheads in the classical EDF feasibility conditions. We compare the response times computed with theoretical feasibility conditions with kernel overhead to the results obtained on a real implementation. We show that the kernel overheads cannot be neglected and that our theoretical results are valid and can be used for a real-time dimensioning of an OSEK system with EDF scheduling policy. Finally, we compare the performances of our EDF implementation to the FP/FIFO native scheduling showing the benefits of implementing EDF in OSEK.

This paper investigates the relative effectiveness of fixed priority (FP) scheduling in a uniprocessor system compared to earliest deadline first (EDF) scheduling. The quantitative metric used in this comparison is the processor speedup factor, defined as the factor by which processor speed needs to increase to ensure that any task set that is schedulable according to EDF can be scheduled using fixed priorities. In the pre-emptive case, exact speedup factors are known for sporadic task sets with implicit or constrained deadlines. In this paper, we derive exact speedup factors for both pre-emptive and non-pre-emptive fixed priority scheduling of arbitrary deadline sporadic task sets. We also show that the exact speedup factor for the pre-emptive case holds when tasks share resources according to the stack resource policy/deadline floor protocol.

Real-time scheduling under heterogeneous routing for industrial Internet of Things

A real-time system is overloaded when all the tasks in a workload cannot meet their deadlines, and hence a robust algorithm is essential to maximize the number of tasks that meet their deadlines with the minimum number of miss rates and context switching. Although the Rate Monotonic (RM), Earliest Deadline First (EDF), and Least Laxity First (LLF) algorithms optimally perform and schedule tasks on a non-overloaded system, they have deficient performance when the system is overloaded. Therefore, we propose a new scheduling algorithm for uniprocessor and partitioned multiprocessor systems to address the overload situation. Since the proposed scheduling algorithm operates like EDF non-overloaded conditions, the proposed algorithm is optimal for non-overloaded systems. In addition, the proposed algorithm is robust against overloading situations as it executes the maximum possible tasks in the overload situation instead of missing deadlines of many tasks or burdening context switching to the system. The proposed algorithm allocates a processor to tasks based on the possibility of executing the task. The experimental results demonstrate that the proposed scheduling algorithm maximizes the number of tasks that meet their deadlines in overload conditions without a domino effect and context switching. In addition, the proposed algorithm achieves the lowest miss rate without context switching and the highest efficiency and processor utilization in the overloaded system compared with RM, EDF, and LLF.

Internet of Things (IoT) based healthcare applications are time‐sensitive and any delay can cause alarming situations, including death of patients. The Earliest Deadline First (EDF) scheduling scheme has been proposed for use in IoT‐based healthcare applications. However, the EDF scheme performs poorly under overloaded conditions due to giving highest priority to packets that are close to missing their deadlines. Some studies have proposed the use of Priority EDF to overcome the challenges of EDF; however, Priority EDF still favours higher priority queues which increases the waiting times of lower priority queues. In order to overcome the limitation of EDF and its variants, this paper proposes a system model for a prioritized scheduling (PS) scheme. The PS scheme is an improvement of the Earliest Deadline First (EDF) scheme and its variants for IoT‐based healthcare applications. The PS scheme uses a heterogeneous multi‐server priority queuing system to provide service differentiation by prioritizing short packets over large packets and delay sensitive packets are serviced before delay tolerant packets. Numerical results demonstrate that the PS scheme minimizes the mean slowdown for both delay sensitive short and large packets at low and high load values. Additionally, the PS scheme performs better than the EDF and Priority EDF schemes in terms of reducing mean slowdown of packets and the PS scheme performs better than the EDF in terms of throughput for all packet sizes at both low and high load values. The performance improvement in terms of throughput is more pronounced at high load values. This addresses the challenge of the EDF scheme which performs poorly under overloaded conditions and the challenge of the Priority EDF scheme which favours higher priority queues at the expense of low priority queues.

A real-time round robin, which is a novel real-time scheduling algorithm, is proposed in this paper. It is a time slot-based algorithm. Tasks are divided into groups and each group of tasks is statically assigned a subset of time slots. In a group, tasks are scheduled by earliest deadline first (EDF). We introduce subsets of time slots. This has the advantage that any periodic tasks can be scheduled only at time slots contained in the subset using the minimum number of time slots. We show a method to divide the universal set of time slots into at least two regular subsets. Consequently, the real-time round robin algorithm can schedule periodic tasks whose processor utilization factor does not exceed 100% at a lower scheduling cost than that of the EDF algorithm. Moreover, no missed deadline of a task in one group affect the tasks in any other groups.

Thispaperpresentsasensitivityanalysisforthedimensioningofreal-timesystemsinwhich sporadic tasks are executed according to the preemptive earliest deadline first scheduling policy. The timeliness constraints of the tasks are expressed in terms of late termination deadlines. New results for earliest deadline first are shown, which enable us to determine the space of feasible worst-case execution times, denoted the C-space, valid for any configuration of worst-case execution times. The C-space is such that any task set with its worst-case execution times in the C-space domain is feasible with earliest deadline first. We show in a first approach that the C-space domain is convex, a property that can be used to reduce the number of inequalities characterizing the C-space domain.We propose in another approach toreducethenumberofinequalitiesbasedontheconceptofworst-casebusyperiodforworstcase execution times in the C-space. This approach can be used for busy periods meeting a given property. We apply the two approaches on an example, and we compare the Cspace obtained with earliest deadline first scheduling to the C-space obtained with deadline monotonic scheduling.

Cache memories are commonly avoided in real-time systems because of their unpredictable behavior. Recently, some research has been done to obtain tighter bounds on the worst case execution time (WCET) of cached programs. These techniques usually assume a non preemptive underlying system. However, some techniques can be applied to allow the use of caches in preemptive systems. This paper describes how to incorporate the effect of instruction cache to the Response Time schedulability Analysis (RTA). RTA is an efficient analysis for preemptive fixed priority schedulers. We also compare through simulations the results of such an approach to the previously available CRMA (Cached RMA: cache effect is incorporated in the utilization based Rate Monotonic schedulability analysis). The results show that the cached version of RTA (CRTA) clearly outperforms CRMA.

Deriving deadlines and periods for update transactions so as to maintain timeliness and data freshness while minimizing imposed workload has long been recognized an important problem in real-time database research. Despite years of active research, the state-of-the-art still has much room for improvement, particularly for periodic transactions scheduled by the Earliest Deadline First (EDF) algorithm. In this paper, we propose a practical and efficient two-phase algorithm, GEneral EDF (GE <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">EDF</sub> ), for assigning periods and deadlines to EDF-scheduled update transactions. Phase 1 of GE <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">EDF</sub> aims at finding solutions for most inputs in linear time, based on the observation that the execution times of update transactions are relatively small compared to the validity interval lengths of real-time data objects in many real-time applications. In the remaining cases for which Phase 1 fails to derive solutions, Phase 2 is invoked by employing an existing deadline-monotonic-based algorithm, which we show is also applicable to our problem. Meanwhile, we have devised several techniques which significantly reduce the cost of schedulability test, and hence greatly improve time efficiency. Our experimental results demonstrate that GE <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">EDF</sub> outperforms existing approaches in terms of generated workloads. Although Phase 2 has a pseudopolynomial time complexity, our experimental study shows that it runs much faster than other solutions with comparable quality.

Recently, significant progress has been made in the development of timed process algebras for the specification and analysis of real-time systems. This paper describes a timed process algebra called ACSR, which supports synchronous timed actions and asynchronous instantaneous events. Timed actions are used to represent the usage of resources and to model the passage of time. Events are used to capture synchronization between processes. To be able to specify real systems accurately, ACSR supports a notion of priority that can be used to arbitrate among timed actions competing for the use of resources and among events that are ready for synchronization. The paper also includes a brief overview of other timed process algebras and discusses similarities and differences between them and ACSR.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

The conventional model of real-time system cannot solve a problem when tasks come earlier than their earliest response time. Fazmah Arif Yulianto solved this problem by purposing a different model which has liveline as new time constraint. This new algorithm is called Earliest Deadline Earliest Liveline First-Fazmah (EDELF-F) which is developed based on EDF-DM algorithm. Then to determine the ability of the algorithm, the comparison between EDELF-F with conventional algorithms EDF (Earliest Deadline First) was performed with 3 scenarios: period > deadline, period = deadline and period < deadline for 10 tasks. After simulated, EDELF-F algorithm has a weakness in order to satisfy task's period. Author has modified EDELF algorithm (called EDELF-S) which is developed based on EDF-C algorithm to overcome weakness of EDELF-F algorithm. This EDELF-S has better response time and feasibility and also can solve the problem related to earliest response time. Both EDELF-F and EDELF-S can solve every case which can be solved by EDF but not vice versa. Both EDELF-F and EDELF-S also has a better feasibility than EDF.