HARTIK 3.0: a portable system for developing real-time applications

Deadlocks are of paramount importance in resource allocation systems, which are usually treated from the perspective of discrete event systems. This paper develops a deadlock prevention strategy for a system modeled with Petri nets, by endowing appropriate time constraints with certain transitions to schedule the firing priority of enabled transitions in a Petri net such that transition sequences leading to deadlocks are prohibited, i.e., expanding an untimed Petri net model into a time Petri net to prevent deadlocks. To increase the system permissiveness of a time Petri net with time constraints endowed, a control place is designed, which does not expand the reachable space of the original Petri net. The predominant role of the control place is to convert continuously enabled transitions at certain markings into newly enabled transitions, which can prolong the firing time of transitions. Furthermore, we propose a method that merely enumerates deadlock prevention condition inequalities to derive a series of time constraints by probing the connection between deadlock prevention conditions and transitions. The developed method only needs to designate time constraints for partial transitions. Examples are provided to demonstrate the effectiveness of the presented methodology.

In hard real-time task systems where periodic and aperiodic tasks coexist, the object of task scheduling is to reduce the response time of the aperiodic tasks while meeting the deadline of periodic tasks. Total bandwidth server (TBS) and advanced TBS (ATBS) are used in dynamic priority systems. However, these methods are not optimal solutions because they use the worst-case execution time (WCET) or the estimation value of the actual execution time of the aperiodic tasks. This paper presents an online slack-stealing algorithm called SSML that can make significant response time reducing by modification of look-ahead earliest deadline first (laEDF) algorithm as the slack computation method. While the conventional slack-stealing method has a disadvantage that the slack amount of each frame must be calculated in advance, SSML calculates the slack when aperiodic tasks arrive. Our simulation results show that SSML outperforms the existing TBS based algorithms when the periodic task utilization is higher than 60%. Compared to ATBS with virtual release advancing (VRA), the proposed algorithm can reduce the response time up to about 75%. The performance advantage becomes much larger as the utilization increases. Moreover, it shows a small performance variation of response time for various task environments.

In a real-time system with both hard deadline periodic tasks and soft deadline aperiodic tasks, hard deadline tasks must be guaranteed to meet their deadlines and soft deadline tasks are serviced in a best-effort manner. To schedule soft deadline aperiodic tasks in dynamic priority systems, one can assign a virtual deadline like the TBS algorithm or use capacity servers like the DPE algorithm. Both approaches have their own advantages, and we cannot say which one is better in terms of response time. In some cases, TBS provides shorter response time than DPE server. In other cases, the reverse may happen. In this paper, we propose a combined approach to improve the response time of soft deadline aperiodic tasks. The proposed method combines the deadline assignment and the capacity server approach. When there is enough capacity available for aperiodic tasks, the aperiodic tasks are served by capacity servers. Otherwise, our method assigns a deadline and schedule aperiodic task together with periodic tasks by EDF algorithm. In the worst case, the proposed method provides response time no later than TBS. Experimental results show that the proposed approach improves the responsiveness of soft deadline aperiodic tasks.

Generally speaking, real-time system is considered to be able to influence the environment by receiving and processing data, and returning calculation results rapid enough, so as to control the environment. In computer science, real-time system describes the software and hardware system affected by time constraints, and its correctness relies on the logical correctness of the function and the time when the result is generated. According to the main characteristics of real-time operating system, such as time constraint, predictability and reliability, it puts forward higher requirements for the time accuracy and reliability of real-time operating system. This paper first introduces the real-time system from its main characteristics, related concepts and scheduling algorithm. Then five classical graph based task models of real-time system are introduced. Finally, this paper introduces the directed graph realtime task model from two aspects of definition and semantics. As an extension of realtime system task model, directed graph real-time task model is considered to be able to provide real-time systems with stronger expressive power and support the formal study of time constraint problems.

This paper describes a real-time soil water content monitoring system from both perspectives of hardware and software. The system consists of an ATmega128 microcontroller with embedded μC/OS-II operating system, BD-I-type soil moisture sensors, RS-485 and RS-232 bus-based data transmission technologies. Compared to traditional microcontroller monitoring systems, the reliability and processing ability of the system are improved greatly by adding the μC/OS-II operating system, which brings real-time multi-task processing capabilities. The system has significances in improving water utility efficiency and precise irrigation control in urban greening as well as agricultural and forestry production.

While scheduling theory has been developed over a long period of time, it is important to note that most results concern problems with static characteristics. However, a real-time system is dynamic and requires on-line and adaptive scheduling strategies. So, an important aspect of real-time systems research is to devise methods flexible enough to react to a dynamic change of processor load and to attempt to schedule all the tasks judiciously. In this paper, we are particularly concerned with the problem of scheduling tasks which are of two kinds: periodic and sporadic, on a monoprocessor machine. Periodic tasks are independent, run cyclically and their characteristics are known in advance. In addition, we allow for the unpredictable occurrence of aperiodic task groups, with timing and precedence constraints. Clearly, the main problem is to devise a schedulability test that makes it possible to decide whether a new occurring group can be accepted, without upsetting the tight timing behavior requirements. We present an optimal acceptance test which returns a decision on the basis of the current state of processor load and by considering tasks to be scheduled according to the well known preemptive algorithm Earliest Deadline. The acceptance algorithm and a complexity analysis are presented.

There are many challenges which face designers of complex system architectures, particularly safety–critical or real-time systems. The introduction of Architecture Description Languages (ADLs) has helped to meet these challenges by consolidating information about a system and providing a platform for modelling and analysis capabilities. However, managing this wealth of information can still be problematic, and evaluation of potential design decisions is still often performed manually. Automatic architectural optimisation can be used to assist this decision process, enabling designers to rapidly explore many different options and evaluate them according to specific criteria. In this paper, we present a multi-objective optimisation approach based on EAST-ADL, an ADL in the automotive domain, with the goal of combining the advantages of ADLs and architectural optimisation. The approach is designed to be extensible and leverages the capabilities of EAST-ADL to provide support for evaluation according to different factors, including dependability, timing/performance, and cost. The technique is applied to an illustrative example system featuring both hardware and software perspectives, demonstrating the potential benefits of this concept to the design of embedded system architectures.

In this paper we discuss some design issues related to the handling of timing constraints in embedded systems and present a tool for the analysis of timing constraints at the architectural design level. Most design tools for real-time applications do not perform any kind of real-time analysis and do not allow the definition of explicit timing constraints. Our tool is aimed at real-time schedulability and performance analysis. It guides the decomposition of the application architecture into a set of hierarchical abstractions representing the active components and the cooperation among them (messages and/or use of shared resources). Deadlines can be specified between any couple of events. The real-time schedulability analysis requires a sufficiently accurate description of the (hardware) architecture, the mapping of the software components on the application nodes and the choice of the resource management algorithms.

Over 90 percent of all microprocessors are now used for real-time and embedded applications, and the behavior of many of these applications is constrained by the physical world. Higher-level programming languages and middleware are needed to robustly and productively design, implement, compose, integrate, validate, and enforce real-time constraints along with conventional functional requirements and reusable components. Designing real-time and embedded systems that implement their required capabilities, are dependable and predictable, and are parsimonious in their use of limited computing resources is hard; building them on time and within budget is even harder. Moreover, due to global competition for market share and engineering talent, companies are now also faced with the problem of developing and delivering new products in short time frames. Therefore it is essential that the production of real-time embedded systems can take advantage of languages, tools, and methods that enable higher software productivity. Ideally, developers should use a programming language that shields them from many accidental complexities, such as type errors, memory management, and steep learning curves. The Java programming language has become an attractive choice because of its safety, productivity,its relatively low maintenance costs, and the availability of well trained developers. Although it has good software engineering characteristics, Java is unsuitable for developing real-time embedded systems, mainly due to under-specification of thread scheduling and the presence of garbage collection. Recently, to address these problems, a number of extensions to Java have been proposed by the Java Community Process Expert Group for the Real-Time Specification for Java (RTSJ) among others. The intent of these specifications is the development of real-time applications by providing several additions such as extending the Java memory model, providing stronger semantics in thread scheduling, and so on. Interest in real-time Java in both the research community and industry, because of its challenges and its potential impact on the development of embedded and real-time applications, has recently increased, significantly. This interest in the industry comes not only from traditional applications, such as industrial control, but also for business and financial applications. The goal of the proposed workshop is to gather researchers working on real-time and embedded Java to identify the challenging problems that still need to be properly resolved in order to assure the success of the of real-time Java as a technology, and to report results and experience gained by researchers.

We introduce a new set of dynamic scheduling algorithms for scheduling and guaranteeing the deadline compliance of a set of aperiodic real-time tasks on a uniprocessor architecture. The task model selected is that of non-preemptable tasks with arbitrary start times and deadlines. The proposed algorithms address a fundamental trade-off in dynamic scheduling between the cost of scheduling and the quality of the resulting schedules. The algorithms control the time allocated to scheduling explicitly, in order to obtain good-quality schedules in reasonable times. We show that taking into account the scheduling time is crucial for honoring the deadlines of scheduled real-time tasks. We provide an experimental evaluation of our algorithms via performance comparisons with existing landmark algorithms that were originally designed to address some similar issues. The results of our experiments show that our algorithms outperform the existing techniques in several parameter configurations.

A real-time system is considered in which a set of periodic tasks are scheduled on an earliest-deadline-first basis and exclusively access critical sections through a dynamic priority ceiling protocol. An optimal online acceptance test is described for hard deadline aperiodic tasks. Aperiodic tasks are accepted only if all deadlines can be met. Here, optimality means that the algorithm is able to answer ‘yes’ to the question of the acceptance of a newly occurring task each time it is possible. The time complexity of the test is O(⌈R/p⌉.n+m) where n is the number of periodic tasks, R is the longest deadline, p is the shortest period and m is the number of aperiodic tasks that have previously been accepted but not completed.

Nowadays, wireless sensor networks (WSNs) are more and more used in applications such as environment monitoring, healthcare monitoring, etc...The challenge in sensor networks is to ensure the sustainability of the system by guaranteeing the required performance level. However, with the limited capacity of finite power sources and the need of guaranteeing a long lifetime of those systems, it is suitable to use energy harvesting which allows to supply low-power electronic systems by converting ambient energy into electric power. Hence, our study is concerned with the problem of soft periodic and aperiodic tasks scheduling in sensor nodes powered by energy harvesters. In this paper, we address this issue by proposing three energy-aware schedulers, namely BG-Green-RTO, BG-Green-BWP and Green-AWP which aim to improve the responsiveness of aperiodic tasks while still guaranteeing the execution of periodic tasks considering their timing and energy constraints. Such algorithms allow to gracefully cope with processing overload and energy starvation. Moreover, a simulation study permits to show their performance.

This paper presents a new type of scheduling algorithm for servicing soft deadline aperiodic tasks in adaptable fixed-priority real-time systems. The major goals of our proposed task scheduling are not only to guarantee all the deadlines of periodic tasks and to obtain fast response time for aperiodic tasks, but also to retain considerable scheduling predictability. To achieve these goals, we have adopted a new aperiodic task scheduling principle in which a normal fixed-priority assignment strategy and the information on a preassignment table built off-line are properly mingled somewhat dynamically according to the aperiodic tasks' arrivals at runtime. The paper also shows some simulation results in terms of the average aperiodic response time, verifying that the new algorithm offers significant performance improvements over other conventional joint scheduling algorithms, especially under a heavy transient overload.

An increasing number of DRTS (Distributed Real-Time Systems) are employing an end-to-end aperiodic task model. The key challenges of such DRTS are guaranteeing utilization on multiple processors to achieve overload protection, and meeting the end-to-end deadlines of aperiodic tasks. This paper proposes an end-to-end utilization control architecture and an IC-EAT (Integration Control for End-to-End Aperiodic Tasks) algorithm, which features a distributed feedback loop that dynamically enforces the desired utilization bound on multiple processors. IC-EAT integrates admission control with feedback control, which is able to dynamically determine the QoS (Quality of Service) of incoming tasks and guarantee the end-to-end deadlines of admitted tasks. Then an LQOCM (Linear Quadratic Optimal Control Model) is presented. Finally, experiments demonstrate that, for the end-to-end DRTS whose control matrix G falls into the stable region, the IC-EAT is convergeut and stable. Moreover, it is capable of providing better QoS guarantees for end-to-end aperiodic tasks and improving the system throughput.

A framework for the development of tolerant real-time applications