Patricia Balbastre

IRIS: a new reclaiming algorithm for server-based real-time systems

In this paper we present a new algorithm for CPU resource reservation in real-time systems that allows the coexistence of hard, soft and non real-time tasks. The proposed algorithm is specifically designed to handle computational overload. A task that needs more CPU-time than reserved can reuse the spare bandwidth, without interfering with the others tasks. With respect to other reclamation schemes, the novelty of the proposed algorithm is that the spare bandwidth is fairly distributed among the needing servers. The effectiveness of the algorithm is demonstrated with an extensive set of experiments. We also propose a methodology to set scheduling parameters depending on the type of the task and on the time constraints needed.

RT control scheduling to reduce control performance degrading

In the framework of real-time digital control, two fundamental parameters are defined, the control effort and the control action interval. The first one is related to the strength of the control that, due to the intersampling open-loop control, determines the degrading of performances under unexpected delays. The second one refers to the unavoidable delays in the multitasking environment due to interactions among the tasks. As a consequence, the scheduling policy should consider not only the tasks delays but also their influence in the control loop behavior, being calculated to minimize the overall degrading of performances.

Optimal deadline assignment for periodic real-time tasks in dynamic priority systems

Real-time systems are often designed using a set of periodic tasks. Task periods are usually set by the system requirements, but deadlines and computation times can be modified in order to improve system performance. Sensitivity analysis in real-time systems has focused on changes in task computation times using fixed priority analysis. Only a few studies deal with the modification of deadlines in dynamic priority scheduling. The aim of this work is to provide a sensitivity analysis for task deadlines in the context of dynamic-priority, pre-emptive, uniprocessor scheduling. In this paper, we present a deadline minimisation method that achieves the maximum reduction. As undertaken in other studies concerning computation times, we also define and calculate the critical scaling factor for task deadlines. Our proposal is evaluated and compared with other works in terms of jitter. The deadline minimisation can be used to strongly reduce jitter of control tasks, in a real-time control application

A Task Model to Reduce Control Delays

Industrial control applications are usually developed in two phases: control design and real-time system implementation. In the control design stage a regulator is obtained and later it is translated into an algorithm in the implementation phase. Traditionally, these two phases have been developed in separate ways. Recently, some works have pointed out the necessity of the integration of the control design and its implementation. One of these works reduce the delay variance of control tasks (defined as the control action interval (CAI) and data acquisition interval (DAI) parameters) splitting every task into three parts. The CAI reduction method highly reduces the delay variance and improves the control performance. This work shows how to evaluate these delays under static and dynamic scheduling policies. A new task model is proposed in order to reduce the CAI and DAI parameters, which implies an improvement in the control performance. The new task model will be implemented in a real process, and the experimental measurements will show how, effectively, the control performance is highly improved with the methods presented in this paper.

Control loop timing analysis using truetime and jitterbug

A modern control system is typically implemented as a multitasking software application executing in a real-time operating system. If the computer load is high, the controller will experience delays and jitter, which in turn degrade the control performance. Arguing for an integrated design approach, the paper describes two computer tools for implementation-aware control analysis: TrueTime and Jitterbug. An example is given where the tools are used together to evaluate the performance of various control task implementations

Minimum Deadline Calculation for Periodic Real-Time Tasks in Dynamic Priority Systems

Real-time systems are often designed using a set of periodic tasks. Task periods are usually set by the system requirements, but deadlines and computation times can be modified in order to improve system performance. Sensitivity analysis in real-time systems has focused on changes in task computation times using fixed priority analysis. Only a few studies deal with the modification of deadlines in dynamic-priority scheduling. The aim of this work is to provide a sensitivity analysis for task deadlines in the context of dynamic-priority, preemptive, uniprocessor scheduling. In this paper, we present a deadline minimization method that computes the shortest deadline of a periodic task. As undertaken in other studies concerning computation times, we also define and calculate the critical scaling factor for task deadlines. Our proposal is evaluated and compared with other works. The deadline minimization proposed strongly reduces jitter and the response time of control tasks, which can lead to a significant improvement in system performance.

A constant-time dynamic storage allocator for real-time systems

Dynamic memory allocation has been used for decades. However, it has seldom been used in real-time systems since the worst case of spatial and temporal requirements for allocation and deallocation operations is either unbounded or bounded but with a very large bound.In this paper, a new allocator called TLSF (Two Level Segregated Fit) is presented. TLSF is designed and implemented to accommodate real-time constraints. The proposed allocator exhibits time-bounded behaviour, O(1), and maintains a very good execution time. This paper describes in detail the data structures and functions provided by TLSF. We also compare TLSF with a representative set of allocators regarding their temporal cost and fragmentation.Although the paper is mainly focused on timing analysis, a brief study and comparative analysis of fragmentation incurred by the allocators has been also included in order to provide a global view of the behaviour of the allocators.The temporal and spatial results showed that TLSF is also a fast allocator and produces a fragmentation close to that caused by the best existing allocators.

Schedulability analysis of window-constrained execution time tasks for real-time control

Feasibility tests for hard real-time systems provide information about the schedulability of a set of tasks. However, this information is a yes or no answer whether the task set achieves the test or not. From the system design point of view, it would be useful to have more information, for example, how much can one vary some task parameters, such as computation time, without jeopardizing the system feasibility. The aim of the work is to provide a method to determine how much a task can increase its computation time, maintaining the system feasibility under a dynamic priority scheduling. This extra time can be determined not only in all the task activations, but in n of a window of m task invocations. This is what we call a window-constrained execution time system. In control applications, this information can be used to execute supervision activities, such as model updating which is not required to be executed in all the periods, or to determine new controller parameters for the current operating conditions. In fault tolerance, this information allows us to recover n faults in m activations.

Control tasks delay reduction under static and dynamic scheduling policies

Industrial application of digital control requires the synergy between well designed control algorithms and carefully implemented control systems. The control performances can be strongly influenced depending on the data acquisition and control action delays. The paper shows how to evaluate these delays (jitter) under static or dynamic scheduling policies. An evaluation of several sets of tasks executed under both scheduling policies is analysed and compared. The results allow us to determine the goodness of both algorithms with respect to the delays due to scheduling. While worst case response time in static scheduling can be easily determined, under EDF scheduling the result is not trivial. A method to determine the worst case response time under EDF scheduling is proposed. The measurement of these delays can be drastically reduced with a task decomposition. This decomposition is studied and evaluated from the delays point of view. The reduction of the data acquisition interval (DAI) and control action interval (CAI) under both scheduling policies can be considered in the control design phase in order to properly adjust the control algorithm.

Jitter Evaluation of Real-Time Control Systems

The real-time implementation of a controller typically introduces artefacts like delay and jitters that have not been considered at the design stage. As a consequence, the system behaves in a non-periodic manner, and the real performance is degraded with respect to the expected response. This paper proposes a hybrid task model to reduce the impact of the scheduling on the control performance. For a large batch of typical plants, we analyze how sensitive the control system is to jitter when the sampling rate is slow or fast compared to the bandwidth of the system