A Comparison of Compositional Schedulability Analysis Techniques for Hierarchical Real-Time Systems

Schedulability analysis of hierarchical real-time embedded systems involves defining interfaces that represent the underlying system faithfully and then compositionally analyzing those interfaces. Whereas commonly used abstractions, such as periodic and sporadic tasks and their interfaces, are simple and well studied, results for more complex and expressive abstractions and interfaces based on task graphs and automata are limited. One contributory factor may be the hardness of compositional schedulability analysis with task graphs and automata. Recently, conditional task models, such as the recurring branching task model, have been introduced with the goal of reaching a middle ground in the tradeoff between expressivity and ease of analysis. Consequently, techniques for compositional analysis with conditional models have also been proposed, and each offer different advantages. In this work, we revisit those techniques, compare their advantages using an automotive case study, and identify limitations that would need to be addressed before adopting these techniques for use with real-world problems

Extensible Energy Planning Framework for Preemptive Tasks

Cyber-physical systems (CSPs) are demanding energy-efficient design not only of hardware (HW), but also of software (SW). Dynamic Voltage and and Frequency Scaling (DVFS) and Dynamic Power Manage (DPM) are most popular techniques to improve the energy efficiency. However, contemporary complicated HW and SW designs requires more elaborate and sophisticated energy management and efficiency evaluation techniques. This paper is concerned about energy supply planning for real-time scheduling systems (units) of which tasks need to meet deadlines. This paper presents a modelbased compositional energy planning technique that computes a minimal ratio of processor frequency that preserves schedulability of independent and preemptive tasks. The minimal ratio of processor frequency can be used to plan the energy supply of real-time components. Our model-based technique is extensible by refining our model with additional features so that energy management techniques and their energy efficiency can be evaluated by model checking techniques. We exploit the compositional framework for hierarchical scheduling systems and provide a new resource model for the frequency computation. As results, our use-case for avionics software components shows that our new method outperforms the classical real-time calculus (RTC) method, requiring 36.21% less frequency ratio on average for scheduling units under RM than the RTC method

Removing Abstraction Overhead in the Composition of Hierarchical Real-Time System

The hierarchical real-time scheduling framework is a widely accepted model to facilitate the design and analysis of the increasingly complex real-time systems. Interface abstraction and composition are the key issues in the hierarchical scheduling framework analysis. Schedulability is essential to guarantee that the timing requirements of all components are satisfied. In order for the design to be resource efficient, the composition must be bandwidth optimal. Associativity is desirable for open systems in which components may be added or deleted at run time. Previous techniques on compositional scheduling are either not resource efficient in some aspects, or cannot achieve optimality and associativity at the same time. In this paper, several important properties regarding the periodic resource model are identified. Based on those properties, we propose a novel interface abstraction and composition framework which achieves schedulability, optimality, and associativity. Our approach eliminates abstraction overhead in the composition

Compositional Feasibility Analysis for Conditional Real-Time Task Models

Conditional real-time task models, which are generalizations of periodic, sporadic, and multi-frame tasks, represent real world applications more accurately. These models can be classified based on a tradeoff in two dimensions – expressivity and hardness of schedulability analysis. In this work, we introduce a class of conditional task models and derive efficient schedulability analysis techniques for them. These models are more expressive than existing models for which efficient analysis techniques are known. In this work, we also lay the groundwork for schedulability analysis of hierarchical scheduling frameworks with conditional task models. We propose techniques that abstract timing requirements of conditional task models, and support compositional analysis using these abstractions

Optimizing the Resource Requirements of Hierarchical Scheduling Systems

Compositional reasoning on hierarchical scheduling systems is a well-founded formal method that can construct schedulable and optimal system configurations in a compositional way. However, a compositional framework formulates the resource requirement of a component, called an interface, by assuming that a resource is always supplied by the parent components in the most pessimistic way. For this reason, the component interface demands more resources than the amount of resources that are really sufficient to satisfy sub-components. We provide two new supply bound functions which provides tighter bounds on the resource requirements of individual components. The tighter bounds are calculated by using more information about the scheduling system. We evaluate our new tighter bounds by using a model-based schedulability framework for hierarchical scheduling systems realized as Uppaal models. The timed models are checked using model checking tools Uppaal and Uppaal SMC, and we compare our results with the state of the art tool CARTS

Process Algebraic Approach to the Schedulability Analysis and Workload Abstraction of Hierarchical Real-Time Systems

Real-time embedded systems have increased in complexity. As microprocessors become more powerful, the software complexity of real-time embedded systems has increased steadily. The requirements for increased functionality and adaptability make the development of real-time embedded software complex and error-prone. Component-based design has been widely accepted as a compositional approach to facilitate the design of complex systems. It provides a means for decomposing a complex system into simpler subsystems and composing the subsystems in a hierarchical manner. A system composed of real-time subsystems with hierarchy is called a hierarchical real-time system This paper describes a process algebraic approach to schedulability analysis of hierarchical real-time systems. To facilitate modeling and analyzing hierarchical real-time systems, we conservatively extend an existing process algebraic theory based on ACSR-VP (Algebra of Communicating Shared Resources with Value-Passing) for the schedulability of real-time systems. We explain a method to model a resource model in ACSR-VP which may be partitioned for a subsystem. We also introduce schedulability relation to define the schedulability of hierarchical real-time systems and show that satisfaction checking of the relation is reducible to deadlock checking in ACSR-VP and can be done automatically by the tool support of ERSA (Verification, Execution and Rewrite System for ACSR). With the schedulability relation, we present algorithms for abstracting real-time system workloads