Finding Response Times in a Real-Time System

Joseph, Mathai

doi:10.1093/comjnl/29.5.390

Cited by 896 publications

(507 citation statements)

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“…The proof is identical to the one given in [10] which states that the worst Case Response Time of any task should be less than or equal to its deadline. An example of GEDF or UEDF algorithm Assuming that there are three tasks which reach at time 0, namely the task τ 1 , τ 2 , τ 3 .…”

Section: Cs Jmentioning

confidence: 77%

An efficient mixed scheduling algorithm for the hybrid task set on heterogeneous multiprocessor

Wang¹,

Cheng²,

Zeng³

2014

Proceedings of the 3rd International Conference on Computer Science and Service System

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Abstract-In this paper we study the schedulability conditions of multiple types of real-time tasks (periodic real-time tasks, sporadic real-time tasks and aperiodic soft real-time tasks) in a heterogeneous multiprocessing environment. With the practical application of complicated environment, we propose a mixed scheduling algorithm in this paper, which itegrates UEDF algorithm with Task-Centric with Slack Defragmentation algorithm in the heterogeneous multiprocessor. Due to its characteristics that making the most of the processor which is already in use at first in the process of scheduling in order to reserve more free resources for future tasks, this algorithm can effectively improve the success rate of the entire hybrid task set scheduling. The results in simulation experiments show that the performance of the proposed algorithm scheduling on both the monotonic performance ordering and the non-monotonic performance ordering resource have obvious advantages over that of the current other combination algorithms.

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Section: Cs Jmentioning

confidence: 77%

An efficient mixed scheduling algorithm for the hybrid task set on heterogeneous multiprocessor

Wang¹,

Cheng²,

Zeng³

2014

Proceedings of the 3rd International Conference on Computer Science and Service System

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“…The traditional response time calculation (Audsley et al 1993;Joseph and Pandya 1986) for fixed-priority pre-emptive scheduling on a uniprocessor is based on an upper bound on the WCET of each task τ i , denoted by C i . By contrast, our MRTA framework dissects the individual components (processor and memory demands) that contribute to the WCET bound and re-assembles them at the level of the worst-case response time.…”

Section: Response Time Analysismentioning

confidence: 99%

An extensible framework for multicore response time analysis

et al. 2017

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In this paper, we introduce a multicore response time analysis (MRTA) framework, which decouples response time analysis from a reliance on contextindependent WCET values. Instead, the analysis formulates response times directly The additional material includes: Section 4: analysis for warmed-up caches and dynamic scratchpads (Sects. 4.3 and 4.2). Section 7: extensions to the task model, including RTOS and interrupts, shared software resources, and open systems and incremental verification. Section 8: presentation of a cycle-accurate multicore simulator. Section 9: evaluation of different local memory types (Sect. 9.2), a comparison between predictable and reference architectures (Sect. 9.3), and a verification of the precision of the analysis using results from the simulator (Sect. 9.4). 123Real-Time Syst from the demands placed on different hardware resources. The MRTA framework is extensible to different multicore architectures, with a variety of arbitration policies for the common interconnects, and different types and arrangements of local memory. We instantiate the framework for single level local data and instruction memories (cache or scratchpads), for a variety of memory bus arbitration policies, including: Round-Robin, FIFO, Fixed-Priority, Processor-Priority, and TDMA, and account for DRAM refreshes. The MRTA framework provides a general approach to timing verification for multicore systems that is parametric in the hardware configuration and so can be used at the architectural design stage to compare the guaranteed levels of real-time performance that can be obtained with different hardware configurations. We use the framework in this way to evaluate the performance of multicore systems with a variety of different architectural components and policies. These results are then used to compose a predictable architecture, which is compared against a reference architecture designed for good average-case behaviour. This comparison shows that the predictable architecture has substantially better guaranteed real-time performance, with the precision of the analysis verified using cycle-accurate simulation.

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“…Yet, it is necessary to evaluate if a certain partitioning leads to a valid solution. We know from [20], that the worst-case response time r i,j,k of an independent thread θ i,j,k scheduled with a preemptive fixed-priority scheduling algorithm, is given by (6):…”

Section: Fully-partitioned Distributed Multi-core Systemsmentioning

confidence: 99%

Allocation of Parallel Real-Time Tasks in Distributed Multi-core Architectures Supported by an FTT-SE Network

Garibay-Martínez¹,

Nelissen²,

Ferreira³

et al. 2015

Lecture Notes in Computer Science

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Distributed real-time systems such as automotive applications are becoming larger and more complex, thus, requiring the use of more powerful hardware and software architectures. Furthermore, those distributed applications commonly have stringent real-time constraints. This implies that such applications would gain in flexibility if they were parallelized and distributed over the system. In this paper, we consider the problem of allocating fixed-priority fork-join Parallel/Distributed real-time tasks onto distributed multi-core nodes connected through a Flexible Time Triggered Switched Ethernet network. We analyze the system requirements and present a set of formulations based on a constraint programming approach. Constraint programming allows us to express the relations between variables in the form of constraints. Our approach is guaranteed to find a feasible solution, if one exists, in contrast to other approaches based on heuristics. Furthermore, approaches based on constraint programming have shown to obtain solutions for these type of formulations in reasonable time. This implies that such applications would gain in flexibility if they were parallelized and distributed over the system. In this paper, we consider the problem of allocating fixed-priority fork-join Parallel/Distributed realtime tasks onto distributed multi-core nodes connected through a Flexible Time Triggered Switched Ethernet network. We analyze the system requirements and present a set of formulations based on a constraint programming approach. Constraint programming allows us to express the relations between variables in the form of constraints. Our approach is guaranteed to find a feasible solution, if one exists, in contrast to other approaches based on heuristics. Furthermore, approaches based on constraint programming have shown to obtain solutions for these type of formulations in reasonable time.

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Finding Response Times in a Real-Time System

Cited by 896 publications

References 0 publications

An efficient mixed scheduling algorithm for the hybrid task set on heterogeneous multiprocessor

An efficient mixed scheduling algorithm for the hybrid task set on heterogeneous multiprocessor

An extensible framework for multicore response time analysis

Allocation of Parallel Real-Time Tasks in Distributed Multi-core Architectures Supported by an FTT-SE Network

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