On-line scheduling in multiprocessor systems based on continuous control using Timed Continuous Petri Nets

Desirena-Lόpez, G.; Vázquez, C.R.; Briz, José Luis; Ramírez-Treviño, A.; Gómez‐Gutiérrez, David

doi:10.1109/wodes.2016.7497860

Cited by 4 publications

(10 citation statements)

References 11 publications

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“…We only provide global multiprocessor schedulers by the reasons explained in Section 2. The scheduling policies available in the framework are an G-EDF ( [1]), an RT fluid scheduler RT-TCPN ( [15]), and an RT-TCPNThermal aware scheduler that are describing below.…”

Section: Available Schedulersmentioning

confidence: 99%

“…RT-TCPN is a scheduler based on the TCPN model presented in [15]. It is composed of a global fluid scheduler and the discretization of the fluid scheduler.…”

Section: Rt-tcpnmentioning

confidence: 99%

“…The elements of SD can be arranged in ascendant order and renamed as SD = {sd 0 , ..., sd α }, where α is the last deadline. We define the the quantum Q as in [15].…”

Section: Rt-tcpnmentioning

confidence: 99%

“…Although it is possible to find practical solutions for specific cases, considering thermal restrictions, optimizing energy or dealing with resource sharing are still open questions ( [6]). We have been exploring the design of Thermal-Aware RT Schedulers in recent contributions, leveraging control techniques and combining fluid and combinatorial schedulers, taking the most of both approaches ( [15]).…”

Section: Introductionmentioning

confidence: 99%

“…We have included three schedulers: a global EDF scheduler from [1], and other two from our own authorship a RT fluid scheduler ( [15]) and a thermal aware RT scheduler ( [16]), however the user can define his own scheduler. Sec.…”

Section: Introductionmentioning

confidence: 99%

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A Flexible Framework for Real-Time Thermal-Aware Schedulers using Timed Continuous Petri Nets

López

Anguiano

Treviño

et al. 2019

CyS

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This work presents TCPN-ThermalSim, a software tool for testing Real-Time Thermal-Aware Schedulers 1 . This framework consists of four main modules. The first one helps the user to define the problem: task set with periods, deadlines and worst case execution times in CPU cycles, along with the CPU characteristics, temperature and energy consumption. The second module is the Kernel simulation, which builds up a global simulation model according to the configuration module. In the third module, the user selects the scheduler algorithm.Finally the last module allows the execution of the simulation and present the results. The framework encompasses two modes: manual and automatic. In manual mode the simulator uses the task set data provided in the first section. In automatic mode the task set is generated by parameterizing the integrated UUniFast algorithm.

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Section: Available Schedulersmentioning

confidence: 99%

“…RT-TCPN is a scheduler based on the TCPN model presented in [15]. It is composed of a global fluid scheduler and the discretization of the fluid scheduler.…”

Section: Rt-tcpnmentioning

confidence: 99%

“…The elements of SD can be arranged in ascendant order and renamed as SD = {sd 0 , ..., sd α }, where α is the last deadline. We define the the quantum Q as in [15].…”

Section: Rt-tcpnmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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