Simulating Execution Time and Power Consumption of Real-Time Tasks on Embedded Platforms

In this paper, we present PARTSim, an open-source power/thermal-aware simulator for embedded real-time systems. This tool is a fork of the well-known RTSim simulator, which can simulate the timing behavior of a set of real-time tasks with various characteristics when running on a multi-processor platform in presence of a number of real-time scheduling policies. PARTSim extends the functionality of RTSim by introducing support for power-aware embedded platforms exhibiting frequency scaling and specific architectural patterns like the ARM big.LITTLE and DynamIQ ones. Experimental results that compare simulated data against execution profiles collected on real platforms show a simulation error under 10 % for both execution time and power consumption at 90th percentile when simulating the effects of DVFS

An adaptive, utilization-based approach to schedule real-time tasks for ARM big. LITTLE architectures

ARM big.LITTLE architectures are spreading more and more in the mobile world thanks to their power-saving capabilities due to the use of two ISA-compatible islands, one focusing on energy efficiency and the other one on computational power. This architecture makes the problem of energy-aware task scheduling particularly challenging, due to the number of variables to take into account and the need for having lightweight mechanisms that can be readily computed in an operating system kernel scheduler. This paper presents a novel task scheduler for big.LITTLE platforms, combining the well-known Constant Bandwidth Server algorithm with a power-aware per-job migration policy. This achieves real-time adaptation of the CPU islands' frequencies based on the individual cores' overall utilization, as available in the scheduler thanks to the use of the resource reservation paradigm. Preliminary results obtained by simulations based on modifications to the open-source RTSim tool show that the proposed technique is able to achieve interesting performance/energy trade-offs

Dynamic Partitioned Scheduling of Real-Time Tasks on ARM big.LITTLE Architectures

This paper presents Big-LITTLE Constant Bandwidth Server (BL-CBS), adynamic partitioning approach to schedule real-time task sets in an energy-efficient way on multi-core platforms based on the ARM big.LITTLE archi-tecture. BL-CBS is designed as an on-line and adaptive scheduler, based ona push/pull architecture that is suitable to be incorporated in the currentSCHED_DEADLINE code base in the Linux kernel. It employs a greedyheuristic to dynamically partition the real-time tasks among the big andLITTLE cores aiming to minimize the energy consumption and the migra-tions imposed on the running tasks. The new approach is validated throughthe open-source RT-Sim simulator, which has been extended integrating anenergy model of the ODROID-XU3 board, fitting tightly the power consump-tion profiles for the big and LITTLE cores of the board. An extensive setof simulations have been run with randomly generated real-time task sets,leading to promising results