In this paper, we study thermal-constrained hard real-time systems, where real-time guarantees must be met without exceeding safe temperature levels within the processor. Dynamic speed scaling is one of the major techniques to manage power so as to maintain safe temperature levels. As example, we adopt a reactive speed control technique in our work. We design an extended busy-period analysis methodology to perform schedulability analysis for general task arrivals under reactive speed control with First-In-First-Out (FIFO), Static-Priority (SP), and Earliest-Deadline-First (EDF) scheduling. As a special case, we obtain a closed-form formula for the worstcase response time of jobs under the leaky-bucket task arrival model. Our data show how reactive speed control can decrease the worst-case response time of tasks in comparison with any constant-speed scheme.

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Abstract-With increasing power densities, raising operating temperatures in chips threaten system reliability. Thermal control therefore has emerged as an important issue in system design and management.For dynamic thermal control to be effective, predictive thermal models of the system are needed. Such models typically use power as input, which renders them difficult to use in practical systems, where power monitoring is not available at processor or chip level. In this paper, we describe a methodology to infer the thermal model based on the monitoring of existing temperature sensors and of instruction counter registers. This allows the thermal model to be easily established, calibrated, and recalibrated at runtime to account for different thermal behavior due to either variations in fabrication or to varying environmental parameters. We validate the proposed methodology through a series of experiments. We also propose and validate an extension of the model and associated methodology for multicore processors.

Abstract-In our research, we study how real-time systems are affected by thermal management to satisfy the temperature constraint. In temperature-constrained real-time systems, deadline guarantees must be met without exceeding safe temperature level of the processor. While processor speed control is the most popular method of thermal management of systems, it eventually makes the task delays longer. In our study, we describe how to find the worst case execution considering speed control in temperature-constrained environment. With the worst case execution scenario, we study how the simple reactive speed scaling scheme can improve the processor utilization compared with any constant-speed scheme. For aperiodic tasks, it is briefly reviewed how the naive application of slack stealing leads to missed deadlines and the design-time slack allocation is proposed. A queueing model is presented to analyze the response time provided to aperiodic jobs and validated with results from a discrete-event simulator.