In real-time embedded systems, minimizing energy consumption is one of the most important tasks. Intra-task dynamic voltage and frequency scaling (DVFS) has been the subject of much research in the task boundary of time-constrained applications for energy reduction. The problem of optimizing energy consumption with respect to intra-task DVFS scheduling can be addressed by assigning proper operational frequencies to individual basic blocks in a program while guaranteeing the deadline. Based on the profile information of a task, we first formulate the problem in terms of integer linear programming (ILP) regarding different assumptions of transition overhead. To verify the effectiveness of ILP formulations, the most representative intra-task DVFS techniques are taken for comparisons. The results of the experiments demonstrate that the proposed ILP method achieves greater energy savings than the existing approaches. Moreover, it determines the optimal scheduling strategy in reasonable execution time for applications with a limited number of blocks. INDEX TERMS Intra-task DVFS technique, time constrained applications, minimize energy consumption, ILP formulations.
Embedded systems for critical applications are often based on resource-constrained devices to meet the requirements like performance predictability and energy consumption. To deal with the increased software complexity, many of these systems have adopted reliable RTOSes (Real-Time Operating Systems) with advanced protection functionalities. Meanwhile, the concept of IoT (Internet of Things) is gaining momentum. Many IoT OSes, specialized to provide the large software stack required by IoT applications, have been released. Nevertheless, neither reliable RTOS nor IoT OS can satisfy all the requirements of IoT-enabled reliable systems. Dual-OS configuration (i.e. the coexistence of reliable RTOS and IoT OS) is a promising approach to achieve high reliability and productivity simultaneously. Existing dual-OS solutions, however, depend on additional hardware features (e.g. virtualization extensions, ARM TrustZone), which are unavailable in most resource-constrained devices. This paper presents iSotEE (iSolated Execution Environment), a middleware allowing IoT OS to run inside an isolated environment on top of a reliable RTOS without special hardware. Open-source implementations of iSotEE for Renesas RX (with TOPPERS/HRP3 as reliable RTOS, Amazon FreeRTOS as IoT OS) and ARMv7-M (with two configurations of Zephyr as reliable RTOS and IoT OS) architectures are provided and evaluated. The results show that iSotEE can create reliable systems with a small footprint for resource-constrained devices, high real-time performance for critical applications, and high productivity and throughput for IoT applications.INDEX TERMS Embedded software, Internet of Things, real-time systems, reliability.
Current embedded systems are usually based on real-time operating system (RTOS). In the near future, embedded systems will include parallel applications for tasks like autonomous driving, and adopt many-core processors to satisfy the performance requirements. However, traditional RTOSes are not designed for high performance applications and whether they can scale well on many-core processors remains unclear. Meanwhile, research has shown that Linux can provide good scalability for processors with tens of cores. In this paper, an experiment environment based on a traditional multi-core RTOS (TOPPERS/FMP) and an off-the-shelf 72-core many-core processor (TILE-Gx72) is presented. By a comparative analysis of RTOS based and Linux based runtime systems, several bottlenecks in RTOS are identified and the methods to avoid them are proposed. After that, the PARSEC benchmark suite is used to evaluate the performance of RTOS and Linux. The results show that the optimized RTOS runtime system tends to deliver better scalability than Linux in many cases. Therefore, we believe that traditional RTOS like TOPPERS/FMP can still be a good choice for embedded many-core processors in the near future.
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