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COTS-based multicores are now the preferred choice for hosting embedded applications owing to their immense computational capabilities, small form factor and low power consumption. Many of these embedded applications have real-time requirements and real-time system designers must be able assess them for their predictability and provide guarantees (at design(More)
Modern multicore processors for the embedded market are often heterogeneous in nature. One feature often available are multiple sleep states with varying transition cost for entering and leaving said sleep states. This research effort explores the energy efficient task-mapping on such a heterogeneous multicore platform to reduce overall energy consumption(More)
Real-time systems demand guaranteed and predictable run-time behaviour in order to ensure that no task has missed its deadline. Over the years we are witnessing an ever increasing demand for functionality enhancements in the embedded real-time systems. Along with the functionalities, the design itself grows more complex. Posed constraints, such as energy(More)
A large part of power dissipation in a system is generated by I/O devices. Increasingly these devices provide power saving mechanisms, inter alia to enhance battery life. While I/O device scheduling has been studied in the past for real-time systems, the use of energy resources by these scheduling algorithms may be improved. These approaches are crafted(More)
Heterogeneous multicore platforms are becoming an interesting alternative for embedded computing systems with limited power supply as they can execute specific tasks in an efficient manner. Nonetheless, one of the main challenges of such platforms consists of optimising the energy consumption in the presence of temporal constraints. This paper addresses the(More)
Energy consumption is a major concern in modern real-time embedded systems and leakage current is a main contributor to it. To deal with the leakage current, several procrastination approaches have been proposed in the past in order to reduce the energy consumption. These approaches approximate the procrastination interval for the ease of analysis and(More)