) In recent years, power efficiency has come to the forefront of research in embedded systems, and has been considered to have arguably equal or more importance when compared to performance. As there are few indications that commercial energy storage solutions will keep pace with innovation in silicon and computer architecture, this trend is likely to continue. Run-time management of multi- and many-core systems have been proposed in the literature to effectively apply dynamic voltage and frequency scaling (DVFS) and dynamic power management (DPM) to trade-off higher core utilisation for reduced power consumption, with little or no impact on performance as hard or soft deadlines remain adhered to. These approaches have tended to consider the execution of, in some cases, just a single application or, in other cases, a series of sequential (i.e. non-concurrent) applications. Application concurrency is known to have multiple associated challenges, and adding run-time power management through DVFS scaling further increases competition for limited and constrained resources, and reduces the time margin in a deadline based real-time system. If the computation tasks are known at design time, or are of a periodic nature, simple solutions can be identified to solve this challenge. However, embedded systems typically deal with aperiodic tasks (such as those involving user input and asynchronous network calls) which mean that decisions must be made at run-time in order to meet deadlines in a power-efficient manner. This research will investigate the interaction between run-time DVFS management and aperiodic task scheduling to determine what elements of run-time management can plausibly be implemented in a real-world multi-core heterogeneous system. Anticipated contributions will be an approach to managing the power consumption of a heterogeneous many-core system, at run-time, while it is running concurrent aperiodic applications. This approach(es) will be thorough evaluated through mathematical modelling and practical experimentation on development boards such as the Odroid-XU4 and the NVIDIA Jetson.