Shin-Haeng Kang

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The next generation of embedded software has high performance requirements and is increasingly dynamic. Multiple applications are typically sharing the system, running in parallel in different combinations, starting and stopping their individual execution at different moments in time. The different combinations of applications are forming system execution(More)
—Due to the trend of many-core systems for dynamic multimedia applications, the problem size of mapping optimization gets bigger than ever making conventional meta-heuristics no longer effective. Thus, in this paper, we propose a problem decomposition approach for large scale optimization problems. We basically follow the divide-and-conquer concept, in(More)
— Finding a tight upper bound of the worst-case response time in a distributed real-time embedded system is a very challenging problem since we have to consider execution time variations of tasks, jitter of input arrivals, scheduling anomaly behavior in a multi-tasking system, all together. In this paper, we translate the problem as an optimization problem(More)
—This paper presents a novel mapping optimization technique for mixed critical multi-core systems with different reliability requirements. For this scope, we derived a quantitative reliability metric and presented a scheduling analysis that certifies given mixed-criticality constraints. Our framework is capable of investigating re-execution, passive(More)
As the number of processors in a chip increases and more functions are integrated, the system status will change dynamically due to various factors such as the workload variation, QoS requirement, and unexpected component failure. A typical method to deal with the dynamics of the system is to decide the mapping decision at runtime, based on the local(More)
This paper presents a static mapping optimization technique for fault-tolerant mixed-criticality MPSoCs. The uncertainties imposed by system hardening and mixed criticality algorithms, such as dynamic task dropping, make the worst-case response time analysis difficult for such systems. We tackle this challenge and propose a worst-case analysis framework(More)
It is challenging to schedule multiple dataflow applications concurrently on multi-processor embedded systems with processor sharing. As a viable solution, an approach has been proposed recently, in which the dataflow graphs are transformed into a set of independent realtime tasks. However, it may produce poor resource utilization and excessive buffer(More)
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