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Worse still, hardware resource status can be changed intentionally through malicious external interference.
At system level, our supports for hardware resource estimation and performance evaluation are applied.
Therefore, MARTE hardware resource modeling (HRM) package is utilized to classify different types of HW elements.
MARTE hardware resource modeling package offers several stereotypes for modeling embedded HW platform.
The complete hardware resource model is divided into logical and physical views.
It has low complexity, is suitable for hardware resource sharing, and provides approximate result.
The finite state machine (FSM) is applied for reducing the hardware resource usage.
Building all required points into circuits independently leads to a massive hardware resource requirement.
In this paper, we present a high level modeling approach for hardware resource reconfiguration mechanisms analysis.
As a result, we were able to achieve higher video resolutions at lower hardware resource cost.
Wireless smart grid scale is usually very large, while the node's energy supply and hardware resource are limited.
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