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This way, designers can choose the optimal deadline and period pairs that best fit application requirements.
In this paper, we try to identify the optimal deadline solving strategy considering both quantity of aborted tasks and their cost.
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Therefore, the optimal and dynamic deadline with the network coding is considered with the optimal policy in the harvest networks, i.e. the long-term throughput.
However, they examine different parameters as they aim at determining the optimal replication level and deadlines to use.
As a result, the optimal policy based on the deadline value is limited to maximize the throughput.
As a result, the analysis yields the identification of an optimal architecture, with respect to real-time deadlines, robustness and system costs.
This approach is based on the calculation of the so-called optimal processor speed which would allow all deadlines to be met.
First, we derive the optimal mechanism, neglecting the incentive constraint for the deadline.
The objective is to find a min-energy (optimal) schedule that finishes every job within its deadline.
A latest work offers an optimal algorithm that allows packets to have arbitrary deadlines but requires them to follow the order they arrive.
Using this fact, it can be proved by induction that energy consumption of a multi-epoch optimal schedule is a strictly decreasing function of transmission deadline.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com