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Table 7 Performance evaluation of system latencies.
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Table 4 lists the comparison of system latency.
However, these routing protocols have not focused on the importance of system latency.
Optimization of system latency is important, because it improves performance, reduces power consumption, and allows a more deterministic behavior that is needed for recurrent modes.
The evaluation results of system switch latencies and interrupt latencies are presented in Table 7.
In both cases (RR-basic and WRR-static), during the interval between 500 and 1000 s, the queue occupancy is overloaded, reaching its limit (set to 90 packets), leading to an increase of the system latency.
System latencies are the key metrics to evaluate the real-time performance of RTOSs.
This paper proposes a novel optimization method that utilizes a multi-population parallel genetic algorithm (GA) to simultaneously optimize the structure and system latency of evolvable block-based neural networks (BbNNs).
We make comparisons of the number of the feedback bits and a system latency in Sect.
However, the extended LF-OSDMA leads to the large increase in the number of feedback bits, and worsens system latency.
Therefore, a maximum system latency delay of one filter length, L, can still be maintained whilst offering significant PAPR reducing capabilities.
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