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The LEPT strategy is a stochastic scheduling strategy that processes jobs in decreasing order with respect to the expected processing time.
This paper proposes a heuristic approach that combines the modified analytic hierarchy process (MAHP), bandwidth aware divisible scheduling (BATS) + BAR optimization, longest expected processing time preemption (LEPT), and divide-and-conquer methods to perform task scheduling and resource allocation.
Longest expected processing time.
Our main results are that the expected processing time, O Nk2logw/α), depends on the following factors: Linear O(N) dependency on the size of data.
The expected processing time is derived accordingly multiplying (14) by αN: hat{t}left( {N,k} right) le log, w cdot frac{{k^{2} }}{{alpha^{2} }} cdot alpha N = {rm O}left( {frac{{ - { log }left( w right) cdot Nk^{2} }}{alpha }} right) (16).
Shortest Expected Processing Time (SEPT): The SEPT approach is similar to the LEPT strategy.
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This approach has a drawback in that different programs might have various expected processing times for requests of different types.
As expected, the processing time increases.
After all the above optimisation stages, we expect the processing time to go down to less than 200 ms and 28 ms on respectively the Cortex-M4 board and the Gumstix6 platform for an input resolution of (320×240).
As expected, sentence processing times were significantly faster in the compatible condition.
One would expect processing to rely on a tangible neural network involving several modules which interchange information and interact as time elapses.
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CEO of Professional Science Editing for Scientists @ prosciediting.com