Complexity of scheduling tasks with processing time dependent profit

We have proposed the forward Discrete Wavelet Transform architecture for real time processing of SM signals to extract target vibration or motion with high

Based on the traditional task network, we proposed the concept of an extended task network and partial network, and a practical dynamic scheduling algorithm for time-

In particular, in the case of the minimum vertex cover problem, given full information, no polynomial time algorithm is known to achieve a better asymptotic performance ratio than 2:

We determine a feasible schedule for problem ¯ P|prec; c ij = 1; p i = 1|C max using the polynomial-time (4/3)-approximation algorithm (see [19]). From this solution, we derive

They are depicted in figures presented afterwards, such that the first row shows preemption and scheduler costs in black along with the idle task in grey, while the following rows

It is worth noting that the algorithm we propose in Section IV enables to solve this problem in O(n log n) time if all release dates are equal to zero. On the other hand,

) dynamic SCH[5] ≤ M-1 O(N+MlogM) dynamic Lem.[7] ≤ 2M-2 O(1) dynamic IZL ≤ M-1 O(1) dynamic Table 1: Optimal scheduling comparative (tasks with same release time and deadline

This algorithm enhances the schedulability of par- allel tasks of fork-join structure, by increasing the parallel segments deadline and getting rid of their strict execution time,