Monte Carlo simulation

Write a Monte Carlo simulation to help determine which partitioning algorithm would be best give that the tasks have memory requirements that meet a poissan distribution with a mean of eight and a time distributionthat is uniform between one and ten, inclusively. The partitioning organizations are shown on Figures 7.2 and 7.3 (Slides 12 and 14).

The attached file provides a specifications within which you are required to work.

Chart the average turn-around time, average relative turn-around time, and average number of failures for each of the three partitioning styles (to be included in your report).

In your report, include a conclusion (decision) as to which of these partitioing style you would recommend for implementation to your management and why.

Upload your source code and report here.

Bonus points (20 points): Include one dynamic partitioning algorithm (Figure 7.4) by selecting one placement algoirthm (Best-fit, worst-fit, first-fit, or next-fit: Figure 7.5 plus in-class discussion) to this assignment. Including the bonus algorithm means that the conclusion is based on all four algorithms, not just the initial three. Consider the 56 M of memory in 1 M units. A process/task must fit into a contiguous hole to be eligible to execute. If no holes are large enough, then, if there is sufficient unused space, a compaction algoirthm should be implemented to allow that process/task to be placed into a partition. If a process requires more than 56 M to execute, then it blocks access to later items until all of memory is unused. At that time, it would take up all of memory for its time required. Subsequently, the other items behind it would be processed in the same manner as before.

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