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LiRa [457]
3 years ago
10

Suppose that a scheduling algorithm (at the level of short-term CPU scheduling) favors those processes that have used the least

processor time in the recent past. Why will this algorithm favor I/O-bound programs and yet not permanently starve CPU-bound programs?
Computers and Technology
1 answer:
alekssr [168]3 years ago
8 0

Answer:

Answer of the given question is :

I/O-bound

programs would not require much CPU usage, having short CPU bursts.

CPU-bound programs require large CPU bursts. CPU-bound processes do not

have to worry about starvation because I/O bound programs finish running

quickly allowing CPU-bound programs to use the CPU often.

Explanation:

I/O-bound

is a thread generally has a tight latency that needs a compare to computer bond thread on the windows workload.

When a mouse click then it response ASAP as compared to batch job which is running in the background.

If the outcome is slower, then the user switch the operating systems and server workload does not care about UI

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A flower is an example of _______________? (Select the best answer.)
Zigmanuir [339]

Answer:

flora

Explanation:

Flora is plant life; fauna refers to animals. Fauna derives from the name of a Roman goddess, but the handiest way to remember the difference between flora and fauna is that flora sounds like flowers, which are part of the plant world; fauna, however, sounds like "fawn," and fawns are part of the animal kingdom.

7 0
3 years ago
Read 2 more answers
I watched an ad but the im button done is no where in sight, has anyone else experienced this recently. it was fine a few days a
Maurinko [17]

Answer:

This is usually just a small glitch that happens sometimes when you are seeing an ad and wanting to skip. Simple fixes to this problem include refreshing the browser or closing the application that you are in. This also would happen to me but following this fix should help with the problem.

7 0
2 years ago
Write a Python program to convert temperatures to and from celsius, fahrenheit.
Rudiy27

Answer:

https://www.w3resource.com/python-exercises/python-conditional-exercise-2.php

3 0
3 years ago
You are working with a database table that contains data about music. The table includes columns for track_id, track_name (name
german

The statement that completes the query is: bytes / 1000 AS kilobytes

<h3>SQL (Structured Query Language)</h3>

This is the language that is used to retrieve, update, and store data in the database.

<h3>Columns</h3>

From the question, we have the following table columns

  • track_id
  • track_name (name of the music track)
  • composer
  • bytes (digital storage size of the music track

To retrieve data from the bytes column, we make use of:

SELECT bytes ......

From the question, we understand that this column should be divided by 1000, and the AS command should be used.

So, the query becomes

SELECT bytes / 1000 AS kilobytes .....

Hence, the statement that completes the query is: bytes / 1000 AS kilobytes

Read more about database at:

brainly.com/question/24223730

5 0
2 years ago
A testing lab wishes to test two experimental brans of outdoor pain long each wiil last befor fading . The testing lab makes six
Simora [160]

Answer:

The answer is "\bold{Brand \ A \ (35, 350, 18.7) \ \ Brand \ B \ (35, 50, 7.07)}"

Explanation:

Calculating the mean for brand A:

\to \bar{X_{A}}=\frac{10+60+50+30+40+20}{6}  =\frac{210}{6}=35

Calculating the Variance for brand A:

\sigma_{A}^{2}=\frac{\left ( 10-35 \right )^{2}+\left ( 60-35 \right )^{2}+\left ( 50-35 \right )^{2}+\left ( 30-35 \right )^{2}+\left ( 40-35 \right )^{2}+\left ( 20-35 \right )^{2}}{5} \\\\

     =\frac{\left ( -25 \right )^{2}+\left ( 25  \right )^{2}+\left ( 15\right )^{2}+\left ( -5 \right )^{2}+\left ( 5 \right )^{2}+\left ( 15 \right )^{2}}{5} \\\\ =\frac{625+ 625+225+25+25+225}{5} \\\\ =\frac{1750}{50}\\\\=350

Calculating the Standard deviation:

\sigma _{A}=\sqrt{\sigma _{A}^{2}}=18.7

Calculating the Mean for brand B:

\bar{X_{B}}=\frac{35+45+30+35+40+25}{6}=\frac{210}{6}=35

Calculating the Variance for brand B:

\sigma_{B} ^{2}=\frac{\left ( 35-35 \right )^{2}+\left ( 45-35 \right )^{2}+\left ( 30-35 \right )^{2}+\left ( 35-35 \right )^{2}+\left ( 40-35 \right )^{2}+\left ( 25-35 \right )^{2}}{5}

    =\frac{\left ( 0 \right )^{2}+\left ( 10 \right )^{2}+\left ( -5 \right )^{2}+\left (0 \right )^{2}+\left ( 5 \right )^{2}+\left ( -10 \right )^{2}}{5}\\\\=\frac{0+100+25+0+25+100}{5}\\\\=\frac{100+25+25+100}{5}\\\\=\frac{250}{5}\\\\=50

 Calculating the Standard deviation:  

\sigma _{B}=\sqrt{\sigma _{B}^{2}}=7.07

4 0
3 years ago
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