Optimal Replacement Policy MCQ Quiz in हिन्दी - Objective Question with Answer for Optimal Replacement Policy - मुफ्त [PDF] डाउनलोड करें
Last updated on Apr 21, 2025
पाईये Optimal Replacement Policy उत्तर और विस्तृत समाधान के साथ MCQ प्रश्न। इन्हें मुफ्त में डाउनलोड करें Optimal Replacement Policy MCQ क्विज़ Pdf और अपनी आगामी परीक्षाओं जैसे बैंकिंग, SSC, रेलवे, UPSC, State PSC की तैयारी करें।
Latest Optimal Replacement Policy MCQ Objective Questions
Top Optimal Replacement Policy MCQ Objective Questions
Optimal Replacement Policy Question 1:
निम्न में से कौन-सा पेज रिप्लेसमेंट ऐल्गोरिद्म, पेज रेफरेन्स की आगे की (भविष्य की) जानकारी पर काम करता है?
Answer (Detailed Solution Below)
Option 4 : ऑप्टिमल
Optimal Replacement Policy Question 1 Detailed Solution
The correct answer is Optimal
Key Points
- Optimal Page Replacement Algorithm: ✅ The Optimal page replacement algorithm replaces the page that will not be used for the longest period of time in the future. This algorithm requires knowledge of future page references, which makes it ideal in theoretical scenarios but impractical in real-world systems since it relies on "futuristic information".
- FIFO (First-In-First-Out): ❌ This algorithm replaces the oldest page in memory (the page that has been in memory the longest). It does not require futuristic information.
- LRU (Least Recently Used): ❌ This algorithm replaces the page that has not been used for the longest period in the past. It uses past information, not futuristic information.
- Second Chance: ❌ This is a variation of the FIFO algorithm that gives a second chance to pages that have been used recently. It does not require futuristic information.
Additional Information
- While the Optimal page replacement algorithm is theoretically the best in terms of minimizing page faults, it is not practical for real-world systems because it requires exact knowledge of future memory accesses.
- In practical systems, algorithms such as LRU or Second Chance are commonly used as they rely on past behavior to predict future behavior instead of requiring exact future knowledge.