Page Replacement Algorithm Calculator – FIFO, LRU & Optimal Simulation

Page Replacement Algorithm Calculator

Simulate and visualize FIFO, LRU, and Optimal page replacement algorithms with step-by-step animations

🧠 What Is Page Replacement in Operating Systems?

Page replacement is a crucial memory management technique used in operating systems when physical memory (RAM) becomes full. When a program requests a page that isn’t currently in memory (causing a page fault), the OS must decide which existing page to remove to make space for the new one.

Think of it like a parking lot with limited spaces. When all spots are full and a new car arrives, you need to decide which parked car to move out to make room. The strategy you use to make this decision is your “page replacement algorithm.”

Why Page Replacement Matters

Efficient page replacement algorithms minimize the number of page faults, which directly impacts system performance. Each page fault requires expensive disk I/O operations, so reducing them is critical for optimal system performance.

📋 Page Replacement Algorithms Explained

FIFO (First In First Out)

The FIFO algorithm removes the oldest page in memory – the one that has been there the longest. It’s simple to implement using a queue data structure but doesn’t consider how frequently pages are used.

Example: If pages arrive in order [A, B, C] and we need to replace one, FIFO will always remove page A first, regardless of whether it’s still being used frequently.

LRU (Least Recently Used)

LRU removes the page that hasn’t been accessed for the longest time. This algorithm assumes that recently used pages are more likely to be used again soon, which often holds true in practice.

Example: If we have pages [A, B, C] and page B was accessed most recently, then A, then C, LRU would remove page C first.

Optimal Algorithm

The optimal algorithm (also called Belady’s algorithm) removes the page that will be needed furthest in the future, or never again. While theoretically perfect, it’s impossible to implement in practice since we can’t predict future page requests.

Example: If we know future requests will be [D, A, E], and we have pages [A, B, C], optimal would remove B since it won’t be needed, keeping A which will be needed soon.

💡 Real-Life Analogies for Better Understanding

FIFO – Library Book Returns

Imagine a small library shelf that can only hold 3 books. When a 4th book arrives, you always remove the book that’s been on the shelf the longest, regardless of how popular it is. This is exactly how FIFO works.

LRU – Your Phone’s Recent Apps

Your smartphone keeps recently used apps in memory. When memory gets full, it removes the app you haven’t used in the longest time. This is LRU in action – prioritizing recently accessed items.

Optimal – Perfect Prediction

Imagine if you could see the future and know exactly which books people will ask for next week. You’d keep those books and remove the ones nobody will want. That’s the optimal algorithm – perfect but impossible in real life.

📈 How to Analyze Page Faults

Page fault analysis helps you understand algorithm efficiency:

  • Page Fault Rate: Number of faults ÷ Total requests
  • Hit Ratio: (Total requests – Page faults) ÷ Total requests
  • Efficiency: Higher hit ratio = Better performance

A good page replacement algorithm should minimize page faults while being computationally efficient to implement.

🔄 Algorithm Comparison

Algorithm Implementation Time Complexity Advantages Disadvantages
FIFO Queue O(1) Simple, Fair Belady’s Anomaly, Ignores usage patterns
LRU Stack/Counter O(1) to O(n) Good performance, Considers recency Complex implementation, Overhead
Optimal Future knowledge O(n) Theoretical minimum faults Impossible to implement practically

🔍 Tips to Minimize Page Faults

  • Increase Physical Memory: More RAM means fewer page faults
  • Optimize Code Locality: Access related data together
  • Use Appropriate Data Structures: Choose structures that promote locality
  • Implement Prefetching: Load pages before they’re needed
  • Choose Right Algorithm: LRU often performs better than FIFO in practice

❓ Frequently Asked Questions

Which page replacement algorithm is best?
There’s no universally “best” algorithm. LRU often performs well in practice due to temporal locality, but the optimal choice depends on your specific workload. FIFO is simpler but may cause more page faults. Optimal is theoretically perfect but impossible to implement.
What causes a page fault?
A page fault occurs when a program tries to access a page that isn’t currently in physical memory. This can happen when: 1) The page has never been loaded, 2) The page was swapped out to disk due to memory pressure, or 3) The page is protected and the access violates permissions.
How is LRU implemented in real systems?
Real systems use approximations of LRU since true LRU is expensive. Common approaches include: Clock algorithm (second chance), aging algorithms with reference bits, and hardware-assisted methods using access timestamps. These provide good LRU approximation with lower overhead.
What is Belady’s Anomaly?
Belady’s Anomaly is a counter-intuitive phenomenon where increasing the number of page frames can actually increase the number of page faults in FIFO algorithm. This doesn’t occur with stack-based algorithms like LRU and Optimal.

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