Key Takeaways
- Internal fragmentation results in waste within allocated memory blocks, leading to unused space that can’t be repurposed,
- External fragmentation causes scattered free memory spaces, making it hard to find contiguous blocks for large data.
- Compaction can help reduce external fragmentation but involves overhead and temporary performance drops.
- Internal fragmentation is more predictable, while external fragmentation varies based on memory allocation patterns.
- Understanding both types helps in choosing appropriate memory management strategies for specific system needs.
What is Internal Fragmentation?
Internal fragmentation happens when a fixed memory block is allocated, but the process doesn’t use all of it, leaving leftover space inside the block.
This leftover space can’t be assigned to other processes, leading to waste. It occurs in systems with fixed partitioning schemes.
Memory Allocation Wastage
When a process requests a specific size, the system assigns a block larger than needed, causing part of the block to stay unused.
This leftover space within the block can’t be used by other processes, creating inefficiency in memory utilization.
Fixed Partitioning Impact
In systems with fixed-sized partitions, processes fitting into these partitions leave small gaps unused.
These gaps accumulate over time, reducing the effective memory available for new processes.
Predictability and Management
Internal fragmentation is easier to predict because it depends on fixed sizes and allocation policies.
Managing it involves choosing optimal block sizes or using variable partitioning to reduce waste.
Performance Considerations
Excessive internal fragmentation can lead to inefficient memory usage, affecting system performance.
It may cause increased swapping or reduce the number of processes which can run simultaneously.
What is External Fragmentation?
External fragmentation occurs when free memory is divided into small, noncontiguous blocks scattered across the system, making it difficult to allocate large contiguous spaces.
This fragmentation stems from processes being allocated and deallocated dynamically, leaving gaps of unused space.
Memory Hole Formation
Repeated allocations and deallocations create small pockets of free memory, which may not be large enough for new processes.
This leads to a situation where large memory chunks are unavailable despite overall free memory being sufficient.
Impact on Large Data Handling
External fragmentation particularly affects the ability to process large files or applications requiring contiguous memory blocks.
It may force the system to split data or perform costly memory management operations to accommodate requests.
Memory Compaction
Compaction is a technique to move allocated blocks together, consolidating free space to reduce external fragmentation.
While effective, it requires system overhead and may temporarily slow down system performance during the process.
Fragmentation Over Time
External fragmentation tends to worsen over time as processes are created and destroyed, leaving behind small unusable gaps.
Without defragmentation, memory becomes less efficient, limiting system capacity and responsiveness.
Comparison Table
Below is a detailed comparison between internal and external fragmentation, highlighting their distinctions across multiple aspects.
| Aspect | Internal Fragmentation | External Fragmentation |
|---|---|---|
| Waste Type | Unused space within allocated blocks | Unused spaces scattered outside allocated blocks |
| Causes | Fixed partition sizes, over-allocation | Dynamic allocation and deallocation processes |
| Predictability | More predictable, due to fixed sizes | Less predictable, varies as processes change |
| Management Method | Choosing optimal block sizes or variable partitioning | Memory compaction or paging techniques |
| Impact on System Performance | Reduces effective memory, may cause delays | Can block large memory requests, slowing processes |
| Occurrence Pattern | Consistent, based on fixed sizes | Irregular, depends on process lifecycle |
| Effect on Large Files | Less problematic, as size isn’t a major issue | More problematic, may prevent large contiguous storage |
| Remediation | Adjusting block sizes, using variable partitioning | Memory defragmentation or paging |
| Resource Wastage | More predictable, small amounts | Can lead to significant wastage over time |
| Effect on Memory Utilization | Decreases efficiency, causes space wastage | Decreases efficiency, causes inability to allocate large blocks |
Key Differences
- Internal Fragmentation is clearly visible in unused space within allocated memory blocks, whereas External Fragmentation appears as scattered free spaces across the memory.
- Internal fragmentation revolves around fixed-size allocations, while External fragmentation depends on dynamic process arrangements.
- Internal fragmentation is predictable and easier to manage, but External fragmentation can fluctuate unpredictably over time.
- External fragmentation relates to overall space availability, while Internal fragmentation concerns inefficiency inside allocated blocks.
FAQs
What are the common techniques to reduce external fragmentation?
Memory compaction and paging are primary methods. Although incomplete. They reorganize or break memory into smaller chunks to improve space utilization.
Can internal fragmentation be completely eliminated?
In most cases, it cannot be fully removed due to fixed block sizes. Although incomplete. Variable partitioning reduces it but doesn’t eliminate it entirely.
How does fragmentation impact system reliability?
High fragmentation can cause failures in memory allocation, leading to crashes or slowdowns, especially when large contiguous blocks are needed.
Are there specific systems more prone to each type of fragmentation?
Fixed partition systems are more affected by internal fragmentation, while systems with frequent process creation and deletion face more external fragmentation.
Last Updated : 06 May, 2025
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Sandeep Bhandari holds a Bachelor of Engineering in Computers from Thapar University (2006). He has 20 years of experience in the technology field. He has a keen interest in various technical fields, including database systems, computer networks, and programming. You can read more about him on his bio page.