Best Fit Algorithm in Operating System Program In Python

July 13, 2023

Best Fit Operator In Python

Introduction to Best Fit Algorithm In Operating System

The Best Fit Algorithm is a memory allocation technique that aims to find the smallest available memory block that can accommodate a process.

In the field of operating systems, the allocation of memory to processes is a crucial task. One of the commonly used memory allocation algorithms is the Best Fit Algorithm. In this article, we will explore the Best Fit Algorithm and its implementation in Python.

Overview of Best Fit Algorithm

It scans through the memory blocks and selects the one that provides the best fit for the process, minimizing wastage of memory.

The Best Fit Algorithm works by iterating through the list of available memory blocks and finding the one that can accommodate the process while leaving the smallest amount of unused memory. It compares the size of the process with the available memory blocks and selects the block that has the minimum leftover memory after allocation.

The Best Fit algorithm offers several advantages:

  1. Efficient utilization of memory: The Best Fit Algorithm aims to minimize the wastage of memory by selecting the memory block with the minimum leftover space.
  2. Better for long-term performance: The algorithm tends to distribute processes across memory blocks more evenly, leading to improved long-term performance.

Despite its advantages, the Best Fit algorithm has a few limitations:

  1. Fragmentation: The Best Fit Algorithm can result in external fragmentation, where small blocks of free memory are scattered throughout the system, making it difficult to allocate large contiguous blocks of memory.
  2. Higher computational overhead: The algorithm requires scanning through the list of memory blocks, which can be computationally expensive for large memory systems.

The Best Fit Algorithm finds applications in various areas, including:

  • Operating systems
  • Virtual memory management
  • Dynamic memory allocation in programming languages

Implementation of Best Fit Algorithm in Python:

Step 1: Initialize the memory blocks and process sizes.

memory_blocks = [100, 500, 200, 300, 600]
process_sizes = [350, 200, 150, 400, 250]

Step 2: Create an allocation list to track the allocation of processes.

allocation = [-1] * len(process_sizes)

Step 3: Iterate through each process and find the best fit memory block for it.

for i in range(len(process_sizes)):
    best_fit_index = -1
    min_leftover = float('inf')

    # Iterate through each memory block
    for j in range(len(memory_blocks)):
        # Check if the memory block can accommodate the process
        if memory_blocks[j] >= process_sizes[i]:
            leftover = memory_blocks[j] - process_sizes[i]
            # Find the memory block with the minimum leftover space
            if leftover < min_leftover:
                min_leftover = leftover
                best_fit_index = j

    # If a suitable memory block is found
    if best_fit_index != -1:
        # Allocate the process to the selected memory block
        allocation[i] = best_fit_index
        memory_blocks[best_fit_index] -= process_sizes[i]

Step 4: Print the allocation list to see the result.

print("Process allocation:", allocation)

Memory Management Introduction

Paging

Difference between Segmentation and Paging

Process Address Space

Run 
# Python implementation of the Best Fit Algorithm
def best_fit(memory_blocks, process_size):
    best_fit_index = -1
    min_leftover = float('inf')

    for i in range(len(memory_blocks)):
        if memory_blocks[i] >= process_size:
            leftover = memory_blocks[i] - process_size
            if leftover < min_leftover:
                min_leftover = leftover
                best_fit_index = i

    if best_fit_index != -1:
        memory_blocks[best_fit_index] -= process_size
        return best_fit_index

    return -1

# Usage example
memory_blocks = [100, 500, 200, 300, 600]
process_size = 350
index = best_fit(memory_blocks, process_size)
print("Process allocated to block:", index)

Process allocated to block: 1
  • In this implementation, the best_fit function takes a list of memory blocks (memory_blocks) and the size of the process to be allocated (process_size) as inputs. It iterates through each memory block, checking if it can accommodate the process. If a memory block is found that has enough space and leaves the minimum leftover space after allocation.
  • In the usage example, we have a list of memory blocks [100, 500, 200, 300, 600] and a process size of 350. By calling the best_fit function with these inputs, we allocate the process to the memory block index returned by the function. Finally, we print the allocated memory block index using the print statement.
Run 
# Python implementation of the Best Fit Algorithm
def best_fit(memory_blocks, process_sizes):
    allocation = [-1] * len(process_sizes)

    # Iterate through each process
    for i in range(len(process_sizes)):
        best_fit_index = -1
        min_leftover = float('inf')

        # Iterate through each memory block
        for j in range(len(memory_blocks)):
            # Check if the memory block can accommodate the process
            if memory_blocks[j] >= process_sizes[i]:
                leftover = memory_blocks[j] - process_sizes[i]
                # Find the memory block with the minimum leftover space
                if leftover < min_leftover:
                    min_leftover = leftover
                    best_fit_index = j

        # If a suitable memory block is found
        if best_fit_index != -1:
            # Allocate the process to the selected memory block
            allocation[i] = best_fit_index
            memory_blocks[best_fit_index] -= process_sizes[i]

    return allocation

# Usage example
memory_blocks = [100, 500, 200, 300, 600]
process_sizes = [350, 200, 150, 400, 250]
allocation = best_fit(memory_blocks, process_sizes)
print("Process allocation:", allocation)

Output:

Process allocation: [1, 2, 1, 4, 3]
  • In this example, the best_fit function takes a list of memory blocks (memory_blocks) and a list of process sizes (process_sizes) as inputs. It initializes an allocation list with -1 values, indicating that no allocation has been made yet for each process.
  • The function then iterates through each process and finds the best fit memory block for it by following the same logic as explained earlier. If a suitable memory block is found, the process is allocated to that block, and the allocation list is updated accordingly.
  • In the usage example, we have a list of memory blocks [100, 500, 200, 300, 600] and a list of process sizes [350, 200, 150, 400, 250]. By calling the best_fit function with these inputs, we allocate each process to the best fit memory block. The resulting allocation list is then printed using the print statement.

Conclusion

The Best Fit Algorithm is a memory allocation technique that aims to minimize memory wastage by selecting the memory block that provides the best fit for a process. In this article, we discussed the algorithm’s working, implemented it in Python, highlighted its advantages and limitations, and compared it with other memory allocation algorithms. Understanding different memory allocation techniques is essential for optimizing the performance of operating systems.

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