file allocation methods - TarisMajor/5143-OpSystems GitHub Wiki

linked-file-allocation

File Allocation Methods:

  • Definition: File allocation methods refer to the strategies used by an operating system to assign disk space to files. These methods determine how files are stored, accessed, and managed on secondary storage (like hard drives). The choice of allocation method can impact performance, fragmentation, and efficiency in file management.
  1. Contiguous Allocation:

    • Definition: In contiguous allocation, each file is stored in a single, contiguous block of space on the disk. The operating system allocates a continuous range of disk blocks to a file, making access to the file fast and efficient because the file’s data is stored sequentially. However, this method can lead to problems with fragmentation as files are created and deleted over time, leaving gaps between used space.
  2. Linked Allocation:

    • Definition: In linked allocation, files are stored as a linked list of blocks scattered throughout the disk. Each block contains a pointer to the next block in the file. This allows files to be stored in non-contiguous blocks, reducing fragmentation. However, it can lead to slower file access since the system must follow the chain of pointers to access the data.
  3. Indexed Allocation:

    • Definition: In indexed allocation, a separate index block is used to store the addresses of all the blocks that make up a file. The file’s data is not stored contiguously, but the index block provides a quick reference to the locations of the data blocks, which can be non-contiguous. This method combines the advantages of both contiguous and linked allocation by allowing random access to files while avoiding fragmentation.

Sources:

  • Silberschatz, A., Galvin, P. B., & Gagne, G. (2018). Operating System Concepts (10th Edition).
  • Tanenbaum, A. S., & Bos, H. (2014). Modern Operating Systems (4th Edition).
  • Stallings, W. (2018). Operating Systems: Internals and Design Principles (9th Edition).
  • ChatGPT
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