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There are three different but related forms of fragmentation: external fragmentation, internal fragmentation, and data fragmentation, which can be present in isolation or conjunction. Fragmentation is often accepted in return for improvements in speed or simplicity. Analogous phenomena occur for other resources such as processors; see below.
The free list may be a separate data structure, such as an array of indices indicating which entries of the slab are free, or it may be embedded within the slab. The Linux SLUB allocator keeps the free list as a linked list of pointers, each of which is stored directly in the free memory area of the slab they represent. [6]
Block suballocation addresses this problem by dividing up a tail block in some way to allow it to store fragments from other files. Some block suballocation schemes can perform allocation at the byte level; most, however, simply divide up the block into smaller ones (the divisor usually being some power of 2). For example, if a 38 KiB file is to be stored in a file system using 32
Thus, fragmentation is an important problem in file system research and design. The containment of fragmentation not only depends on the on-disk format of the file system, but also heavily on its implementation. [9] File system fragmentation has less performance impact upon solid-state drives, as there is no mechanical seek time involved. [10]
Data thus structured are said to be blocked. The process of putting data into blocks is called blocking, while deblocking is the process of extracting data from blocks. Blocked data is normally stored in a data buffer, and read or written a whole block at a time. Blocking reduces the overhead and speeds up the handling of the data stream. [3]
When constructing a linked list, one is faced with the choice of whether to store the data of the list directly in the linked list nodes, called internal storage, or merely to store a reference to the data, called external storage. Internal storage has the advantage of making access to the data more efficient, requiring less storage overall ...
However, there still exists the problem of internal fragmentation – memory wasted because the memory requested is a little larger than a small block, but a lot smaller than a large block. Because of the way the buddy memory allocation technique works, a program that requests 66 K of memory would be allocated 128 K, which results in a waste of ...
Region-based memory management works best when the number of regions is relatively small and each contains many objects; programs that contain many sparse regions will exhibit internal fragmentation, leading to wasted memory and a time overhead for region management. Again, in the presence of region inference this problem can be more difficult ...