Next Fit Policy

Duration: 3 min

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Module outline

  1. About the Course: About the Course
  2. Paper-1 & 2 | Basic Numeracy: Ratio and Proportion (Ratios), Divisibility Rules, Mixture and Alligation, Permutation and Combination, Logarithm, Number System, HCF LCM, Sequence and Series (Series), Speed Time and Distance, Percentage, Average, Mensuration and Geometry, Age Problems, Arithmetic, Statistics, Probability, Profit and Loss, Simple Interest and Compound Interest, Partnership, Speed Mathematics and Basic Mathematics, Algebra, Powers and Exponents (Surds and Indices), Time and Work, Pipe and Cistern, RSSB Specific Videos - Basic Numeracy
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  4. Paper-1 & 2 | General Mental Ability: Mental Ability, RSSB Specific Videos - Mental Ability
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  18. Paper-2 | Algorithms: Algorithm Analysis, Time Complexity Analysis, Sorting Algorithms, Greedy Algorithms, Advanced Algorithms
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AI summary & chapters

AI Summary

An AI-generated summary of this video lecture.

The video lecture covers memory allocation strategies, specifically focusing on the "Next fit policy" and "External fragmentation". The instructor begins by defining Next fit as a modification of the Best fit algorithm. He illustrates on a whiteboard how the search for memory blocks continues from the last allocated position rather than restarting from the beginning. Later, the lecture transitions to the concept of External fragmentation, explaining it as a consequence of contiguous allocation policies where free memory exists but is non-contiguous, preventing the allocation of larger processes. This progression highlights the relationship between allocation efficiency and memory wastage.

Chapters

  1. 0:00 – 2:00 00:00-02:00

    The instructor introduces the "Next fit policy" using a slide that defines it as a modification of the best fit algorithm. He explains that after satisfying a request, the search for the next request starts from the "current position" rather than the beginning of memory. Visually, he draws a long horizontal rectangle on the whiteboard to represent memory blocks. He marks specific sections with diagonal lines to denote allocated space and draws a red arrow pointing to the right to demonstrate the search pointer moving forward from the last allocation point. He emphasizes that this approach avoids scanning the entire memory list repeatedly, unlike the standard Best fit method, which restarts the search from the start every time.

  2. 2:00 – 3:04 02:00-03:04

    The lecture transitions to a new topic, "External fragmentation," displayed on the slide. The text defines it as a function of contiguous allocation policy where requested space is available but not contiguous. The instructor explains that this wastage occurs because the scattered free blocks cannot be combined to satisfy a single large request. He uses hand gestures to indicate separate, non-adjacent blocks of memory. The slide text explicitly states, "The space requested by the process is available in memory but, as it is not being contiguous, cannot be allocated this wastage is called external fragmentation." He clarifies that even if total free space is sufficient, the lack of contiguity prevents allocation.

The lesson progresses from a specific allocation algorithm to a fundamental memory management problem. By first detailing how Next fit optimizes search efficiency compared to Best fit, the instructor sets the stage for understanding the limitations of contiguous allocation. The introduction of External fragmentation highlights the trade-off: while algorithms like Next fit manage allocation efficiently, the requirement for contiguous blocks inherently leads to wasted space when free memory is fragmented. This connects the mechanical process of allocation to the resulting state of the memory system, showing how efficient searching does not solve the underlying issue of scattered free blocks.

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