Document Type

Technical Report

Publication Date

2003-10-10

Filename

wucse-2003-69.pdf

DOI:

10.7936/K7PZ574P

Technical Report Number

WUCSE-2003-69

Abstract

Typically, when a program executes, it creates objects dynamically and requests storage for its objects from the underlying storage allocator. The patterns of such requests can potentially lead to internal fragmentation as well as external fragmentation. Internal fragmentation occurs when the storage allocator allocates a contiguous block of storage to a program, but the program uses only a fraction of that block to satisfy a request. The unused portion of that block is wasted since the allocator cannot use it to satisfy a subsequent allocation request. External fragmentation, on the other hand, concerns chunks of memory that reside between allocated blocks. External fragmentation becomes problematic when these chunks are not large enough to satisfy an allocation request individually. Consequently, these chunks exist as useless holes in the memory system. In this thesis, we present necessary and sufficient storage conditions for satisfying allocation and deallocation sequences for programs that run on systems that use a binary-buddy allocator. We show that these sequences can be serviced without the need for defragmentation. We also explore the effects of buddy-coalescing on defragmentation and on overall program performance when using a defragmentation algorithm that implements buddy system policies. Our approach involves experimenting with Sun’s Java Virtual Machine and a buddy system simulator that embodies our defragmentation algorithm. We examine our algorithm in the presence of two approximate collection strategies, namely Reference Counting and Contaminated Garbage Collection, and one complete collection strategy - Mark and Sweep Garbage Collection. We analyze the effectiveness of these approaches with regards to how well they manage storage when we alter the coalescing strategy of our simulator. Our analysis indicates that prompt coalescing minimizes defragmentation and delayed coalescing minimizes number of coalescing in the three collection approaches.

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Permanent URL: http://dx.doi.org/10.7936/K7PZ574P

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