Memory Allocation Technique for Segregated Free List Based on Genetic Algorithm | ||
| Journal of Al-Nahrain University - Science | ||
| Article 1, Volume 15, Issue 2, June 2012, Pages 161-168 | ||
| Author | ||
| Manal F. Younis | ||
| Abstract | ||
| Dynamic memory management is an important part of computer systems design. Efficient memory allocation, garbage collection and compaction are becoming increasingly more critical in parallel, distributed and real-time applications. The memory efficiency is related to the fragmentation. Segregation is one of the simplest allocation policies which use a set of free lists, where each list holds blocks of a particular size. When the process requests a memory. The free list for the appropriate size is used to satisfy the request. This paper proposes a scheme to reduce the internal fragmentation of a segregated free list for improving memory efficiency using genetic algorithm (GA) to find the optimal configuration. Because the genetic algorithms (GAs) are largely used in optimization problems, they facilitate a good alternative in problem areas where the number of constraints is too large for humans to efficiently evaluate. This GA is tested under five randomly created workloads to find the best configuration. The results are acceptable when compared with optimal configurations of these workloads | ||
| Keywords | ||
| Memory allocation; Segregated free list; genetic algorithm; Crossover; Mutation | ||
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