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True random and adjustable memory management evaluation framework with Markov chain

Authors: Alvin Syarifudin Shahab; Dadet Pramadihanto; Sritrustra Sukaridhoto; Adhe Widianjaya;

True random and adjustable memory management evaluation framework with Markov chain

Abstract

Memory management evaluation test is one of the ways to understand the characteristic and performance of dynamic memory allocation algorithm. DMA is one of the RTOS parts that provide storage management when the applications are running. Nowadays there is a lot of memory management algorithm, and each algorithm has its own characteristics like the deterministic or nondeterministic algorithm. We develop a testing framework using Markov chain in order to test the allocation algorithm performance to fit the allocation behavior in RTOS. The framework generates various type of scenario test which can determine deterministic and nondeterministic of the algorithm based on the performance result. The result shows the impact of allocation size and allocation variation affect the allocation performance respond that generated by this framework.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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