Belief-Based Storage Systems


Dusan Ramljak and Krishna Kant, Temple University


The current data growth and consequent increase in complexity of its usage patterns indicate that intelligent management of data storage is becoming ever more crucial . We rely on the claim that efficient pattern discovery and description, coupled with the observed predictability of complex patterns within many high-performance applications, offers significant potential to enable many I/O optimizations. We developed a compact flexible caching and pre-fetching framework that could, potentially address any imposed reliability, performance, energy efficiency requirement and have the ability to add any relevant information. Here, we discuss possible ways to extend this framework towards belief based storage systems.

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@inproceedings {203392,
author = {Dusan Ramljak and Krishna Kant},
title = {{Belief-Based} Storage Systems},
booktitle = {9th USENIX Workshop on Hot Topics in Storage and File Systems (HotStorage 17)},
year = {2017},
address = {Santa Clara, CA},
url = {},
publisher = {USENIX Association},
month = jul,