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Nam, Beomseok
Data Intensive Computing Lab
Research Interests
  • Distributed and parallel computing, high performance computing, database systems, OS and storage systems

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Multi-dimensional multiple query scheduling with distributed semantic caching framework

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Title
Multi-dimensional multiple query scheduling with distributed semantic caching framework
Author
Eom, YoungmoonKim, JinwoongNam, Beomseok
Issue Date
2015-09
Publisher
SPRINGER
Citation
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, v.18, no.3, pp.1141 - 1156
Abstract
It is becoming more important to leverage a large number of distributed cache memory seamlessly in modern large scale systems. Several previous studies showed that traditional scheduling policies often fail to exhibit high cache hit ratio and to achieve good system load balance with large scale distributed caching facilities. To maximize the system throughput, distributed caching facilities should balance the workloads and leverage cached data at the same time. In this work, we present a distributed job processing framework that yields high cache hit ratio while achieving balanced system load. Our framework employs a scheduling policy-DEMA that considers both cache hit ratio and system load and it supports geographically distributed multiple job schedulers. We show collaborative task scheduling and the data migration can even further improve the performance by increasing the cache hit ratio while achieving good load balance. Our experiments show that the proposed job scheduling policies outperform legacy load-based job scheduling policy in terms of job response time, load balancing, and cache hit ratio
URI
https://scholarworks.unist.ac.kr/handle/201301/17584
URL
http://link.springer.com/article/10.1007%2Fs10586-015-0464-6
DOI
10.1007/s10586-015-0464-6
ISSN
1386-7857
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