Dynamically Iterative MapReduce
學年 102
學期 1
出版(發表)日期 2013-11-01
作品名稱 Dynamically Iterative MapReduce
著者 Lee, Wei-Tsong; Wu, Ming-Zhi; Wei, Hsin-Wen; Yu, Fang-Yi; Lin, Yu-Sun
單位 淡江大學電機工程學系
出版者 臺北市:臺灣學術網路管理委員會
著錄名稱、卷期、頁數 網際網路技術學刊=Journal of Internet Technology 14(6),頁953-962
摘要 MapReduce is a distributed and parallel computing model for data-intensive tasks with features of optimized scheduling, flexibility, high availability, and high manageability. MapReduce can work on various platforms; however, MapReduce is not suitable for iterative programs because the performance may be lowered by frequent disk I/O operations. In order to improve system performance and resource utilization, we propose a novel MapReduce framework named Dynamically Iterative MapReduce (DIMR) to reduce numbers of disk I/O operations and the consumption of network bandwidth by means of using dynamic task allocation and memory management mechanism. We show that DIMR is promising with detail discussions in this paper.
關鍵字 Dynamically iterative MapReduce;K-Means;Particle swarm optimization (PSO);Genetic algorithm (GA);Simulated annealing (SA)
語言 en
ISSN 1607-9264
期刊性質 國內
收錄於 SCI EI
通訊作者 Wei, Hsin-Wen
國別 TWN
出版型式 ,紙本

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/93541 )


SDGS 產業創新與基礎設施