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Online and offline based load balance algorithm in cloud computing

delete2017-12-01
delete17
PRE
AI
L
Linlin Tang *
Z
Zuohua Li
J
Jeng‐Shyang Pan
Z
Zhe‐Ming Lu
苏敬勇 (Jingyong Su)
Z
Zhenyu Meng
DOI:10.1016/j.knosys.2017.09.040delete
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摘要

摘要

En 中文
Cloud Computing (CC) makes it possible for a common user to get an access to large pools of data and computational resources through a variety of interfaces. Among the so many important problems in CC, load balancing technique has been paid more and more attention for its important role. Good load balance algorithms can make whole system run more efficient. A new load balancing method combined with the advantage of online and offline load balancing algorithms are proposed in this paper. Two choice algorithm and its improvement are used in the online step. Bacteria Foraging Optimization (BFO) and its improvement motivated by Lamarck Evolutionary Theory are introduced in our offline step. Online load balancing uses imperfect information, aiming at finishing tasks as fast as possible; while the offline makes full use of all information to make a supplement. Experiments on the heterogeneous tasks and serving points for computation intensive loads have been used here and the good performance shows the efficiency of our proposed method. (C) 2017 Elsevier B.V. All rights reserved.
Keyword:
Cloud computing
Bacteria foraging optimization algorithm
Load balance
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期刊

K
Knowledge-Based Systems
IF:
7.6
论文数:
1.2W
被引数:
4.5W

机构

H
harbin institute of technology
学者数:
8.0W
论文数: 6.6W
被引数: 66
Texas Tech University System 封面图
Texas Tech University System
学者数:
1.5W
论文数: 1.3W
被引数: 15
Z
zhejiang university
学者数:
17.7W
论文数: 12.1W
被引数: 152
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