TY - JOUR
T1 - CLB
T2 - A novel load balancing architecture and algorithm for cloud services
AU - Chen, Shang Liang
AU - Chen, Yun Yao
AU - Kuo, Suang Hong
N1 - Funding Information:
The authors thank the Ministry of Science and Technology No. MOST-103-2221-E-006 -085 - , who sponsored this research and provided related technological support. Due to support from the Ministry of Science and Technology , this research could proceed smoothly.
Publisher Copyright:
© 2016 Elsevier Ltd
PY - 2017/2/1
Y1 - 2017/2/1
N2 - Cloud services are widely used in manufacturing, logistics, digital applications, and document processing. Cloud services must be able to handle tens of thousands of concurrent requests and to enable servers to seamlessly provide the amount of load balancing capacity required to respond to incoming application traffic in addition to allowing users to obtain information quickly and accurately. In the past, researchers have proposed the use of static load balancing or server response times to evaluate load balancing capacity, a lack of which may cause a server to load unevenly. In this study, a dynamic annexed balance method is used to solve this problem. Cloud load balancing (CLB) takes into consideration both server processing power and computer loading, thus making it less likely that a server will be unable to handle excessive computational requirements. Finally, two algorithms in CLB are also addressed with experiments to prove the proposed approach is innovative.
AB - Cloud services are widely used in manufacturing, logistics, digital applications, and document processing. Cloud services must be able to handle tens of thousands of concurrent requests and to enable servers to seamlessly provide the amount of load balancing capacity required to respond to incoming application traffic in addition to allowing users to obtain information quickly and accurately. In the past, researchers have proposed the use of static load balancing or server response times to evaluate load balancing capacity, a lack of which may cause a server to load unevenly. In this study, a dynamic annexed balance method is used to solve this problem. Cloud load balancing (CLB) takes into consideration both server processing power and computer loading, thus making it less likely that a server will be unable to handle excessive computational requirements. Finally, two algorithms in CLB are also addressed with experiments to prove the proposed approach is innovative.
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U2 - 10.1016/j.compeleceng.2016.01.029
DO - 10.1016/j.compeleceng.2016.01.029
M3 - Article
AN - SCOPUS:84975744267
SN - 0045-7906
VL - 58
SP - 154
EP - 160
JO - Computers and Electrical Engineering
JF - Computers and Electrical Engineering
ER -