@inproceedings{ab165e1334e34766b8d31f7a4f6c35d2,
title = "An Adaptive Control Strategy for Resource Allocation of Service-Based Systems in Cloud Environment",
abstract = "Service-based systems (SBS) resource allocation in cloud computing environment is important to guarantee Quality of Service (QoS) to satisfy requirements of service requests as well as reduce operating costs. In this paper, a control strategy is presented to allocate the system resources of cloud provider to the servers using PID self tuning adaptive control dynamically. Meanwhile, an adaptive mechanism using Radial Basis Function (RBF) neural network is devised to adjust parameters of PID controller adaptively in run time. Experimental results show that the approach enables to satisfy the requirements of services-requests with less adjustment of resource allocation, and has better adaptive ability and stability compared to conventional PID control.",
keywords = "Cloud environment, PID self-Tuning adaptive control, Quality of service, RBF neural network, Resource allocation",
author = "Siqian Gong and Beibei Yin and Wenlong Zhu and Kaiyuan Cai",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; IEEE International Conference on Software Quality, Reliability and Security-Companion, QRS-C 2015 ; Conference date: 03-08-2015 Through 05-08-2015",
year = "2015",
month = nov,
day = "6",
doi = "10.1109/QRS-C.2015.17",
language = "英语",
series = "Proceedings - 2015 IEEE International Conference on Software Quality, Reliability and Security-Companion, QRS-C 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "32--39",
booktitle = "Proceedings - 2015 IEEE International Conference on Software Quality, Reliability and Security-Companion, QRS-C 2015",
address = "美国",
}