Real-time Optimization of Power and Performance for Application Server Clusters Based on MILP

被引:0
作者
Xiong Z. [1 ]
Zhao M. [1 ]
Cai H. [1 ]
Zhu C. [2 ]
Xu J. [1 ]
机构
[1] College of Engineering, Shantou University, Shantou
[2] Scientific Research Management Division, Shantou University, Shantou
来源
Hunan Daxue Xuebao/Journal of Hunan University Natural Sciences | 2023年 / 50卷 / 08期
基金
中国国家自然科学基金;
关键词
application server clusters; constrained optimization; mixed integer linear programming; power optimization; real-time; special-ordered set constraint;
D O I
10.16339/j.cnki.hdxbzkb.2023280
中图分类号
学科分类号
摘要
In the environment of energy saving and fierce peer competition,it is very urgent to optimize the power and performance optimization of application server clusters. Aiming at the deficiencies of the existing research in performance indicators and real-time performance,a real-time optimization scheme of cluster power and performance was proposed. This scheme combined the linear weighting method and the master objective method to optimize the cluster power and request drop rate,so converting the bi-objective optimization into a single-objective constrainted optimization. Firstly,based on the server load-power model in the CPU frequency equivalent continuous adjustment mode,the cluster optimization was described as a mixed integer quadratic programming problem by defining few variables. Then,variable splitting and variable conversion were used to transform the problem into a MILP(mixed integer linear programming)problem,and we introduced an SOS(special-Ordered set)constraint. Finally,the Gurobi optimizer was used to solve the MILP problem. Through further optimization of CPU frequency adjustment,the switching of CPU frequency was greatly reduced. Tests in various scenarios showed that the average solution time of the scheme was approximately 10 ms and the introduction of SOS constraint made the solution time more stable,which can ensure the real-time optimization. © 2023 Hunan University. All rights reserved.
引用
收藏
页码:153 / 164
页数:11
相关论文
共 31 条
[1]  
ZHOU Z, YUAN Y J M,, LI F M., Energy consumption modeling and quantitative calculation of servers in cloud data center[J], Journal of Hunan University(Natural Sciences), 48, 4, pp. 36-44, (2021)
[2]  
JIN C Q,, BAI X L,, YANG C, A review of power consumption models of servers in data centers[J], Applied Energy, 265, (2020)
[3]  
A heuristic task scheduling algorithm based on server power efficiency model in cloud environments[J], Sustainable Computing:Informatics and Systems, 20, pp. 56-65, (2018)
[4]  
DE ALMEIDA A., A review on energy efficiency and demand response with focus on small and medium data centers[J], Energy Efficiency, 12, 5, pp. 1399-1428, (2019)
[5]  
WANG J L,, GONG B, LIU H, Green heterogeneous scheduling algorithm through deep integration of hardware and software energy saving principles, Journal of Software, 32, 12, pp. 3768-3781, (2021)
[6]  
O'DWYER K J, PURCELL M, Power saving proxies for web servers[J], The Computer Journal, 63, 2, pp. 179-192, (2020)
[7]  
MOSSE D., Power optimization for dynamic configuration in heterogeneous web server clusters[J], Journal of Systems and Software, 83, 4, pp. 585-598, (2010)
[8]  
SUN J,, LIAO D, A strategy for queuing theory-based performance and energy management in heterogeneous data centers [J], Journal of University of Electronic Science and Technology of China, 47, 2, pp. 161-168, (2018)
[9]  
CHANG C J, CHANG F M, KE J C., Optimal power consumption analysis of a load-dependent server activation policy for a data service center[J], Computers & Industrial Engineering, 130, pp. 745-756, (2019)
[10]  
LI K Q., Power and performance management for parallel computations in clouds and data centers[J], Journal of Computer and System Sciences, 82, 2, pp. 174-190, (2016)