Software ageing process as an evolving dynamic system

被引:3
作者
Jia, Yun-Fei [1 ]
Zhou, Zhi Quan [2 ]
Wu, Renbiao [1 ]
机构
[1] Civil Aviat Univ China, Tianjin Key Lab Adv Signal Proc, Tianjin 300300, Peoples R China
[2] Univ Wollongong, Inst Cybersecur & Cryptol, Sch Comp & Informat Technol, Wollongong, NSW 2522, Australia
基金
澳大利亚研究理事会;
关键词
ageing; resource allocation; software reliability; Linux; Jacobian matrices; software performance evaluation; computing resources; computer system; dynamic system; nonlinear dynamic model; dynamic inversion method; resource variables; central processing unit usage; software performance; Linux operating system; software ageing process; Jacobi matrix method;
D O I
10.1049/iet-sen.2019.0155
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Software ageing is correlated with available computing resources of the computer system. These available resources evolve with time, reflecting the developing mechanism of the ageing process. This study is the first to consider a degrading computer system as an evolving dynamic system. The authors proposed a non-linear dynamic model of software ageing, where the coefficients are estimated using a dynamic inversion method, and conduct controlled software experiments, where the experimental conditions are controlled to expedite ageing. The model can be used to forecast mutations of resource variables such as the buffer, cache and central processing unit usage, which have a direct impact on software performance. The stability of the model is assessed by the Jacobi matrix method, and the results show that, when part of a resource has become unallocable, the Linux operating system can readjust the resources to keep the system's performance stable. This process repeats until some of the resources are exhausted, when the system will crash or hang. This study provides hints on the ageing mechanism of computer systems, which are rarely reported in the past.
引用
收藏
页码:702 / 710
页数:9
相关论文
共 21 条
[1]   Generalised dynamic inversion spacecraft control design methodologies [J].
Bajodah, A. H. .
IET CONTROL THEORY AND APPLICATIONS, 2009, 3 (02) :239-251
[2]  
Bishop C. M.., 2006, PATTERN RECOGN
[3]   Software execution processes as an evolving complex network [J].
Cai, Kai-Yuan ;
Yin, Bei-Bei .
INFORMATION SCIENCES, 2009, 179 (12) :1903-1928
[4]   Analyzing software science data with partial repeatability [J].
Cai, KY ;
Chen, L .
JOURNAL OF SYSTEMS AND SOFTWARE, 2002, 63 (03) :173-186
[5]   Infodynamics: Analogical analysis of states of matter and information [J].
Ceruti, Marion G. ;
Rubin, Stuart H. .
INFORMATION SCIENCES, 2007, 177 (04) :969-987
[6]   ARF-Predictor: Effective Prediction of Aging-Related Failure Using Entropy [J].
Chen, Pengfei ;
Qi, Yong ;
Li, Xinyi ;
Hou, Di ;
Lyu, Michael Rung-Tsong .
IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING, 2018, 15 (04) :675-693
[7]   Long-Stroke Hydraulic Robot Motion Control With Incremental Nonlinear Dynamic Inversion [J].
Huang, Yingzhi ;
Pool, Daan M. ;
Stroosma, Olaf ;
Chu, Qiping .
IEEE-ASME TRANSACTIONS ON MECHATRONICS, 2019, 24 (01) :304-314
[8]  
Jia YF, 2017, INT ARAB J INF TECHN, V14, P223
[9]   Using Neural Networks to Forecast Available System Resources: An Approach and Empirical Investigation [J].
Jia, Yun-Fei ;
Zhou, Zhi Quan ;
Xue, Ke-Xian ;
Zhao, Lei ;
Cai, Kai-Yuan .
INTERNATIONAL JOURNAL OF SOFTWARE ENGINEERING AND KNOWLEDGE ENGINEERING, 2015, 25 (04) :781-802
[10]   A workload-based nonlinear approach for predicting available computing resources [J].
Jia Yunfei ;
Zhou Zhiquan ;
Wu Renbiao .
JOURNAL OF SYSTEMS ENGINEERING AND ELECTRONICS, 2020, 31 (01) :224-230