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Articles by Meng Haining
Total Records ( 3 ) for Meng Haining
  Qi Yong , Meng Haining , Hou Di and Chen Ying
  Software rejuvenation is a main method for counteracting software aging, when it is performed in cluster system, system reliability can be significantly increased. We firstly presented a software rejuvenation policy of application sever cluster. Then we set up a software rejuvenation model in two-dimension state space for a two-node application server cluster and give the quantitative analysis using continuous time Markov process. Finally, the numerical experiment results show that the selected optimal software rejuvenation interval can greatly reduce expected systematic downtime and improve software reliability of application server cluster.
  Meng Haining , Hei Xinhong and Liu Jianjun
  As a proactive and preventive software fault tolerant technique, software rejuvenation is a main method for counteracting software aging. In this study, a software rejuvenation model based on periodical inspection policy is set up. Firstly, by analyzing runtime state and failure feature of software system, the functions of system unavailability and cost rate are given and optimal system inspection interval and software rejuvenation interval are selected via minimizing system unavailability and cost rate. Then boundary conditions of cost rate and optimal inspection interval are deduced. Finally, quantitative analysis and numeric experiment result show that selecting optimal inspection interval and software rejuvenation interval can greatly reduce system cost and improve system availability and reliability. In addition, the numeric experiment result further validate that the software rejuvenation model with periodical inspection policy has higher system availability than the general software rejuvenation model in the case of the failure rate following Weibull and exponential distribution.
  Meng Haining , Hei Xinhong , Liu Jianjun and Wei Wei
  Long-running software system tends to show performance degradation and sudden failures, due to error accumulation or resource exhaustion over time. This phenomenon is usually called software aging. This study presents a memory-related detection method to investigate software aging in a service-oriented J2EE application server running on Java Virtual Machine (JVM). By studying the problem of memory leaks in JVM, the memory analyzer tool referred as Profiler is designed and developed to collect the performance data of JVM heap memory. Finally, the experimental results and statistical analysis of collected data validate the presence of software aging in the application server.
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