The integrated modular avionics (IMA) architecture is an open standard in avionics industry, in which the number of functionalities implemented by software is greater than ever before. In the IMA architecture, the reliability of the avionics system is highly affected by the software applications. In order to enhance the fault tolerance feature with regard to software application failures, many industrial standards propose a layered health monitoring/fault management (HM/FM) scheme to periodically check the health status of software application processes and recover the malfunctioning software process whenever an error is located. In this paper, we make an analytical study of the HM/FM system for avionics application software. We use the stochastic Petri nets (SPN) to build a formal model of each component and present a method to combine the components together to form a complete system model with respect to three interlayer query strategies. We further investigate the effectiveness of these strategies in an illustrative system.
Wan JianxiongXiang XudongBai XiaoyingLin ChuangKong XiangzhenLi Jianxiang
条件随机场(condition random fields,CRFs)可用于解决各种文本分析问题,如自然语言处理(natural language processing,NLP)中的序列标记、中文分词、命名实体识别、实体间关系抽取等.传统的运行在单节点上的条件随机场在处理大规模文本时,面临一系列挑战.一方面,个人计算机遇到处理的瓶颈从而难以胜任;另一方面,服务器执行效率较低.而通过升级服务器的硬件配置来提高其计算能力的方法,在处理大规模的文本分析任务时,终究不能从根本上解决问题.为此,采用"分而治之"的思想,基于Apache Spark的大数据处理框架设计并实现了运行在集群环境下的分布式CRFs——SparkCRF.实验表明,SparkCRF在文本分析任务中,具有高效的计算能力和较好的扩展性,并且具有与传统的单节点CRF++相同水平的准确率.
