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集群环境下实时应用系统的安全调度-太原科技大学主站

时间 :2019-09-12 15:34:35

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Abstract: An increasing number of real-time parallel applications on clusters, such as aircraft control and medical electronics systems, require high quality of security to assure confidentiality, authenticity, and integrity of information. Conventional scheduling algorithms for clusters have been proposed to achieve high performance of parallel applications without security requirements; howev...


Abstract: An increasing number of real-time parallel applications on clusters, such as aircraft control and medical electronics systems, require high quality of security to assure confidentiality, authenticity, and integrity of information. Conventional scheduling algorithms for clusters have been proposed to achieve high performance of parallel applications without security requirements; however, enhancing security of clusters for parallel applications requiring service flexibility remains a challenging problem. In this talk, we will focus on scheduling mechanisms and algorithms for applications with timing and security constraints on clusters. In particular, we will first articulate an adaptive control framework for quality of security in cluster computing systems. The framework is centered on a model of security-sensitive real-time applications and security overhead model. The overhead model is incorporated to measure security overheads incurred by an array of security services, including encryption, authentication, integrity check, and the like. Next, we will shed light on a dynamic real-time scheduling algorithm, or TAPADS (Task Allocation for Parallel Applications with Deadline and Security constraints), which seamlessly integrates security requirements into real-time scheduling for clusters. To quantitatively evaluate the performance TAPADS, we conducted extensive experiments driven by real world applications and traces as well as synthetic benchmarks. We will present experimental results to demonstratively show that TAPADS significantly improves system performance in terms of quality of security and schedulability over the three existing scheduling algorithms.

 

Biosketch:

秦啸,1974年生,男,博士,湖北武汉人,美国奥本大学计算机科学与软件工程系教授,计算机系研究生部主任。2011年被太原科技大学聘为教授,山西省“百人计划”引进人才。主要研究领域:数据密集型计算、并行与分布式计算,高密度数据存储等。在ACM/IEEE汇刊等国际顶级学术期刊上发表学术论文40多篇,以及近百余篇国际学术会议论文;主持承担美国国家自然科学基金项目5项,合作参与了美国国家自然科学基金项目5项;担任了40多次的国际学术会议程序委员会主席和程序委员会委员;2009年获美国国家科学基金会杰出青年奖,2010年度获美国奥本大学青年教授研究成就奖;指导博士研究生22人,硕士研究生13人,其中:指导的博士研究生获得2010年度、2015年度、2018年度奥本大学优秀博士论文奖。

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