This article highlights some recent research advances on trusted computing in China,focusing mainly on the methodologies and technologies related to trusted computing module,trusted computing platform,trusted network ...
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This article highlights some recent research advances on trusted computing in China,focusing mainly on the methodologies and technologies related to trusted computing module,trusted computing platform,trusted network connection,trusted storage,and trustworthy software.
As an important aspect of the hardware resource consolidation in virtualization environment, memory consolidation and over-commitment has been motivated by the increasing elastic computing cloud platform. The most pop...
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Open Source Forge (OSF) websites provide information on massive open source software projects, extracting these web data is important for open source research. Traditional extraction methods use string matching among ...
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Wireless sensor networks (WSN) is a critical technology for information gathering covering many areas, including health-care, transportation, air traffic control and environment monitoring. Despite wide use, the fast ...
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Nowadays open source software has become an indispensable basis for both individual and industrial software engineering. Various kinds of labeling mechanisms like categories and tags are used in open source communitie...
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ISBN:
(纸本)9781450315609
Nowadays open source software has become an indispensable basis for both individual and industrial software engineering. Various kinds of labeling mechanisms like categories and tags are used in open source communities to annotate projects and facilitate the discovery of certain software However as large amounts of software are attached with no/few labels or the existing labels are from different ontology space, it is still hard to retrieve potentially topic-relevant software. This paper highlights the valuable semantic information of project descriptions and labels, proposes labeled software topic detection LSTD a hybrid approach combining topic models and ranking mechanisms to detect and enrich the topics of software by mining the large amount of textual software profiles, which can be employed to do software categorization and tag recommendation. LSTD makes use of labeled LDA to capture the semantic correlations between labels and descriptions and then construct the label-based topic-word matrix. Based on the generated matrix and the generality of labels, LSTD designs a simple yet eficient algorithm to detect the latent topics of software that expressed as relevant and popular labels. Comprehensive evaluations are conducted on the large-scale datasets of representative open source communities and the results validate the effectiveness of LSTD.
Efficient designs for intra-session network coding based practical applications largely rely on a better understanding on its queueing behaviors. However, few work devote on this topics. In this paper, we build a mult...
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Soft errors caused by energetic particle strikes in on-chip cache memories have become a critical challenge for microprocessor design. Architectural vulnerability factor (AVF), which is defined as the probability that...
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Soft errors caused by energetic particle strikes in on-chip cache memories have become a critical challenge for microprocessor design. Architectural vulnerability factor (AVF), which is defined as the probability that a transient fault in the structure would result in a visible error in the final output of a program, has been widely employed for accurate soft error rate estimation. Recent studies have found that designing soft error protection techniques with the awareness of AVF is greatly helpful to achieve a tradeoff between performance and reliability for several structures (i.e., issue queue, reorder buffer). Considering large on-chip L2 cache, redundancy-based protection techniques (such as ECC) have been widely employed for L2 cache data integrity with high costs. Protecting caches without accurate knowledge of the vulnerability characteristics may lead to the over-protection, thus incurring high overheads. Therefore, designing AVF-aware protection techniques would be attractive for designers to achieve a cost-efficient protection for caches, especially at early design stage. In this paper, we propose an improved AVF estimation framework for conducing comprehensive characterization of dynamic behavior and predictability of L2 cache vulnerability. We propose to employ Bayesian Additive Regression Trees (BART) method to accurately model the variation of L2 cache AVF and to quantitatively explain the important effects of several key performance metrics on L2 cache AVF. Then we employ bump hunting technique to extract some simple selecting rules based on several key performance metrics for a simplified and fast estimation of L2 cache AVF. Using the simplified L2 cache AVF estimator, we develop an AVF-aware ECC technique as an example to demonstrate the cost-efficient advantages of the AVF prediction based dynamic fault tolerant techniques. Experimental results show that compared with traditional full ECC technique, AVF-aware ECC technique reduces the L2 cache acc
Code clone is a prevalent activity during the development of softwares. However, it may be harmful to the maintenance and evolution of softwares. Current techniques for detecting code clones are most syntax-based, and...
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In this paper, we apply tree-structured conditional random field (TCRF) to all-words word sense disambiguation (WSD), where the graphical structure of TCRF is the dependency syntax tree produced by Minipar. The extrem...
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Cyber-Physical Systems (CPS) involve deep interactions between computation cores, communication networks, and physical environments. These systems are inherently complex and highly nondeterministic. This makes the tra...
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