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学者姓名：李小燕
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Diagnosability is an important parameter to measure the fault tolerance of a multiprocessor system. If we only care about the state of a node, instead of doing the global diagnosis, Hsu and Tan proposed the idea of local diagnosis. Chiang and Tan provided an extended star structure to diagnose a node under comparison model. In this work, we evaluate the local diagnosability better by proposing a tree structure around this node. We provide the corresponding algorithm to diagnose the node. Simulation results are presented for different failure probability of a node in the tree and different percentage of faulty nodes in the tree, showing the performance of our algorithm. © 2024 Institute of Information Science. All rights reserved.
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| GB/T 7714 | Chen, Meirun , Li, Xiao-Yan , Lin, Cheng-Kuan et al. A New Tree Structure for Local Diagnosis [J]. | Journal of Information Science and Engineering , 2024 , 40 (2) : 231-244 . |
| MLA | Chen, Meirun et al. "A New Tree Structure for Local Diagnosis" . | Journal of Information Science and Engineering 40 . 2 (2024) : 231-244 . |
| APA | Chen, Meirun , Li, Xiao-Yan , Lin, Cheng-Kuan , Pai, Kung-Jui . A New Tree Structure for Local Diagnosis . | Journal of Information Science and Engineering , 2024 , 40 (2) , 231-244 . |
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Modern large-scale computing systems always demand better connectivity indicators for reliability evaluation. However, as more processing units have been rapidly incorporated into emerging computing systems, existing indicators (e.g., l-component edge connectivity and l-extra edge connectivity) have gradually failed to provide the required fault tolerance. In addition, these indicators require, for example, that the faulty network should have at least l components (or that each component should have at least l nodes). These fault assumptions are not flexible enough to deal with diversified structural demands in practice circumstances. In order to address these challenges simultaneously, this article proposes two novel indicators for network reliability by utilizing the partition matroid technique, named matroidal connectivity and conditional matroidal connectivity. We first investigate the accurate values of (conditional) matroidal connectivity of k-ary n-cube Q(n)(k), which is an appealing option as the underlying topology for modern parallel computing systems. Moreover, we propose an O(k(n-1)) algorithm for determining structural features of minimum edge sets whose cardinality is the conditional matroidal connectivity of Q(n)(k). Simulation results are presented to verify our algorithm's correctness and further investigate the distribution pattern of edge sets subject to the restriction of partition matroid. We also present comparative analyses illustrating the superior edge fault tolerance of our findings in relation to prior research, which even exhibits an exponential enhancement when k >= 4.
Keyword ：
conditional matroidal connectivity conditional matroidal connectivity fault tolerance fault tolerance k-ary k-ary matroidal connectivity matroidal connectivity n-cubes n-cubes network reliability network reliability
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| GB/T 7714 | Zhuang, Hongbin , Li, Xiao-Yan , Lin, Cheng-Kuan et al. Novel Reliability Indicators From the Perspective of Data Center Networks [J]. | IEEE TRANSACTIONS ON RELIABILITY , 2024 . |
| MLA | Zhuang, Hongbin et al. "Novel Reliability Indicators From the Perspective of Data Center Networks" . | IEEE TRANSACTIONS ON RELIABILITY (2024) . |
| APA | Zhuang, Hongbin , Li, Xiao-Yan , Lin, Cheng-Kuan , Liu, Ximeng , Jia, Xiaohua . Novel Reliability Indicators From the Perspective of Data Center Networks . | IEEE TRANSACTIONS ON RELIABILITY , 2024 . |
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Star networks play an essential role in designing parallel and distributed systems. With the massive growth of faulty edges and the widespread applications of the longest paths and cycles, it is crucial to embed the longest fault-free paths and cycles in edge-faulty networks. However, the traditional fault model allows a concentrated distribution of faulty edges and thus can only tolerate faults that depend on the minimum degree of the network vertices. This paper introduces an improved fault model called the partitioned fault model, which is an emerging assessment model for fault tolerance. Based on this model, we first explore the longest fault-free paths and cycles by proving the edge fault-tolerant Hamiltonian laceability, edge fault-tolerant strongly Hamiltonian laceability, and edge fault-tolerant Hamiltonicity in the $n$-dimensional star network $Sn$. Furthermore, based on the theoretical proof, we give an $O(nN)$ algorithm to construct the longest fault-free paths in star networks based on the partitioned fault model, where $N$ is the number of vertices in $Sn$. We also make comparisons to show that our result of edge fault tolerance has exponentially improved other known results. IEEE
Keyword ：
Bipartite graph Bipartite graph Computational modeling Computational modeling emerging assessment model emerging assessment model fault tolerance fault tolerance Fault tolerance Fault tolerance Fault tolerant systems Fault tolerant systems Hypercubes Hypercubes large-scale missing edges large-scale missing edges longest paths longest paths Program processors Program processors Star networks Star networks Stars Stars
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| GB/T 7714 | Li, X. , Chang, J. . LP-Star : Embedding Longest Paths into Star Networks with Large-Scale Missing Edges under an Emerging Assessment Model [J]. | IEEE Transactions on Emerging Topics in Computing , 2024 : 1-15 . |
| MLA | Li, X. et al. "LP-Star : Embedding Longest Paths into Star Networks with Large-Scale Missing Edges under an Emerging Assessment Model" . | IEEE Transactions on Emerging Topics in Computing (2024) : 1-15 . |
| APA | Li, X. , Chang, J. . LP-Star : Embedding Longest Paths into Star Networks with Large-Scale Missing Edges under an Emerging Assessment Model . | IEEE Transactions on Emerging Topics in Computing , 2024 , 1-15 . |
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云计算与物联网安全课程是信息安全专业本科生的必修课,培养学生运用所学的云计算与物联网技术分析和解决问题.本教学创新成果报告围绕3个课堂教学真实问题:一是学生多学科交叉基础知识不足;二是学生解决实际问题和实践能力不足;三是存在产学落差,学生所学技术无法符合产业需求.并且分别提出3个教学方案解决对应的课堂教学真实问题:一是开发"AI助教"APP,以增强现实(AR)和人工智能(AI)语音问答协助学生的学习过程,结合创新性;二是引入心率带、脑波仪、机器人等设备,强化学生的自主学习动机和学习习惯,培养学生解决问题的思维能力,提升高阶性;三是结合"码云"分享开源代码,由企业下载和评价,增加挑战度.
Keyword ：
人工智能 人工智能 信息教育 信息教育 物联网 物联网
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| GB/T 7714 | 吴伶 , 李小燕 , 陈志华 et al. 人工智能与增强现实应用于本科教育 [J]. | 科学咨询 , 2024 , (4) : 131-134 . |
| MLA | 吴伶 et al. "人工智能与增强现实应用于本科教育" . | 科学咨询 4 (2024) : 131-134 . |
| APA | 吴伶 , 李小燕 , 陈志华 , 钟展良 . 人工智能与增强现实应用于本科教育 . | 科学咨询 , 2024 , (4) , 131-134 . |
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Fault detection and localization are vital for ensuring the stability of data center networks (DCNs). Specifically, adaptive fault diagnosis is deemed a fundamental technology in achieving the fault tolerance of systems. The highly scalable data center network (HSDC) is a promising structure of server-centric DCNs, as it exhibits the capacity for incremental scalability, coupled with the assurance of low cost and energy consumption, low diameter, and high bisection width. In this paper, we first determine that both the connectivity and diagnosability of the m-dimensional complete HSDC, denoted by HSDCm(m), are m. Further, we propose an efficient adaptive fault diagnosis algorithm to diagnose an HSDCm(m) within three test rounds, and at most N+4m(m-2) tests with m >= 3 (resp. at most nine tests with m=2), where N=m center dot 2m is the total number of nodes in HSDCm(m). Our experimental outcomes demonstrate that this diagnosis scheme of HSDC can achieve complete diagnosis and significantly reduce the number of required tests.
Keyword ：
adaptive diagnosis adaptive diagnosis cycle decomposition cycle decomposition data center networks data center networks diagnosability diagnosability hamiltonian hamiltonian
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| GB/T 7714 | Lin, Wanling , Li, Xiao-Yan , Chang, Jou-Ming et al. An Improved Fault Diagnosis Algorithm for Highly Scalable Data Center Networks [J]. | MATHEMATICS , 2024 , 12 (4) . |
| MLA | Lin, Wanling et al. "An Improved Fault Diagnosis Algorithm for Highly Scalable Data Center Networks" . | MATHEMATICS 12 . 4 (2024) . |
| APA | Lin, Wanling , Li, Xiao-Yan , Chang, Jou-Ming , Wang, Xiangke . An Improved Fault Diagnosis Algorithm for Highly Scalable Data Center Networks . | MATHEMATICS , 2024 , 12 (4) . |
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Blockchain-based healthcare IoT technology research enhances security for smart healthcare services such as real-time monitoring and remote disease diagnosis. To incentivize positive behavior among participants within a blockchain-based smart healthcare system, existing efforts employ benefit distribution and reputation assessment methods to enhance performance. Yet, there remains a significant gap in multidimensional assessment strategies and consensus improvements in addressing complex healthcare scenarios. In this paper, we propose a blockchain and trusted reputation assessment-based incentive mechanism for healthcare services (BtRaI). BtRaI provides a realistic and comprehensive reputation assessment with feedback to motivate blockchain consensus node participation, thus effectively defending against malicious behavior in the healthcare service system. Specifically, BtRaI first introduces multiple moderation factors for comprehensive multidimensional reputation assessment and credibly records the assessment results on the blockchain. Then, we propose an improved PBFT algorithm, grounded in the reputation assessment, to augment blockchain consensus efficiency. Finally, BtRaI designs a token-based reward and punishment mechanism to motivate honest participation in the blockchain, inhibit potential misbehavior, and promote enhanced service quality in the healthcare system. Theoretical analysis and simulation experiments conducted across various scenarios demonstrate that BtRaI effectively suppresses malicious attacks in healthcare services, improves blockchain node fault tolerance rates, and achieves blockchain transaction processing efficiency within 0.5 s in a 100-node consortium chain. BtRaI's reputation assessment and token incentive mechanism, characterized by realistic differentiation granularity and change curves, are well-suited for dynamic and complex healthcare service environments.
Keyword ：
Blockchain Blockchain Consensus mechanism Consensus mechanism Healthcare Internet of Things Healthcare Internet of Things Incentive mechanism Incentive mechanism PBFT algorithm PBFT algorithm Reputation assessment Reputation assessment
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| GB/T 7714 | Liu, Yanhua , Liu, Zhihuang , Zhang, Qiu et al. Blockchain and trusted reputation assessment-based incentive mechanism for healthcare services [J]. | FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE , 2024 , 154 : 59-71 . |
| MLA | Liu, Yanhua et al. "Blockchain and trusted reputation assessment-based incentive mechanism for healthcare services" . | FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 154 (2024) : 59-71 . |
| APA | Liu, Yanhua , Liu, Zhihuang , Zhang, Qiu , Su, Jinshu , Cai, Zhiping , Li, Xiaoyan . Blockchain and trusted reputation assessment-based incentive mechanism for healthcare services . | FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE , 2024 , 154 , 59-71 . |
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Abstract ：
Diagnosability is an important parameter to measure the fault tolerance of a multiprocessor system. If we only care about the state of a node, instead of doing the global diagnosis, Hsu and Tan proposed the idea of local diagnosis. Chiang and Tan provided an extended star structure to diagnose a node under comparison model. In this work, we evaluate the local diagnosability better by proposing a tree structure around this node. We provide the corresponding algorithm to diagnose the node. Simulation results are presented for different failure probability of a node in the tree and different percentage of faulty nodes in the tree, showing the performance of our algorithm.
Keyword ：
comparison model comparison model diagnosis algorithm diagnosis algorithm fault diagnosis fault diagnosis local diagnosability local diagnosability tree tree
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| GB/T 7714 | Chen, Meirun , Li, Xiao-Yan , Lin, Cheng-Kuan et al. A New Tree Structure for Local Diagnosis [J]. | JOURNAL OF INFORMATION SCIENCE AND ENGINEERING , 2024 , 40 (2) : 231-244 . |
| MLA | Chen, Meirun et al. "A New Tree Structure for Local Diagnosis" . | JOURNAL OF INFORMATION SCIENCE AND ENGINEERING 40 . 2 (2024) : 231-244 . |
| APA | Chen, Meirun , Li, Xiao-Yan , Lin, Cheng-Kuan , Pai, Kung-Jui . A New Tree Structure for Local Diagnosis . | JOURNAL OF INFORMATION SCIENCE AND ENGINEERING , 2024 , 40 (2) , 231-244 . |
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The kary n-cube Q(n)(k) serves as an indispensable interconnection network in the design of data center networks, network-on-chips, and parallel computing systems since it possesses numerous attractive properties. In these parallel architectures, the paired (or unpaired) many-to-many m-disjoint path cover (m-DPC) plays a significant role in message transmission. Nevertheless, the construction of m-DPC is severely obstructed by large-scale edge faults due to the rapid growth of the system scale. In this paper, we investigate the existence of paired 2-DPC in Q(n)(k) under the partitioned edge fault (PEF) model, which is a novel fault model for enhancing the networks' fault-tolerance related to path embedding problem. We exploit this model to evaluate the edge fault-tolerance of Q(n)(k) when a paired 2-DPC is embedded into Q(n)(k). Compared to the other known works, our results can help Q(n)(k) to achieve large-scale edge fault-tolerance.
Keyword ：
Fault-tolerant embedding Fault-tolerant embedding Interconnection networks Interconnection networks k-ary n-cubes k-ary n-cubes Paired 2-disjoint path cover Paired 2-disjoint path cover PEF model PEF model
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| GB/T 7714 | Zhuang, Hongbin , Li, Xiao-Yan , Chang, Jou-Ming et al. Paired 2-disjoint path covers of k-ary n-cubes under the partitioned edge fault model [J]. | JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING , 2024 , 190 . |
| MLA | Zhuang, Hongbin et al. "Paired 2-disjoint path covers of k-ary n-cubes under the partitioned edge fault model" . | JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING 190 (2024) . |
| APA | Zhuang, Hongbin , Li, Xiao-Yan , Chang, Jou-Ming , Liu, Ximeng . Paired 2-disjoint path covers of k-ary n-cubes under the partitioned edge fault model . | JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING , 2024 , 190 . |
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In the realm of multiprocessor systems, the evaluation of interconnection network reliability holds utmost significance, both in terms of design and maintenance. The intricate nature of these systems calls for a systematic assessment of reliability metrics, among which, two metrics emerge as vital: connectivity and diagnosability. The R-g-conditional connectivity is the minimum number of processors whose deletion will disconnect the multiprocessor system and every processor has at least g fault-free neighbors. The R-g-conditional diagnosability is a novel generalized conditional diagnosability, which is the maximum number of faulty processors that can be identified under the condition that every processor has no less than g fault-free neighbors. In this paper, we first investigate the R-g-conditional connectivity of generalized exchanged X-cubes GEX(s , t) and present the lower (upper) bounds of the R-g-conditional diagnosability of GEX(s , t) under the PMC model. Applying our results, the R-g-conditional connectivity and the lower (upper) bounds of R-g-conditional diagnosability of generalized exchanged hypercubes, generalized exchanged crossed cubes, and locally generalized exchanged twisted cubes under the PMC model are determined. Our comparative analysis highlights the superiority of R-g-conditional diagnosability, showcasing its effectiveness in guiding reliability studies across a diverse set of networks.
Keyword ：
Fault tolerance Fault tolerance Generalized exchanged X-cubes Generalized exchanged X-cubes PMC model PMC model Reliability Reliability R-g-conditional restriction R-g-conditional restriction
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| GB/T 7714 | Lin, Wanling , Zhuang, Hongbin , Li, Xiao-Yan et al. Reliability evaluation of generalized exchanged X-cubes under the Rg-conditional restriction [J]. | JOURNAL OF SUPERCOMPUTING , 2024 , 80 (8) : 11401-11430 . |
| MLA | Lin, Wanling et al. "Reliability evaluation of generalized exchanged X-cubes under the Rg-conditional restriction" . | JOURNAL OF SUPERCOMPUTING 80 . 8 (2024) : 11401-11430 . |
| APA | Lin, Wanling , Zhuang, Hongbin , Li, Xiao-Yan , Zhang, Yufang . Reliability evaluation of generalized exchanged X-cubes under the Rg-conditional restriction . | JOURNAL OF SUPERCOMPUTING , 2024 , 80 (8) , 11401-11430 . |
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The Hamiltonian path/cycle serves as a robust tool for transmitting messages within parallel and distributed systems. However, the prevalent device -intensive nature of these systems often leads to the occurrence of faults. Tackling the critical challenge of tolerating numerous faults when constructing Hamiltonian paths and cycles in these systems is of utmost significance. The alternating group graph AG n is a suitable interconnection network for building parallel and distributed systems due to its outstanding topological properties. Many studies have been dedicated to the fault -tolerant embedding of Hamiltonian paths and cycles in AG n , but they all fail to reach the desired level of fault -tolerance. In this paper, we aim to enhance the edge fault -tolerant embedding capability of AG n by leveraging a newly emerged fault model, called the Partitioned Edge Fault (PEF) model. We prove the existence of Hamiltonian paths/cycles tolerating large-scale edge faults in AG n under the PEF model. Additionally, we propose a fault -tolerant Hamiltonian path embedding algorithm for AG n under the PEF model and validate its effectiveness through experiments. To gauge the significance of each missed edge, we conduct experimental calculations for the average path length of every edge along the Hamiltonian path produced by the proposed embedding algorithm. Furthermore, the fault -tolerance comparison and experimental analysis reveal that our results improve the fault -tolerant embedding capability of AG n from a linear level to an exponential one. To our knowledge, this is the first time that a Hamiltonian path/cycle embedding approach is proposed and actually implemented for AG n with large-scale edge faults.
Keyword ：
Alternating group graphs Alternating group graphs Embedding Embedding Fault-tolerance Fault-tolerance Interconnection networks Interconnection networks Partitioned edge faults Partitioned edge faults
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| GB/T 7714 | Zhuang, Hongbin , Li, Xiao-Yan , Wang, Dajin et al. Enabling high fault-tolerant embedding capability of alternating group graphs [J]. | FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE , 2024 , 158 : 110-121 . |
| MLA | Zhuang, Hongbin et al. "Enabling high fault-tolerant embedding capability of alternating group graphs" . | FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 158 (2024) : 110-121 . |
| APA | Zhuang, Hongbin , Li, Xiao-Yan , Wang, Dajin , Lin, Cheng-Kuan , Zhao, Kun . Enabling high fault-tolerant embedding capability of alternating group graphs . | FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE , 2024 , 158 , 110-121 . |
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