A hierarchical peer-to-peer（P2P）model and a data fusion method for network security situation awareness system are proposed to improve the efficiency of distributed security behavior monitoring network.The single po...A hierarchical peer-to-peer（P2P）model and a data fusion method for network security situation awareness system are proposed to improve the efficiency of distributed security behavior monitoring network.The single point failure of data analysis nodes is avoided by this P2P model,in which a greedy data forwarding method based on node priority and link delay is devised to promote the efficiency of data analysis nodes.And the data fusion method based on repulsive theory-Dumpster/Shafer（PSORT-DS）is used to deal with the challenge of multi-source alarm information.This data fusion method debases the false alarm rate.Compared with improved Dumpster/Shafer（DS）theoretical method based on particle swarm optimization（PSO）and classical DS evidence theoretical method,the proposed model reduces false alarm rate by 3%and 7%,respectively,whereas their detection rate increases by 4%and 16%,respectively.展开更多
In Cognitive radio ad hoc networks （CRAHNs）, the secondary users （SUs） or cognitive radio nodes （CRs） are always equipped with limited energy and have a high error probability of data transmission. To address th...In Cognitive radio ad hoc networks （CRAHNs）, the secondary users （SUs） or cognitive radio nodes （CRs） are always equipped with limited energy and have a high error probability of data transmission. To address this issue, we first describe the network utility under energy constraint as a max-min model, where the re-transmission strategy with network coding is employed. Additionally, the expression of retransmission probability is presented in terms of power and bit error rate （BER）. Moreover, since the max-min model is non-convex in both objective and constraints, we use a normal- form game to find a near-optimal solution. The simulation results show that the proposed approach could achieve a higher network utility than the compared approaches.展开更多
In order to achieve failure prediction without manual intervention for distributed systems, a novel failure feature analysis and extraction approach to automate failure prediction is proposed. Compared with the tradit...In order to achieve failure prediction without manual intervention for distributed systems, a novel failure feature analysis and extraction approach to automate failure prediction is proposed. Compared with the traditional methods which focus on building heuristic rules or models, the autonomic prediction approach analyzes the nonlinear correlation of failure features by recognizing failure patterns. Failure data are sorted according to the nonlinear correlation and failure signature is proposed for autonomic prediction. In addition, the Manifold Learning algorithm named supervised locally linear embedding is applied to achieve feature extraction. Based on the runtime monitoring of failure metrics, the experimental results indicate that the proposed method has better performance in terms of both correlation recognition precision and feature extraction quality and thus it can be used to design efficient autonomic failure prediction for distributed systems.展开更多
The World Art Museum of China Millennium Monument is aimed at collecting,studying and exhibiting treasures of world civilizations and arts.As an innovative type of museum,it was established in 2006 and has since then ...The World Art Museum of China Millennium Monument is aimed at collecting,studying and exhibiting treasures of world civilizations and arts.As an innovative type of museum,it was established in 2006 and has since then reached out extensively in international cultural exchanges,not only promoting its own development,but also facilitating China’s展开更多
基金Supported by the National Natural Science Foundation of China(61370212)the Research Fund for the Doctoral Program of Higher Education of China(20122304130002)+1 种基金the Natural Science Foundation of Heilongjiang Province(ZD 201102)the Fundamental Research Fund for the Central Universities(HEUCFZ1213,HEUCF100601)
文摘A hierarchical peer-to-peer（P2P）model and a data fusion method for network security situation awareness system are proposed to improve the efficiency of distributed security behavior monitoring network.The single point failure of data analysis nodes is avoided by this P2P model,in which a greedy data forwarding method based on node priority and link delay is devised to promote the efficiency of data analysis nodes.And the data fusion method based on repulsive theory-Dumpster/Shafer（PSORT-DS）is used to deal with the challenge of multi-source alarm information.This data fusion method debases the false alarm rate.Compared with improved Dumpster/Shafer（DS）theoretical method based on particle swarm optimization（PSO）and classical DS evidence theoretical method,the proposed model reduces false alarm rate by 3%and 7%,respectively,whereas their detection rate increases by 4%and 16%,respectively.
基金This work was supported in part by the Research Fund for the Doctoral Program of Higher Education of China under Grant 20122304130002,the Natural Science Foundation in China under Grant 61370212,the Fundamental Research Fund for the Central Universities under Grant HEUCFZ1213 and HEUCF100601
文摘In Cognitive radio ad hoc networks （CRAHNs）, the secondary users （SUs） or cognitive radio nodes （CRs） are always equipped with limited energy and have a high error probability of data transmission. To address this issue, we first describe the network utility under energy constraint as a max-min model, where the re-transmission strategy with network coding is employed. Additionally, the expression of retransmission probability is presented in terms of power and bit error rate （BER）. Moreover, since the max-min model is non-convex in both objective and constraints, we use a normal- form game to find a near-optimal solution. The simulation results show that the proposed approach could achieve a higher network utility than the compared approaches.
基金Supported by the National High Technology Research and Development Programme of China （ No. 2007AA01Z401 ） and the National Natural Science Foundation of China （No. 90718003, 60973027）.
文摘In order to achieve failure prediction without manual intervention for distributed systems, a novel failure feature analysis and extraction approach to automate failure prediction is proposed. Compared with the traditional methods which focus on building heuristic rules or models, the autonomic prediction approach analyzes the nonlinear correlation of failure features by recognizing failure patterns. Failure data are sorted according to the nonlinear correlation and failure signature is proposed for autonomic prediction. In addition, the Manifold Learning algorithm named supervised locally linear embedding is applied to achieve feature extraction. Based on the runtime monitoring of failure metrics, the experimental results indicate that the proposed method has better performance in terms of both correlation recognition precision and feature extraction quality and thus it can be used to design efficient autonomic failure prediction for distributed systems.
文摘The World Art Museum of China Millennium Monument is aimed at collecting,studying and exhibiting treasures of world civilizations and arts.As an innovative type of museum,it was established in 2006 and has since then reached out extensively in international cultural exchanges,not only promoting its own development,but also facilitating China’s
