With the rapid development of Internet technology,the issues of network asset detection and vulnerability warning have become hot topics of concern in the industry.However,most existing detection tools operate in a si...With the rapid development of Internet technology,the issues of network asset detection and vulnerability warning have become hot topics of concern in the industry.However,most existing detection tools operate in a single-node mode and cannot parallelly process large-scale tasks,which cannot meet the current needs of the industry.To address the above issues,this paper proposes a distributed network asset detection and vulnerability warning platform(Dis-NDVW)based on distributed systems and multiple detection tools.Specifically,this paper proposes a distributed message sub-scription and publication system based on Zookeeper and Kafka,which endows Dis-NDVW with the ability to parallelly process large-scale tasks.Meanwhile,Dis-NDVW combines the RangeAssignor,RoundRobinAssignor,and StickyAssignor algorithms to achieve load balancing of task nodes in a distributed detection cluster.In terms of a large-scale task processing strategy,this paper proposes a task partitioning method based on First-In-First-Out(FIFO)queue.This method realizes the parallel operation of task producers and task consumers by dividing pending tasks into different queues according to task types.To ensure the data reliability of the task cluster,Dis-NDVW provides a redundant storage strategy for master-slave partition replicas.In terms of distributed storage,Dis-NDVW utilizes a distributed elastic storage service based on ElasticSearch to achieve distributed storage and efficient retrieval of big data.Experimental verification shows that Dis-NDVW can better meet the basic requirements of ultra-large-scale detection tasks.展开更多
In the field of statistical mechanics and system science, it is acknowledged that the financial crisis has a profound influence on stock market. However, the influence of total asset of enterprise on stock quote was n...In the field of statistical mechanics and system science, it is acknowledged that the financial crisis has a profound influence on stock market. However, the influence of total asset of enterprise on stock quote was not considered in the previous studies. In this work, a modified cross-correlation matrix that focuses on the influence of total asset on stock quote is introduced into the analysis of the stocks collected from Asian and American stock markets, which is different from the previous studies. The key results are obtained as follows. Firstly, stock is more greatly correlated with big asset than with small asset. Secondly, the higher the correlation coefficient among stocks, the larger the eigenvector is. Thirdly, in different periods, like the pre-subprime crisis period and the peak of subprime crisis period, Asian stock quotes show that the component of the third eigenvector of the cross-correlation matrix decreases with the asset of the enterprise decreasing.Fourthly, by simulating the threshold network, the small network constructed by 10 stocks with large assets can show the large network state constructed by 30 stocks. In this research we intend to fully explain the physical mechanism for understanding the historical correlation between stocks and provide risk control strategies in the future.展开更多
Using the classification results by the fuzzy clustering models as the basis for choosing the choosing patterns, a feed forward networks model for classification is given. Remarkable success was achieved in training t...Using the classification results by the fuzzy clustering models as the basis for choosing the choosing patterns, a feed forward networks model for classification is given. Remarkable success was achieved in training the networks to learn the patterns and in classifying the coal reserve assets. The results show that the neural network approach for classification has some advantages such as stability and reliability.展开更多
Today, we observe that more and more, radio frequency identification (RFID) technology has been used to identify and track objects in enterprises and institutions. In addition, we also perceive the growing adoption of...Today, we observe that more and more, radio frequency identification (RFID) technology has been used to identify and track objects in enterprises and institutions. In addition, we also perceive the growing adoption of cloud computing, either public or private, to process and store data from the objects. In this context, the literature does not present an initiative that looks into the network on enterprise-cloud interactions, so neglecting network performance and congestion information when transmitting data to the cloud. Thus, we are presenting a model named ACMA—Automatic Control and Management of Assets. ACMA employs context awareness to control and monitor corporate assets in companies with multiple units. ACMA provides a centralized point of access in the cloud in which interested actors can get online data about each corporate asset. In particular, our scientific contribution consists in considering network congestion to control dynamically the data updating interval from sensors to the cloud. The idea is to search for reliability and integrity of operations, without losing or corrupting data when updating the information to cloud. Thus, this article describes the ACMA model, its architecture, algorithms and features. In addition, we describe the evaluation methodology and the results obtained through experiments and simulations based on the developed prototype.展开更多
World energy consumption increased by 56 percent, from 524 quadrillion Btu in 2010 to 820 quadrillion Btu in 2040. The increased demand in energy consumption is fulfilled by different renewable and non-renewable sourc...World energy consumption increased by 56 percent, from 524 quadrillion Btu in 2010 to 820 quadrillion Btu in 2040. The increased demand in energy consumption is fulfilled by different renewable and non-renewable sources such as petroleum, natural gas, electricity, nuclear etc. Natural gas is one of the most important sources of energy. SNGPL has been managing a 94,263 km long gas pipelines network covering approximately the northern part of Pakistan. In this paper we have presented the use of condition based maintenance (CBM) management techniques with a?geographical information system (GIS) for asset management of a gas distribution network of?SNGPL. The continuous monitoring and updating of asset data reveal where the assets are located and which needs maintenance or which lies in critical condition. The system helps to save time and reduce visits to the sites and labour reduction.展开更多
基金supported by the Fundamental Research Funds for the Central Universities(Grant No.HIT.NSRIF.201714)Weihai Science and TechnologyDevelopment Program(2016DX GJMS15)+1 种基金Weihai Scientific Research and Innovation Fund(2020)Key Research and Development Program in Shandong Provincial(2017GGX90103).
文摘With the rapid development of Internet technology,the issues of network asset detection and vulnerability warning have become hot topics of concern in the industry.However,most existing detection tools operate in a single-node mode and cannot parallelly process large-scale tasks,which cannot meet the current needs of the industry.To address the above issues,this paper proposes a distributed network asset detection and vulnerability warning platform(Dis-NDVW)based on distributed systems and multiple detection tools.Specifically,this paper proposes a distributed message sub-scription and publication system based on Zookeeper and Kafka,which endows Dis-NDVW with the ability to parallelly process large-scale tasks.Meanwhile,Dis-NDVW combines the RangeAssignor,RoundRobinAssignor,and StickyAssignor algorithms to achieve load balancing of task nodes in a distributed detection cluster.In terms of a large-scale task processing strategy,this paper proposes a task partitioning method based on First-In-First-Out(FIFO)queue.This method realizes the parallel operation of task producers and task consumers by dividing pending tasks into different queues according to task types.To ensure the data reliability of the task cluster,Dis-NDVW provides a redundant storage strategy for master-slave partition replicas.In terms of distributed storage,Dis-NDVW utilizes a distributed elastic storage service based on ElasticSearch to achieve distributed storage and efficient retrieval of big data.Experimental verification shows that Dis-NDVW can better meet the basic requirements of ultra-large-scale detection tasks.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.11705042 and 71874172)the China Postdoctoral Science Foundation(Grant Nos.2018T110040 and 2016M590041)+2 种基金the Fundamental Research Funds for Central Universities,China(Grant No.JZ2018HGTB0238)Curriculum Planning and Design Research Project,China(Grant No.102-033119)the Teaching Quality and Teaching Reform Project,China(Grant No.JYQZ1815)
文摘In the field of statistical mechanics and system science, it is acknowledged that the financial crisis has a profound influence on stock market. However, the influence of total asset of enterprise on stock quote was not considered in the previous studies. In this work, a modified cross-correlation matrix that focuses on the influence of total asset on stock quote is introduced into the analysis of the stocks collected from Asian and American stock markets, which is different from the previous studies. The key results are obtained as follows. Firstly, stock is more greatly correlated with big asset than with small asset. Secondly, the higher the correlation coefficient among stocks, the larger the eigenvector is. Thirdly, in different periods, like the pre-subprime crisis period and the peak of subprime crisis period, Asian stock quotes show that the component of the third eigenvector of the cross-correlation matrix decreases with the asset of the enterprise decreasing.Fourthly, by simulating the threshold network, the small network constructed by 10 stocks with large assets can show the large network state constructed by 30 stocks. In this research we intend to fully explain the physical mechanism for understanding the historical correlation between stocks and provide risk control strategies in the future.
文摘Using the classification results by the fuzzy clustering models as the basis for choosing the choosing patterns, a feed forward networks model for classification is given. Remarkable success was achieved in training the networks to learn the patterns and in classifying the coal reserve assets. The results show that the neural network approach for classification has some advantages such as stability and reliability.
文摘Today, we observe that more and more, radio frequency identification (RFID) technology has been used to identify and track objects in enterprises and institutions. In addition, we also perceive the growing adoption of cloud computing, either public or private, to process and store data from the objects. In this context, the literature does not present an initiative that looks into the network on enterprise-cloud interactions, so neglecting network performance and congestion information when transmitting data to the cloud. Thus, we are presenting a model named ACMA—Automatic Control and Management of Assets. ACMA employs context awareness to control and monitor corporate assets in companies with multiple units. ACMA provides a centralized point of access in the cloud in which interested actors can get online data about each corporate asset. In particular, our scientific contribution consists in considering network congestion to control dynamically the data updating interval from sensors to the cloud. The idea is to search for reliability and integrity of operations, without losing or corrupting data when updating the information to cloud. Thus, this article describes the ACMA model, its architecture, algorithms and features. In addition, we describe the evaluation methodology and the results obtained through experiments and simulations based on the developed prototype.
文摘World energy consumption increased by 56 percent, from 524 quadrillion Btu in 2010 to 820 quadrillion Btu in 2040. The increased demand in energy consumption is fulfilled by different renewable and non-renewable sources such as petroleum, natural gas, electricity, nuclear etc. Natural gas is one of the most important sources of energy. SNGPL has been managing a 94,263 km long gas pipelines network covering approximately the northern part of Pakistan. In this paper we have presented the use of condition based maintenance (CBM) management techniques with a?geographical information system (GIS) for asset management of a gas distribution network of?SNGPL. The continuous monitoring and updating of asset data reveal where the assets are located and which needs maintenance or which lies in critical condition. The system helps to save time and reduce visits to the sites and labour reduction.
