Network Situation Research Articles

A path characteristics based adaptive subflow switching algorithm for dynamic heterogeneous MPTCP network

Multipath Transmission Control Protocol (MPTCP) can support simultaneous transmission of data packets over multiple paths, improve transmission reliability and aggregate network bandwidth to improve throughput. However, MPTCP cannot adjust the access state of subflows in real time according to the actual situation in the dynamic network, resulting in poor performance under the limitation of limited buffers. The existing path management algorithms, such as Fullmesh and PCDC, only select the subflows for concurrent transmission at the beginning, and cannot dynamically manage the subflow during the transmission. Therefore, we propose a path characteristics based adaptive subflow switching management (PASS) algorithm to manage multiple paths of MPTCP in real time and dynamically manage whether a subflow joins the transmission or not. Experimental results show that PASS is more stable and flexible than traditional Fullmesh algorithm and PCDC algorithm, and can obtain higher network throughput.

When Does Competitive Learning Occur? The Impact of Alliance Network Embeddedness on Technological Invasion

AbstractFirms participate in an alliance network to collaborate for specific goals and common values; however, the network situation and the interaction between partnering firms enable them to appropriate their partners’ proprietary knowledge and adopt competitive actions. Little is known about whether and when the focal firm would invade its partner's technological domains in alliance networks. We examined how relational embeddedness and positional embeddedness influence the focal firm's technological invasion behaviour against its partner, and the moderating role of relative alliance experience. Although previous studies have emphasized that a central position would enhance firms’ competitive aggression, we argue that this central position imposes more constraints on firms’ competitive behaviour. The empirical results show a U‐shaped relationship between relational embeddedness and technological invasion, while relative centrality negatively affects technological invasion behaviour and negatively moderates the U‐shaped relationship. Furthermore, the results indicate that relative alliance experience attenuates the U‐shaped relationship between relational embeddedness and technological invasion, while it enhances the negative effect of relative centrality on technological invasion. These findings provide new insights and perspectives to study the coopetition phenomenon in alliance networks.

Study on the rare waterbird habitat networks of a new UNESCO World Natural Heritage site based on scenario simulation

As a newly established World Natural Heritage site, the conservation of rare waterbird habitats in the Yancheng coastal wetlands has attracted wide international attention. In view of the importance of this area in international biodiversity conservation and waterbird habitat conservation, the study of the current situation of rare waterbird habitat networks with spatial isolation features of great demonstration significance to improve the habitat conservation quality of the heritage site. Based on the data obtained from habitat suitability assessments of rare waterbirds, this paper used complex network theory, ecological stepping-stone theory and circuit models to analyze the current status and robustness of rare waterbird habitat networks in the Yancheng coastal wetlands. The results showed that the stepping stones of the red-crowned cranes and the Oriental storks were mainly distributed around important habitat areas, including aquaculture ponds and reed marshes, with areas of 1275.68 hm2 and 1247.74 hm2, respectively, while the stepping stones of Saunders's gulls were mainly distributed within the Tiaozini habitat site, with an area of 1180.76 hm2. The stability and connectivity of the habitat networks of red-crowned cranes and Oriental storks in the northern habitat area were better. At the Tiaozini habitat site, there was spatial isolation and low connectivity among the habitats and stepping stones of Saunders's gulls. In the optimal protection scenario, the stability and connectivity of the habitat network structure of red-crowned cranes and Oriental storks were the best, and the networks tended to exhibit assortativity. In the random destruction scenario, the connectivity of the habitat networks of Saunders's gulls was the lowest, and the network structure was the most fragile. Finally, the optimization and restoration patterns of habitat network based on improving the support capacity of important habitat nodes and the enhancement of the stability and connectivity of the stepping-stone networks were proposed.

The Magical Santayanan Groundwork for Metaphysical Coherentism

The Magical Santayanan Groundwork for Metaphysical Coherentism

Risk Aversion of B2C Cross-Border e-Commerce Supply Chain

In recent years, with the booming development of the B2C cross-border e-commerce industry, the supply chain of B2C cross-border e-commerce faces many potential risk factors, which must be prevented. To solve this problem, this paper studies the supply chain risk factors of B2C cross-border e-commerce and puts forward avoidance strategies. First, the fitness network model of a dual local world is constructed by combining the fitness model with the local world model. Then, the fitness network model of the dual local world is verified by the risk dynamics simulation model to fit the actual network situation. On this basis, the SIRS virus transmission model is constructed to simulate the risk transmission of the B2C cross-border e-commerce supply chain, and the evaluation index system of the supply chain risk immunity ability and external risk intensity are established according to the supply chain risk immunity ability and external risk intensity. AHP is used to calculate the factors that have the greatest influence on supply chain risk immunity and external risk intensity. The results show that: from the point of view of the enterprise’s own risk immunity, it is more necessary to ensure the stability of the company’s capital and to establish a perfect risk monitoring and coping mechanism to avoid risks. From the perspective of enterprise external risk intensity, the risk should be avoided from two aspects of transaction security and logistics.

A BIPMU-based network security situation assessment method for wireless network

With the rapid development of information technology, wireless network has been accepted by the public and widely used in the daily life and work. Especially with the comprehensive deployment of 5G network technology, the application scope of wireless network is continuously increasing, which can greatly reduce the IT infrastructure overhead and human resource investment. Although the tremendous advantages, wireless network inevitably suffers from some severe security challenges. For example, the network data is characterized by large volumes, variety and high dimensions, which would greatly affect the efficiency and accuracy of network security situation assessment (NSSA). To solve this problem, we first design a novel model based on parsimonious memory unit (PMU), namely, bidirectional parsimonious memory unit (BIPMU). Compared with PMU, BIPMU can not only learn and characterize data through its time series relationship, but also comprehensively and effectively manage the potential connection of long-term and short-term dependence on time series data. Subsequently, we adopt BIPMU to design a novel NSSA method to evaluate the real-time security situation of wireless network. Finally, we develop a prototype implementation of our proposed NSSA method and provide the performance evaluation. The experimental results demonstrate that compared with the previous NSSA methods, our proposed NSSA method is much more attractive in efficiency and accuracy.

Application of Key Technologies of College English Online Teaching Platform in Deep Learning

With the rapid development of information technology, the network has become a part of the daily life of current college students. The use of network tools to develop college English teaching platform is necessary and beneficial. Various versions of online English teaching platforms have been developed in China and used by many Chinese universities. Through research and analysis, according to the theory of communicative learning, this paper puts forward the design plan of English university teaching platform for Chinese colleges and universities. The article first summarizes the research origin and importance of the college English online teaching platform. It then outlines the current situation of college English online teaching platforms and provides a demonstration of a specific platform for a specific teaching network. This article discusses the research on deep learning using advanced technology on college English teaching platforms. Through questionnaires, group discussions, in-depth interviews, classroom observations, and other research methods, we can understand the current situation of school computer networks from a macro perspective. It integrates foreign language courses and the problems teachers and students encounter in the process. The results show that 56% of the students said that this method can promote their own learning, and 12% of the students think that there will be no good learning effect. For this new test method, 86% of the teachers think that it can achieve a certain learning effect, which is a good similar to an adaptive test method.

Situation awareness method of the distribution network based on EMD-SVD and Elman neural network

In order to ensure reliability and security of power supply, the situation awareness of some elements in the distribution network is studied in this paper. Considering the influence of the interference signal, Empirical Mode Decomposition (EMD) is introduced to reduce it. Subsequently, according to operation characteristics of the actual distribution network, several evaluation indexes are proposed to describe the operation situation of the overall distribution network and internal elements, especially evaluation of fragile nodes. Based on these indexes and characteristics of actual distribution network, the comprehensive evaluation method of fragile nodes (CEMFN) is constructed, which mainly aims at the fragile nodes in the distribution network and synthesizes the single index coefficient to realize the identification of fragile nodes. Through the simulation calculation, it can be seen that the result of CEMFN is more accurate than that of the traditional evaluation model, which provides an important theoretical support for the operation and maintenance of distribution network and reliable power supply.

Application of network security situational awareness in power information system security

The increasingly complex network environment leads to more and more intense network attacks. Traditional firewall and intrusion detection technology cannot guarantee the network security of power information system, so network space situation awareness becomes the most important in the field of network security. Big data technology can be used to better understand the operation of the network, and different types of data for rapid analysis. Build a security situation awareness system framework that integrates data collection, data processing, data storage, data analysis and data presentation to filter out harmful data and ensure network security. In this paper, the basic concept and system framework of network security situational awareness are briefly introduced. Firstly, Flume and Kafka are used to obtain log or network attack information, and MapReduce and Storm technologies are used for batch or real-time analysis to achieve the perception of network security. Then, the analytic hierarchy process (AHP) is used to determine the index weight, extract the characteristics of the network situation, and complete the evaluation of the network security situation by analyzing and constructing the decision matrix. The system has the characteristics of high availability, scalability and easy deployment, which can better support the perception and prediction of various network security threats.

Social Networks and Support to Older People in Refugee Situation in Western Countries

Background: Forced migration of humans as a result of conflict continues to be a global problem. Many of the refugees displaced and made vulnerable by conflict induced forced migration are older adults. These older adults may lose their social networks and support as a result of the conflicts leading to migration and be unable to recreate them, making them more vulnerable. This review aims to describe the social network and support situation of older adults in refugee situation as presented in global literature.
 Methods/Design: The five steps of Arksey and O’Malley’s (2005) framework to search multiple databases from inception till June 2021 will be followed. MeSH terms and keywords, e.g., “older refugees”, “refugees”, and “social network”, “social support”, will be adopted for the following databases: SocINDEX, PsychINFO, Social Work Abstracts, Sociology Abstracts, Social Services Abstracts, Web of Science and/or Scopus, Canadian electronic library. Citations will be screened (title/abstract and full text) using predefined inclusion and exclusion criteria. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) will be used to describe the process of data inclusion and exclusion.
 Discussion: This review will reveal gaps in the provision of social support to older refugees and inform policy development for the improvement of support to older refugees.

Enhanced Reliable Communication Using Direct-Trust-Based GPSR Protocol in VANETs

Vehicular Ad-hoc Network (VANET) is becoming a potential solution to improve traffic safety and efficiency by facilitating communication among vehicles via exchanging reliable messages. Therefore, reliable and authentic message delivery from legitimate vehicles is a prerequisite. But internal malicious vehicles may disrupt proper functioning by discarding or fabricating packets. For this objective, a computationally efficient direct trust-based model is proposed which evaluate vehicle behavior by verifying the correctness of communicated message even in sparse network situation. We ensure the reliability of each communicated message by secure path selection in Direct-trust-based GPSR routing protocol (DT-GPSR) incorporating trustworthy vehicle. Simulation and analyses show our model help legitimate vehicles to mitigate effect of malicious vehicle communicating false or bogus data to disrupt network.

Comparative Study on Characteristics of Urban Road Network in Station Catchment Area between China and Other Countries for Station-City Integration

The urban road network is one of the most important factors affecting urban traffic operation in station catchment areas, as well as the main factor in station-city integration. China’s high-speed railway has developed rapidly, and station catchment areas encompassed by station-city integration have emerged as city planning and urban design aims. However, the differences in urban road network characteristics in the station catchment area between China and other countries have not been adequately researched yet. Considering 20 station catchment areas encompassed by the station-city integration as examples, this study analyzes the intersection quantity and network density in station catchment areas to compare the characteristics of urban road networks in China with those in Europe, North America, and Japan. Combined with the square block model calculation, we found the following. (1) The network density in non-China cases is concentrated in 16–22 km/km2. The Honkong West Kowloon Station and Shapingba Station approach this range, while the Shanghai Hongqiao Station and Hangzhou East Station feature considerably lower values than this range. (2) The intersection quantity in non-China cases is concentrated in 225 pcs/km2. Except for that of the Honkong West Kowloon Station, the values for the Shapingba Station, Shanghai Hongqiao Station, and Hangzhou West Station are lower than this range. (3) Developing small-scale blocks by gridding has an optimal effect on station catchment areas within the side-length range of 47.1–97.5 m. (4) The current situation of the entire urban road network and the specifications for the design codes of the road network exhibit a certain correlation with the road network characteristics of the station catchment areas.

Quantitative Method for Security Situation of the Power Information Network Based on the Evolutionary Neural Network

Cybersecurity is the security cornerstone of digital transformation of the power grid and construction of new power systems. The traditional network security situation quantification method only analyzes from the perspective of network performance, ignoring the impact of various power application services on the security situation, so the quantification results cannot fully reflect the power information network risk state. This study proposes a method for quantifying security situation of the power information network based on the evolutionary neural network. First, the security posture system architecture is designed by analyzing the business characteristics of power information network applications. Second, combining the importance of power application business, the spatial element index system of coupled interconnection is established from three dimensions of network reliability, threat, and vulnerability. Then, the BP neural network optimized by the genetic evolutionary algorithm is incorporated into the element index calculation process, and the quantitative model of security posture of the power information network based on the evolutionary neural network is constructed. Finally, a simulation experiment environment is built according to a power sector network topology, and the effectiveness and robustness of the method proposed in the study are verified.

Strategic Directions: Evaluation of Village Development Strategies in the Case of Applicants for the Hungarian Village Renewal Award

Village roles have changed significantly in Central Europe over the last century and a half. In our article, we mainly deal with the conditions in Hungary. Based on the relevant literature, we follow the changing role, problems and presence of Hungarian villages. Our research focuses on evaluating village development strategies; thus, an essential part of the article is the presentation of the European and Hungarian village renewal movement, as the 50 settlements examined are also part of the settlements launched at the Hungarian Village Renewal Award competition. In this research, the 50 settlements were divided into three groups according to their role in the settlement network. The settlement group analysed their development priorities by summarizing the Hungarian Village Renewal Award applications. As a result, it was found that the development directions of the villages belonging to the individual settlement groups can be well separated from each other. The choice of the settlement development strategy is greatly influenced by the distance from the central settlements and the settlement network situation. We compared our results with the analysis of the strategies of some foreign villages (located in the former socialist bloc) and then examined the Hungarian village surveys of the last century and a half, focusing on land use changes and their role in development. As a result of the analysis, it became clear that the importance of land use in the life of villages in the initial period decreased spectacularly over time and was replaced by employment and the role of the settlement network. The main result of our research is that we have proven that the strategic priorities of village development can be grouped based on the position of the villages in the settlement network, and the priorities are mainly determined by the size of the central settlement and the distance from it.

Identifying Suitable Solid Waste Landfill Sites Using Spatial Multi-Criteria Decision Analysis

The required skill sets for dealing with solid waste management are lacking in developing countries. Further, this issue is compounded by the rapid growth of waste generation in those countries. This study helps to address this problem by performing a landfill site selection for the Twin Cities of Pakistan. The study uses a multi-criteria decision model for siting a suitable landfill utilizing Geographic Information Systems (GIS). The use of geospatial technology provides network-based spatial analysis and assists in modeling practical network situations. In particular, this analysis accounts for proximity to urban/residential areas, road networks, water streams, and water reservoirs/lakes. It also accounts for land slope and land use/land cover. The results indicate that 96.3% of the Twin Cities area is unsuitable, 1.6% is moderately suitable, and 2.1% is most suitable. The results of the study identify appropriate sites for more detailed analysis based on current and future land use, population growth, and waste generation. As similar challenges of handling solid waste are common in developing countries, this study can serve as a guide in other developing countries.

Research on data mining method of network security situation awareness based on cloud computing

Abstract Due to the complexity and versatility of network security alarm data, a cloud-based network security data extraction method is proposed to address the inability to effectively understand the network security situation. The information properties of the situation are generated by creating a set of spatial characteristics classification of network security knowledge, which is then used to analyze and optimize the processing of hybrid network security situation information using cloud computing technology and co-filtering technology. Knowledge and information about the security situation of a hybrid network has been analyzed using cloud computing strategy. The simulation results show that a cyber security crash occurs in window 20, after which the protection index drops to window 500. The increase in the security index of 500 windows is consistent with the effectiveness of the concept of this document method, indicating that this document method can sense changes in the network security situation. Starting from the first attacked window, the defense index began to decrease. In order to simulate the added network defense, the network security events in the 295th time window were reduced in the original data, and the defense index increased significantly in the corresponding time period, which is consistent with the method perception results, which further verifies the effectiveness and reliability of this method on the network security event perception. This method provides high-precision knowledge of network security situations and improves the security and stability of cloud-based networks.

TiSEFE: Time Series Evolving Fuzzy Engine for Network Traffic Classification

Monitoring and analyzing network traffic are very crucial in discriminating the malicious attack. As the network traffic is becoming big, heterogeneous, and very fast, traffic analysis could be considered as big data analytic task. Recent research in big data analytic filed has produces several novel large-scale data processing systems. However, there is a need for a comprehensive data processing system to extract valuable insights from network traffic big data and learn the normal and attack network situations. This paper proposes a novel evolving fuzzy system to discriminate anomalies by inspecting the network traffic. After capturing traffic data, the system analyzes it to establish a model of normal network situation. The normal situation is a time series data of an ordered sequence of traffic information variable values at equally spaced time intervals. The performance has been analyzed by carrying out several experiments on real-world traffic dataset and under extreme difficult situation of high-speed networks. The results have proved the appropriateness of time series evolving fuzzy engine for network classification.

Multimedia Security Situation Prediction Based on Optimization of Radial Basis Function Neural Network Algorithm.

Aiming at the problem of prediction accuracy in network situation awareness, a network security situation prediction method based on a generalized radial basis function (RBF) neural network is proposed. This method uses the K-means clustering algorithm to determine the data center and expansion function of the RBF and uses the least-mean-square algorithm to adjust the weights to obtain the nonlinear mapping relationship between the situation value before and after the situation and carry out the situation prediction. Simulation experiments show that this method can obtain situation prediction results more accurately and improve the active security protection of network security. Compared with the PSO-RBF model, AFSA-RBF model, and IAFSA-RBF model, the maximum relative error and minimum relative error of the IAFSA-PSO-RBF model are reduced by 14.27%, 8.91%, and 32.98%, respectively, and the minimum relative error is reduced by 1.69%, 12.97%, and 0.61%, respectively. This shows that the IAFSA-PSO-RBF model has reduced the prediction error interval, and the average relative error is 5%. Compared with the other three models, the accuracy rate is improved by more than 5%, and it has met the requirements for the prediction of the network security situation.

An experimental study to recognize and mitigate the malevolent attack in wireless sensors networks

The Wireless Sensor Network (WSN)is applied in several networking situations. It suffers from dissimilar types of attack because of its meagre security mechanisms. The Sinkhole attack is the most destructive attack of WSN. A Reliable Self Reconfiguration (RSR) mechanism has been suggested in this work to eliminate the malicious sinkhole attack from the network. The proposed reliable reconfiguration (RSR)) system consists of two steps. The malicious node is detected and after detection it is corrected without resource loss by using the reconfiguration mechanism. In this paper, the reconfiguration mechanism for correcting sinkhole attack is applied using the C++ built simulator and factors such as Packet Delivery ratio and energy consumption are obtained for estimation The differences in the energy level have been calculated for the three scenarios i.e., Network without attack, Network with sinkhole attack and Network after Reconfiguration. The proposed Reliable Self-Reconfiguration (RSR) method outperforms the various detection mechanisms in finding and eliminating the sinkhole attack.

A network security situation assessment model based on BP neural network optimized by D-S evidence theory

Abstract Traditional networks rely heavily on the distribution of expert experience when assessing complex network security situations, resulting in low assessment accuracy, which has been unable to adapt to the current network security needs of the big data era, and has unavoidable problems such as low efficiency and poor flexibility. In response to these problems, this paper proposes a network security situation assessment method based on D-S evidence theory to optimize neural networks. First establish the CS-BP neural network model, enhance the local search ability of the cuckoo algorithm through conjugate gradient calculation, and then introduce it into the BP neural network to improve the training convergence speed and overcome the local minimum problem; finally, in order to reduce the basic probability distribution (BPA) subjective impact, using DS evidence theory to optimize the CS-BP neural network, determine the degree of impact of each attack, and evaluate the value of the network security situation. The experimental results show that the network situation assessment model of CS-BP neural network optimized based on D-S evidence theory can effectively assess the network security situation in the environment of trusted equipment.