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In this paper, snake optimization algorithm (SOA) is used to find the optimal gains of an enhanced controller for controlling congestion problem in computer networks. M-file and Simulink platform is adopted to evaluate the response of the active queue management (AQM) system, a comparison with two classical controllers is done, all tuned gains of controllers are obtained using SOA method and the fitness function chose to monitor the system performance is the integral time absolute error (ITAE). Transient analysis and robust analysis is used to show the proposed controller performance, two robustness tests are applied to the AQM system, one is done by varying the size of queue value in different period and the other test is done by changing the number of transmission control protocol (TCP) sessions with a value of ± 20% from its original value. The simulation results reflect a stable and robust behavior and best performance is appeared clearly to achieve the desired queue size without any noise or any transmission problems. [ABSTRACT FROM AUTHOR]

With the invention of modern network technologies in recent decades, the exponential growth in wireless devices and their ease in wireless connectivity, network traffic is significantly increasing. Unluckily, this ease of connectivity is increasing the risk of network intrusion and exploitation of information. This vulnerability also provides opportunities for attackers to perform malicious activities, resulting in serious security threats such as DDoS, DoS, Brute Force, SQL Injection, Malware, and Phishing attack, thus creating the demand for an effective network intrusion detection system. The traditional approaches for identifying the attacks performed by an intruder are mostly packet analysis-based and thus cannot achieve good performance. Unluckily, inspection of a packet is not possible in the case of a high-speed and encrypted packet. Additionally, a packet is a small chunk of information as compared to flow thereby, extracting the nature (attack) of traffic for which a packet is being used is constrained. Considering the power of information processing in the human brain's visual cortex, we propose a cortex-inspired ensemble-based network intrusion detection system (CI-EnsID) capable of detecting attacks or intrusions in a network flow. The proposed system consists of a multilayer feed-forward network that processes the information like an ensemble classification in addition to its cortex-like information processing. Moreover, the proposed system hybridizes contemporary unsupervised and supervised learning techniques. This system is to be installed in a cascade to analyze the network flow to identify malicious traffic resulting from network intruders. To evaluate the proposed system, it was tested on standard and publicly available KDDCup99 and CICIDS2017 datasets. The experimental results show that the proposed CI-EnsID outperforms the Naive Bayes, artificial neural network, logistic regression, decision tree, and random forest-based contemporary classification techniques. [ABSTRACT FROM AUTHOR]

Middleboxes are widely used in modern networks for a variety of network functions in cybersecurity, performance enhancement, and monitoring. Middlebox policy enforcement is however complex and tedious with unreliable manual re-configuration of legacy routers. The existing solution on automated policy enforcement relies on software-defined networking and does not apply to the traditional non-SDN networks, which remain popular today in enterprise deployment and core networks. This paper proposes a new architecture based entirely on software-defined middleboxes (instead of using software-defined switches in the prior art) to enable dependable and automated policy enforcement in non-SDN networks whose routers forward packets based on traditional routing protocols that are not policy-sensitive. We present a hot-potato enforcement strategy, which is then enhanced with two optimizations for load-balanced policy enforcement among software-defined middleboxes. Next, we propose two additional optimizations that minimize total traffic and aggregate end-to-end delays subject to link capacity constraints. Further enhancements are made to relieve middlebox processing overhead, avoid packet fragmentation due to policy enforcement, recover from failures, and mitigate delay for time-sensitive applications. We evaluate the proposed architecture on a real-life campus network topology and two simulated topologies to demonstrate the superior performance of our load-balanced enforcement strategies. [ABSTRACT FROM AUTHOR]

Software defined networking (SDN) has been proposed as an effective approach to improve network management efficiency and increase network intelligence in various networks. However, configuring and deploying suitable SDN functionalities is challenging. To overcome these obstacles in SDN network deployment, machine learning models have been introduced to monitor and predict the quality of service (QoS) in an SDN-enabled network. However, most existing studies are applicable only to deployed SDN networks with specific network topologies. In this study, a prediction-based SDN network configuration and deployment scheme is proposed for unseen network topologies before the actual deployment of SDN functionalities. In addition, a machine learning-based pre-deployment SDN performance prediction problem is formulated, and a neural network boosting regression model (i.e., NNBoost) is proposed as the solution. Numerical experiments demonstrate that NNBoost outperforms other machine learning algorithms, including deep learning methods, proposed in the literature, on datasets generated with both real-world and synthetic network topologies, compared with random forest (RF), AdaBoost, XGBoost, LightGBM, deep neural network (DNN) and long short-term memory (LSTM). It is found that NNBoost achieves lower root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE) results for the maximum and mean values for the Round-Trip Time (RTT), Switch-to-Controller (S2C) traffic, and Controller-to-Controller (C2C) traffic. It is also found that by adding extra training data samples generated with synthetic network topologies, NNBoost achieves a better prediction performance on the test data samples for real-world network topologies. • A prediction-based SDN network configuration and deployment scheme is defined. • A ML-based pre-deployment SDN performance prediction problem is well-formulated. • A neural network boosting regression model is proposed as the solution. [ABSTRACT FROM AUTHOR]

The paper is devoted to analysis of modern directions of innovation-investment formation of intelligent computer networks that control the fast-moving technological processes of electricity supply. It is based on the conclusion that the problem of increasing the productivity of information exchange between information resources and consumers is dominant. A method for increasing the efficiency of information exchange is proposed as a search for the rational location of a new node and the organization of such a set of its connections among the whole set of nodes of the computer network, which provides a minimum average topological distance. Mathematical models of effective topological organization of connections in computer network of power consumption control at the level of traction substations, electric power distances and the railway in general are proposed. [ABSTRACT FROM AUTHOR]

With the rapid development of network data communication technology, the complexity of the network environment makes the data in the data stream have uncertain characteristics, and a large number of data streams are generated in many fields. Therefore, it is necessary to find an efficient and accurate processing method to process a large amount of data in a computer network. This paper takes the skyline probability calculation and the actual efficiency of the unknown object index structure in the skyline query processing technology on the uncertain data stream as the research object. Based on the skyline query technology, we study an efficient skyline query processing method on the unknown network traffic based on the model SUMG. The method includes two algorithms: dynamic modeling algorithm DMG and skyline query algorithm GST. The DMG algorithm samples the data in the sliding window of the uncertain data stream and establishes a model to convert the data stream into the parameter stream in the uncertain object probability density function, the GST algorithm establishes the R-tree index structure, which is in order to reduce the amount of calculation, it uses the parameter flow of the model. In both methods, the set of local skyline results is first obtained at the distributed node, and the skyline query is performed again on the union of the local skyline results to obtain the global skyline result set. The experimental results show that compared with the skyline query method BNL for unknown network traffic without an index structure, the SUMG method can not only effectively model the link-type unknown object to assist the skyline query, but also effectively prune the uncertain data object and improve the skyline. The distributed skyline query method can cope with the skyline query task on the distributed data stream. [ABSTRACT FROM AUTHOR]

The congestion of the network increases exponentially due to continuous growth of the Internet. TCP is a protocol of Transport layer which deals with the congestion of the network. TCP has many variants to deal with different types of congestion problems. Congestion of the network depends on many factors like transfer of packet size, type of cross traffic, number of competing connections,the load on every link in the path, router buffer size and bottleneck queue size. This paper presents a new congestion detection method which is based on bottleneck queue size. It is estimated according to variation of round-trip time. The experimental results confirm that the proposed TCP provide better results for throughput and packet drops. [ABSTRACT FROM AUTHOR]

The propagation of malicious codes such as worms have been characterized using compartmental epidemic models which are mostly mathematical equations. Aside the challenge of identifying the type of virus or worm represented by these compartmental models, we noticed that the representation of internet protocol (IP) address space is absent. Therefore, this study evaluates the impact of the IPV4 address space using the following epidemic models; SAIR, SEIR, SEI-V, SEIQR and Q-SEIR. By our modifications, the implication is that these models now characterize the scan-based worms that probe the address space in order to find and attack vulnerable computers. To the best of our knowledge, this is the first study that evaluates the impact of this IP addressing format on epidemic computer network models. Numerical simulations with the Runge-Kutta order 4 and 5 method are used to illustrate several existent variations with the models without IPV4 address space. Results are time histories and 3 dimensional phase plots of the models, and from them it was discovered that the standard incidence cancels the effect of adding the expression of IPV4 address scanning space for the worms. More so, characteristically temporal variations were also noted for the susceptible compartment of these models. [ABSTRACT FROM AUTHOR]

Lab work activities are one of the hearts of science learning, but several students have limited use and time to explore computer network tools. This study proposes a virtual reality (VR) application used to support lab work activities of a computer network so that students may conduct lab work activities by themselves at any time. The method used in this study is a multimedia development life cycle (MDLC) that consists of five stages, they are concept, design, material collecting, assembly, and testing & evaluation. A formative evaluation carried out by involving two experts, namely software expert and material expert, to measure the feasibility of application before conducting user testing. Meanwhile, a summative evaluation used to evaluate the VR application by involving 25 students who were taking the course of computer networking. Statistical analysis shows that the score of Cronbach's alpha test is higher than 0.6 for aspects of material subject and experience. Hence, the VR application can be used to support the lab work activities of a computer network. [ABSTRACT FROM AUTHOR]

Introduction: From 2005 to 2009, the Scientific and Technical Branch Program "Cuban Network of Science" was developed under the auspices of the Cuban Ministry of Science, Technology and Environment, which obtained outstanding results and a national and international impact. Then more than 10 years after its design, it became necessary to develop a new version in correspondence with the current state of ICT and its services. With the purpose of modernizing and completing the Cuban Network of Science as a digital network of contents, products and services of Science, Technology and Environment, the project "Modernization of the Cuban Network of Science" was developed. Objective: to approach the main results of the project, their correspondence with the objectives that were set and ways to achieve them. Material and methods: the techniques and methods used, the historical - logical, the systemic approach, the focus group and force field techniques, the interviews, the scientific observation, the literature review, the expert opinion and the Iadov technique stand out. Results and discussion: the commissioning of a modernized technological infrastructure of the network with higher levels of access and connectivity, a general portal of the Cuban Network of Science 2.0 web version, a system of selection, acquisition, processing, organization and updating of the contents, as well as the creation of experimental facilities for cloud computing. Conclusions: the project contributed to improving integration with other networks and services with shared and personalized use in a more efficient way. [ABSTRACT FROM AUTHOR]

With the rapid development of the Internet, the use of computer networks is becoming more and more frequent. However, in the process of network use, various vulnerabilities and some other factors lead to network security problems occur from time to time. How to make the network provide efficient and rapid services for people and also meet different levels of security issues has become a problem. Based on this, the use of artificial intelligence technology has been studied, and the system detection algorithm based on the concept of artificial intelligence has been proposed. Integrating artificial intelligence into the field of network security can not only improve the overall performance of the network, but also effectively and reliably guarantee the security. Firstly, according to the characteristics of computer network system, an immune detection algorithm is proposed to evaluate the security of the system. Secondly, based on the analysis of computer network security technology, a system detection algorithm based on artificial intelligence concept is further proposed. Then, data mining is carried out based on Prefix, and the intrusion lines and their correlation are analyzed. Finally, the effectiveness of the algorithm is analyzed experimentally. The results show that the proposed algorithm has good accuracy and adaptability, and can play a good supporting role in the security detection of computer network system. [ABSTRACT FROM AUTHOR]

To provide broadband access services to customers, which resides residential and enterprise field, Worldwide Interoperability for Microwave Access (WiMAX) is one of the famous wireless technologies. WiMAX can provide high-speed data rate with large-scale coverage such that it contains a high transmission range as well as it supports high mobility with a large number of nodes. It requires scheduling algorithm in the MAC layer of its protocol stack because the number of users that want service is high in number. One of the most used scheduling algorithms is the Earliest Deadline First (EDF) but it contains certain performance limitations. As well as there is a need for security before allocation of bandwidth to the users because WiMAX is a wireless technology and may be vulnerable to lots of security attacks and if once the bandwidth is allocated to any malicious user, then the system of WiMAX communication will be under dangerous attacks. In this paper, we proposed a secure heuristic earliest deadline first uplink scheduler in the MAC layer of the WiMAX with some authorization procedures. The proposed scheme protects the allocation of bandwidth to any malicious node such that the system will be prevented from security attacks like Denial of Service (DoS), flooding attack, etc., as well as it will use heuristic approach for scheduling. Therefore, it can efficiently schedule user's request and provide fairness to the WiMAX system and we called as Secure Heuristic EDF Uplink Scheduler (SH-EDF). The performance of SH-EDF uplink scheduler will be evaluated in the provisions of various performance metrics. [ABSTRACT FROM AUTHOR]

In this paper, the simulation model of computer network security evaluation based on neural network is proposed. Network security has now become one of the focuses of computer communication researchers. Due to the suddenness and human nature of network security problems, it is often difficult to detect problems after they appear. Combined with the characteristics of network security situation prediction problem, the computer network security evaluation model is constructed by BP neural network algorithm, and the network system security detection algorithm is used to evaluate it, to predict the network security posture. Therefore, the defense can be implemented in advance, and the network security belt can be reduced. The resulting hazards will provide constructive advice on the future development of cybersecurity. Through test simulation, the algorithm can be well applied in the simulation model system; it is worth further promotion in practice. [ABSTRACT FROM AUTHOR]

• Artificial intelligence and deep learning have good prospects in computer network security. • Improving computer network security detection rate. • Reducing false positives in computer network security. With the continuous progress of the information age and science and technology, how to combine complex and changeable data with self-protection ability has become an urgent problem that needs to be solved. In the computer system, the traditional technology for protection is somewhat passive. To this end, this paper analyzes computer network security monitoring under artificial intelligence (AI) deep learning technology and discusses its development trend, which monitors network security to find and address problems in time. The results show that the deep learning technology of computer network security detection can improve its security performance with high safety performance, high detection rate, and low false alarm rate. It can monitor the vulnerabilities in the computer network in time and realize effective security attack detection of the computer network. Deep learning technology for computer network security detection can improve its security performance, timely monitor vulnerabilities in computer networks, and achieve effective security attack detection on computer networks [Display omitted] [ABSTRACT FROM AUTHOR]

The network users need to evaluate the alternative transmission pathways to avoid some routing problems such as possible network attacks, data traffic, etc. in computer networks. In order to provide a mathematical solution to this situation, in this paper the computer network system is considered as a graph, and a random data structure denoted by Bloom filter is used to forward data between computers in the network. The Bloom filter has been used for encoding the routes minimises the query response time, although it has a significant risk of producing errors indicated by false positives (FP). The study aims to assess all paths between two distinct computers on a multi-attribute computer network considering risk and FP values regarding paths. These considerations are inherently vagueness. That being the case, a novel two-stage research methodology is presented to determine the desired pathways during message transmission on a multi-attribute computer network under uncertainty. At this point, the values of the possible risks and the probability of FP of the transmission edges are defined by employing triangular fuzzy numbers to reach the theoretical solutions. The novelty of the study is proposing a research methodology based on fuzzy Multi-Criteria Decision Making (MCDM) techniques to offer alternative routes during data transmission on any multi-attribute computer network under uncertainty for the first time. Further, a sensitivity analysis is implemented. In all computational analyses, the most appropriate and reliable transmission pathways are listed, and some managerial insights and main findings are provided for the network users. • All paths are encoded in a multi-attribute network represented by a graph. • A two-stage research methodology based on fuzzy MCDM approaches is presented. • An extensive computational analysis is performed through a set of scenarios. • In all scenarios, the preference rankings are obtained for alternative paths. • Key findings and managerial insights are provided. [ABSTRACT FROM AUTHOR]

Along with the progress of the society, the computer network has entered the homes of ordinary families, bringing convenience to their life and a profound influence on the economic development of the society. However, there are still problems which need to be solved, especially the route selection. Aiming at solving the convergence speed and optimization ability problems in network route selection, this paper proposes the quantum evolutionary algorithm. It improves it by adjusting the direction of the rotation angle and the function to optimize its performance while preserving the advantages of small scale and strong searching ability. It was found that the improved quantum evolution algorithm has faster search speed and more rigorous pursuit accuracy. It can play a better role in network route selection. [ABSTRACT FROM AUTHOR]

It is noted, that information-technological reserve is a new type of information redundancy, the use of which in distributed automated informational control systems allows to increase the efficiency of their performance while processing the typical user requests. The task of optimal allocation of identical copies of information-technological reserve throughout the nodes of the distributed system is formulated in the form of a minisum problem of finding the p-median of a graph. The algorithm is proposed for solving this problem and the example of the solution is given. The brief analysis of the solution algorithm results is performed. [ABSTRACT FROM AUTHOR]

With the continuous expansion of the application scope of computer network technology, various malicious attacks that exist in the Internet range have caused serious harm to computer users and network resources. This paper attempts to apply artificial intelligence (AI) to computer network technology and research on the application of AI in computing network technology. Designing an intrusion detection model based on improved back propagation (BP) neural network. By studying the attack principle, analyzing the characteristics of the attack method, extracting feature data, establishing feature sets, and using the agent technology as the supporting technology, the simulation experiment is used to prove the improvement effect of the system in terms of false alarm rate, convergence speed, and false negative rate, the rate reached 86.7%. The results show that this fast algorithm reduces the training time of the network, reduces the network size, improves the classification performance, and improves the intrusion detection rate. [ABSTRACT FROM AUTHOR]

The main stages are presented of creating an information-technological data reserve in distributed automated informational control systems. The reserve is formed on the basis of the results of the analysis of subject areas, regular requests to the system and the analysis of the execution sequence of requests processing procedures. The tasks are set of the reserve structure design and of the optimal allocation of reserve copies among computer network nodes. It is noted that this type of reserve allows reducing the processing time of typical, regular requests to the system due to the fact that the reserve contains the data sets, prepared beforehand and later used at requests processing. [ABSTRACT FROM AUTHOR]

Information-centric networking (ICN) is gradually becoming the alternative approach to the traditional Internet architecture through enlightening information (content) distribution on the Internet with content names. The growing rate of Internet traffic has adapted the content-centric architectures to better serve the user requirement of accessing data. Routing disseminates preliminary topology and strategy information as well as long-term changes in them and computes the routing table to coordinate the forwarding procedure. A good routing scheme is essential to reduce delay and to enhance the performance of the network with an efficient searching of the desired content item. In this paper, we present a novel scheme for ICN which evaluates the path for searching the desired content item with an efficient lookup process and we call as Intelligent Routing (IR). Our implement IR scheme utilizes the concept of ternary digital search for making an efficient lookup and evaluates the satisfaction score for making a forwarding decision. The simulation results recommend that IR scheme can reliably accomplish the better performance across other hashing and routing approaches proposed in this field. [ABSTRACT FROM AUTHOR]

The entry of computer network technology into the field of foreign language teaching will of course change the information transmission channel of traditional foreign language teaching, the integration of teaching content and activities, and even the teaching process. It will also make a huge change in the structure of teaching structure and its constituent elements, and promote the change of teaching concepts, leading to changes in the value of teaching and evaluation criteria. This thesis is mainly aimed at exploratory research on the integration of computer network and foreign language teaching in college English teaching reform. The key point is to overcome the problems and confusions faced by foreign language teaching after integration, and to explain the various aspects of integration by applying the applicable theory of foreign language teaching. [ABSTRACT FROM AUTHOR]

Summary: Network operators heavily depend on security services to secure their information technology infrastructures. On the other hand, due to the complexity of security policies, it is not appropriate to straightforwardly use previous pathwise enforcement approaches. In this paper, the enforcement problem of the security policy on middleboxes is formulated as a weighted K set covering problem that requires a policy space analysis tool. This tool is intended to be supported on range‐represented hyperrectangles, which are tagged using a prioritized R‐tree. This methodological work initially evaluates the topological features of diverse types of policies. Hybrid firefly bat algorithm–supported heuristic information shows the inherent difficulties of security policies and provides direction for the design of the enforcement algorithm. At the same time, a scopewise policy enforcement procedure is proposed, which requires a moderate number of enforcement network nodes for organizing the various policy subsets in a greedy manner. Our results demonstrate that the proposed hybrid firefly bat algorithm with policy space analysis offer greatly improved outcomes in terms of the rule overhead, network security, packet delivery ratio, packet loss ratio, and time efficiency above the set operations of the security policy. [ABSTRACT FROM AUTHOR]

Network operators depend on security services with the aim of safeguarding their IT infrastructure. Various types of network security policies are employed on a global scale and are disseminated among several security middleboxes implemented in networks. But, owing to the complications in security policies, it is not quite efficient to directly use the path-wise enforcement schemes that are prevalent. The major motivation of this work is to improve security levels and solve the policy enforcement problem. For the first time, this work reports the issue of policy enforcement on middleboxes. The major contribution of this work is to design security policy enforcement as a Weighted K Set Covering Problem, and we designed a Policy Space Analysis (PSA) tool intended for a group of operations in the security policy. This PSA tool was developed based on range-signified hyper-rectangles, which are indexed by the Hilbert R-tree. Leveraging the PSA, we first investigated the topological features of various kinds of policies. Balancing the PSA tool in a non-dominated sorting particle swarm optimization technique exposes the intrinsic difficulties of this security strategy and provides guidance for designing the enforcement approach. In addition, in this research, a new fuzzy rule-based classification system is introduced for packet classification. A scope-wise policy enforcement algorithm was proposed, which chooses a moderate number of enforcement network nodes for deploying multiple policy subsets in a greedy manner. This scheme is much quicker compared with the first one and therefore has found its application in real-time deployments. [ABSTRACT FROM AUTHOR]

This paper presents a review of three datasets, namely KDD Cup ‘99, NSL-KDD and Kyoto 2006+ datasets, which are widely used in researching intrusion detection in computer networks. The KDD Cup ‘99 dataset consists of five million records, each containing 41 features which can classify malicious attacks into four classes: Probe, DoS, U2R and R2L. The KDD Cup ‘99 dataset cannot reflect real traffic data since it was generated by simulation over a virtual computer network. In the NSL-KDD dataset, redundant and duplicate records form the KDD Cup ‘99 dataset are removed from training and test sets, respectively. The Kyoto 2006+ dataset is built on real three year-network traffic data which are labeled as normal (no attack), attack (known attack) and unknown attack. The Kyoto 2006+ dataset contains 14 statistical features derived from the KDD Cup ‘99 dataset and 10 additional features. [ABSTRACT FROM AUTHOR]

• We examine the performance of computer network by using bipolar complex fuzzy (BCF). • Partition Heronian mean (PHM) operators under BCF are also used for this examination. • To enhance this study different PHM operators are defined. • Based on these defined PHM operators decision making examples are solved. • To show value and authority of the proposed methods comparative study is made. The goal of this paper is to study and assessment of the performance of a computer network with the assistance of partition Heronian mean (PHM) operators in the environment of bipolar complex fuzzy (BCF) information. In today's world computers play a significant role in both professional and personal lives. With the advancement of technology, networking arrived in the space and we continuously advanced from wired network innovation to wireless network innovation. A computer network is a gathering of two or more computer systems that are associated together to share information and resources. It can be considered the base of communication in the area of information technology. Thus, for studying and performance evaluation of a computer network, firstly, this paper contains BCF partition Heronian mean (BCFPHM), BCF weighted partition Heronian mean (BCFWPHM), BCF partition geometric Heronian mean (BCFPGHM), and BCF weighted partition geometric Heronian mean (BCFWPGHM) and their corresponding properties. After that, this paper contains a decision-making (DM) mechanism constructed on the explored operators and a genuine-life example to evaluate the performance of a computer network based on the DM mechanism in the environment of BCF information. The last part of the paper contains the comparison of the explored mechanism of DM and operators with certain current work for exhibiting the capacity and profits of the explored work. [ABSTRACT FROM AUTHOR]

Current networks-aided experiment test program consists of a dozen of independent experiments， thus， as requested，making students complete them one by one mechanically， without helping to develop students ^ practical skills. This paper proposes a newnetwork-aided test program，reforming to conduct all individual experiments within it. The new test program not only satisfies students^experiment needs，but also improves them to solve actual problems. In the paper，the implementation of the new program is illustrated in details， with an aim of shedding new light on the network-aided experiment test programs in colleges [ABSTRACT FROM AUTHOR]

Methods for innovative transformation of railway power supply systems are analyzed. It is shown that modern intelligent power networks represent a new quality of a mutually integrated architecture of a distributed computer environment for the control of power supply and the topology of a traction power network, which are oriented towards the accumulation of new knowledge and optimization of energy resources. To synthesize mathematical models for investigating intelligent systems, a graph of a distributed computer environment is proposed, which adequately reflects the topology of a railway power grid. The paper also proposes a differential mathematical model of a distributed computer environment of intellectualization of procedures for all-mode control of power supply and methods for determining the probabilities of states of nodes, throughput, number of busy channels, and number of failures of requests for service. [ABSTRACT FROM AUTHOR]

Computer networks are usually randomly deployed in locations where there is no underlying network infrastructure. When a computer node is exposed to a malicious attack environment, the nodes are vulnerable to unknown attacks, resulting in misplaced errors. Traditional node detection methods are difficult to operate safely without human participation, and the detection speed is slow. In this paper, a method of boundary malicious node detection based on multivariate classification is proposed. First of all, the background and the objectives are described. Then, the detection method is studied. The experimental results show that this method can quickly identify unknown attack problems, and through the effective detection method to complete the detection of boundary malicious nodes, with fast speed and low false detection rate. [ABSTRACT FROM AUTHOR]

• Circulating of data causes network congestion, which results in packets time delay, loss and butter overflow. • As a solution, an adaptive controller is suggested to achieve robust AQM system using Whale Optimization Algorithm. • The purpose is to enhance the system performance and test its efficiency and superiority. • The results reflect an efficient and robust response. • The obtained results indicate the robust controller behavior and its adaptability to achieve stable system response. The development of the life, increasing the internet users and circulated data on the computer network caused the network congestion. Accordingly, some essential issues arose in terms of packets time delay, packets loss, and buffer overflow in the intermediate routers. In order to tackle those issues, Transmission Control Protocol and Active Queue Management (TCP/AQM) has been introduced. AQM is the main approach used to control congestion and overcome those problems to improve network performance. In this study, an adaptive controller is suggested to achieve robust AQM system based on a smart Whale Optimization Algorithm (WOA) to enhance the system performance, then to test its efficiency and superiority with other controllers a comparison with two classical PI controller is done which indicates that the suggested controller is more desirable performance than other controllers. The simulation of TCP/AQM are carried out using MATLAB (R2020a), simulation results reflect an efficient and robust response in facing different matters may happens during simulation like change model parameters (±20%) or facing disturbance signal, in all types of robustness analysis system need small duration time to return to its desired response, 15 s when changing the no. of sessions and the no. of packets and need 3 s when adding the disturbance signal. The results obtained indicate the robust controller behavior and its adaptability to achieve stable system response. [ABSTRACT FROM AUTHOR]

In today's social development, the level of informatization has been greatly improved. Computer networks are now used in all aspects of society, especially with the popularity of mobile phones and computers. Basically, a mobile phone is a computer that stores all the information of a person, so it is indispensable for carrying out research on computer network security evaluation. The purpose of this article is to examine the growing state of information security threats in computer networks. Neural network technology, which is considered secure, has high flexibility, fast access to information, strong logic, and low failure. Toward creating a low-cost network topology, we used a low-cost network risk assessment method to assess the security of computer networks based on neural networks, and we evaluated existing risks that are appropriate for future computer security research. The results of the study show that neural networks using the Bayesian network method have a significant impact on network security. Considering the problems that can occur with information security risks, computer security systems based on neural networks have a 30% reduction in information error rate compared with traditional methods, and computer network systems based on neural networks have better learning performance to safeguard network security. Improving the security of information requires further research and evaluation of computer network security based on neural networks. [ABSTRACT FROM AUTHOR]

Routing under multiple independent constrains in point-to-point networks has been studied for over 10 years. Its NP-hardness keeps pushing researchers to study approximate algorithms and heuristics, and many results have been published in these years. To the best of our knowledge, the nature of its average case has been explored only for the selfadaptive multiple constraints routing algorithm (SAMCRA), which is an algorithm about multiple constraints routing. In this paper, we simplify SAMCRA into a format that is convenient for our average case analysis. This variant algorithm gives optimal solutions also for very large dimensional networks such as with more than 1000 nodes. Although it runs in exponential time in the worst case, we prove that its average case time complexity is bounded by a polynomial function of the number of nodes in the network. Lastly, we give empirical results that align with our theoretical work. [ABSTRACT FROM AUTHOR]

The paper briefly introduced the concept, characteristic and the development trend of SDN (Software Defined Network), and put forward virtual simulation experiment teaching means to SDN experiment teaching. The SDN experiment teaching scheme was designed as follows: Mininet, a network simulation platform, was adopted in simulating SDN networks, and OpenDayLight controller was adopted in the centralized control Network. Finally, using & "SDN forwarding control” experiment as an example, the paper detailed the scheme of SDN experiment teaching by the whole experimental process. Students can use SDN controller to carry out the network of the centralized control and scheduling by the simple operation in the experiment. The proposed SDN experiment teaching scheme based on virtualization technology was helpful to improve the teaching quality of SDN and arouse the students' interest in learning SDN. [ABSTRACT FROM AUTHOR]

The evolutionary development of railway power-supply systems and computer networks and technologies that control these systems are analyzed. It is shown that the optimization of electricity consumption is based on the intellectualization of electricity supply procedures. A graph is constructed whose topology adequately represents the typical architecture of a computer network of control at the layer of a distance of power supply of railways with a view to investigating the mutual integration of a power supply infrastructure and a computer network architecture of all-mode control. This article proposes a differential mathematical model for investigating the computer network architecture of an all-mode system of control over a distance of power supply and methods (in analytical form) for determining values of probabilities of states of system nodes, their capacities, and the number of failures of requests as the basis for the intellectualization of power supply procedures. [ABSTRACT FROM AUTHOR]

A simple distributed object model, called an asynchronous distributed object protocol (ADOP), was designed and implemented as middleware for a control system of a synchrotron radiation source. The ADOP replaces time-constrained parts of the control system that were previously based on the Java Remote Method Invocation (RMI) model. Under RMI’s synchronous communication, when a client executes a remote-method invocation for a device/component to be controlled on a remote server, the client is suspended until the server sends a result back to the client after completing the control sequence. Using the ADOP, even in a multi-client environment, clients are not blocked when they make remote-method invocations with an object parameter/return object that includes short control data associated with the event data, status data, and setting data for the devices/components. The clients can asynchronously receive resultant control data from the remote servers. Performance measurements obtained in experiments demonstrate that the ADOP had an execution time that was 1.4–13.1% of the RMI’s execution time. [ABSTRACT FROM AUTHOR]

This paper deals with retrial queueing models having an unlimited/a finite orbit capacity with control retrial policy of a multiprogramming-multiprocessor computer network system. Under the Markovian assumptions and light-traffic condition, the steady-state probabilities of the number of programs in the system and the mean number of programs in the orbit are studied using matrix geometric/analytic methods. The expressions for the Laplace-Stieglitz transforms of the busy period and the waiting time are obtained. The probability generating function for the number of retrials made by a tagged program is also derived. Some interesting performance measures of the system and the various moments of quantities of interest are discussed. Finally, extensive numerical results are illustrated to reveal the impact of the system parameters on the performance measures. [ABSTRACT FROM AUTHOR]

Aiming at the problems existing in the experimental teaching of computer network course, in order to cultivate the ability for solving the problems of complex engineering problems and innovation, it researches the optimization design of practice teaching and diversified evaluation mode at three-levels-ladder which concludes basic skills, comprehensive application ability, engineering practice and innovation ability with combination the outcomes-based education (OBE). With the integration of education and research training, relying on research projects related to the most advanced and practical achievements in scientific research and network technology, it penetrates output indicators and curriculum knowledge into all levels from the easy to the difficult and complicated. By introducing the concept of OBE into practice, the learning outcome-driven is to replace the traditional teaching content-driven and form the continuous improvement of the quality assurance system. [ABSTRACT FROM AUTHOR]

Internet of things (I0T) is the core of the next generation of information technology, and the Internet is the foundation of I0T, therefore the computer networlc curriculum group has become the most important professional course of the information engineering specialty which undertakes the task of teaching knowledge of the network module. However, the traditional teaching model of experimental system could not keep the pace with the construction of the network curriculum group under I0T. This paper proposes a hierarchical architecture for network experiment curriculum group and builds an integrated experimental platform simultaneously according to the teaching conception of innovation priority, capability-driven, curriculum coordination and project-driven to meet the needs of talents cultivation through analyzing the contents and characteristics of the experimental teaching in computer networlc curriculum group, aiming at solving the problems which exist in the experiment teaching. [ABSTRACT FROM AUTHOR]

We propose a new dynamic ID-based remote user authentication scheme using smart cards, which it is based on one-way hash function, ElGamal's public key cryptosystem and nonce. The scheme achieves the following security requirements: 1) users can choose and change their password freely, 2) mutual authentication between the user and the server, 3) the user and the server establish a session key after successful authentication process, 4) the server does not maintain a verification table, 5) the login request message does not contain the user's identity, and 6) the authentication phase does not require time-synchronization, making it more secure than previous schemes. In order to verify the security characteristics of our protocol, we have modelled and analysed the proposal using High-level Protocol Specification Language (HLPSL) and Automated Validation of Internet Security Protocols and Applications (AVISPA) tool. The results demonstrate that our protocol achieves more security requirements than previous works. [ABSTRACT FROM AUTHOR]

Principle of computer networks is a core subject in computer specialty. There are many unintelligible protocols, processes and algorithm. By using Authorware, authors develop a computer networks multimedia courseware which is simple, powerful and interactive. This paper describes architecture and methods of designing courseware using Authorware. The courseware focuses on three typical protocols and the implementation of the process principle and implementation method which include three ways of information exchange, stop-waiting protocol and subnet exchange process. Authors summarize and solve the problems arising from the implementation process, especially discuss on using icon tips. Practice has proved that multimedia courseware can simulate network protocols and process principle to visualize protocols and process, and also enhance interactive learning, autonomy and creativity. [ABSTRACT FROM AUTHOR]

In order to reduce disaster damage, there are several media such as email, TV, radio and a public address system with outdoor loudspeakers to deliver emergency announcements to the people at risk. The Great East Japan Earthquake revealed the importance of a public address system with outdoor loudspeakers for emergency announcements and the difficulty of its intelligibility. To achieve a public address system with sufficient intelligibility for residents, one important factor is to suppress sound overlap caused by reflection from terrain or buildings, or caused by the simultaneous emission of other loudspeakers. Recent Internet technologies and devices will contribute to avoid sound overlap caused by the simultaneous emission of other loudspeakers. In this paper, a method of controlling emission timing to minimize the sound overlap caused by the simultaneous emission of other loudspeakers of a public address system is proposed. This method focused on the transmission of a signal between the input and output of a public address system. Under the assumptions that the attenuation and delay factor between a loudspeaker and a listening point depend only on the distance and the directivity of each node is omnidirection, the optimal emission timing for a pair of nodes is expressed in terms of the signal to interference ratio. Then, on the basis of the above optimal emission timing, the emission timing for a set of nodes in a management area is determined. In the proposed method, each node collects and shares the positions of each node obtained by the Global Positioning System via a computer network to determine the emission timing, and then taking into account whether other nodes emit sound or not each node autonomously determines its emission timing and the delay time for other nodes. The proposed method can be implemented without any dedicated hardware and can, therefore, be applied to existing loudspeakers. The delay and error factors in a public address system employing the proposed method are also modeled and estimated. [ABSTRACT FROM AUTHOR]

Presently, computer network technology and application have penetrated all fields of society, particularly towards advanced primary education in Chinese universities and engineering colleges. They are hardly used to improve the standard of advanced teaching using multimedia assistive instruction. This paper examines the teaching mode of physical education based on Advanced Multimedia Technology (AMT) for Teaching Evaluation in engineering education to improve the current standard of education. Education in physical activity has a distinct advantage in terms of its instructional role and services in the network environment, which offers a functional training atmosphere for the learners. According to a questionnaire survey, the students said the impact of digital teaching became substantially higher than the conventional teaching in physical education and hence agree that computer-aided instruction would increase learning interest than traditional mode. Instantly, the difficulties of physical education teaching provide some suggestions based on the student evaluation of teaching in multimedia-assisted technology, which has become a successful approach to evaluating teaching faculties. The experimental research indicates that the suggested methods can precisely classify student evaluation tasks. Mutual trust and cooperation between teachers and students are strengthened by the implementation of multimedia-assisted teaching and other techniques with a positive impact, and the practical capacity of students is greatly improved. [ABSTRACT FROM AUTHOR]