Intelligent Network Management System Research Articles

Review on Tunnel Communication Technology

Tunnels account for an increasing proportion of highways. Due to the semi-closed structure of tunnels, signal communication is difficult in tunnels. This review analyzes the signal data transmission requirements of intelligent network management systems, such as lighting systems, wind protection systems, fire protection systems, and vehicle and pedestrian positioning systems in tunnels. The selection of signal coverage and transmission methods are also discussed. The advantages and disadvantages of various networking methods are analyzed. This paper summarizes the wireless signal transmission, wired signal transmission and signal transmission modes of different tunnel types.

БЕСПРОВОДНЫЕ СЕНСОРНЫЕ СЕТИ В ЗАЩИЩАЕМЫХ ЗОНАХ

For military purposes, wireless sensor networks allow you to "link autonomous systems" into acomplex that has the property of self-organization, when objects "know" how to find each other andform a network, and in the event of a failure of any of the nodes can establish new routes for transmittingmessages. It is possible to achieve the desired efficiency of such complexes, mainly by improvingthe intellectual component of their control system in general and individual node in particular.However, it should be noted that the vast majority of research in this area remains at the theoreticallevel. The goal is to: 1) the study and development of algorithms for network design with mobilenodes and their possible failures due to the combat mission; 2) the study and development of site usesensor network to collect, analyze, and transmit data about the situation and decision-making in thearea of responsibility; 3) to offer relatively simple algorithms for giving the network node the property of intelligent behavior under the conditions of restrictions on power consumption and speed.It is shown that the required algorithms can be developed if the classes of typical situations andsuccessful methods of action in real conditions are identified. On this basis, it becomes possible todevelop formal models (patterns) for implementation in the node management system. A two-levelstructure of an intelligent network management system is proposed. The upper level, implementedby the operator, corresponds to such properties as survival, security, fulfillment of mission obligations,accumulation and adjustment of the knowledge base in the form of effective behavior patterns.The object of control for it is the network, considered as a functional system.

Intelligent network management system for solving the problem of offline monitoring 5G technologies

Maintenance and management of fourth-generation (4G) current networks are still done manually and semi-automatically, which is expensive and time-consuming. This poses a major challenge for network management of disparate, software-defined, and virtualized fifth-generation (5G) systems. Fifth-generation (5G) cellular networks include a wide variety of technologies to address very different uses. Assessing these technologies and exploring future alternatives is complicated by relying solely on network administrators. 5G network intelligence is an important alternative to network administrators. With the advent of network intelligence for the 5G system opens the possibility of intelligent control. Without the intervention of administrators, the new approach can autonomously solve network problems, cyberattacks and inefficient use of resources, which in turn can reduce operating costs, improve user experience and reduce the time to market of new services. This work presents a test bench of a 5G mobile network with a virtualized and organized structure that focuses on integration into artificial intelligence programs. The presented test bench uses open-source technologies for deployment and orchestration of virtual network functions for flexible creation of various scenarios of mobile networks with clear topologies of frontal and feedback. The article explains how to deploy the structure of the test bench and reproduce the presented results with the provided algorithms and presents the recommended architecture, functionality, closed control, algorithms that include network intelligence. An intelligent 5G test bench has been installed, and experimental results confirm the feasibility and effectiveness.

Extending a communication service provider's operations management based on knowledge granules and aspects derived from imperfect information

SummaryThe core of a communication service provider's business revolves around service‐related operations management, usually relying strongly on expert knowledge built inside the company. Knowledge representation in this environment inevitably requires addressing various domains. Team members working on common tasks bring domain diversity to their teams due to their various ontological areas of expertise. All team members must attain an acceptable level of knowledge regarding other domains to reach a team's desired level of effectiveness. This paper provides a novel way of linking divergent domain ontologies to facilitate and enrich service management in the communication service provider environment. The typical service provider infrastructure offers an extensive source of information for deriving knowledge regarding services, but the information is generally imperfect, inconsistent, and incomplete. Introducing a granular approach based on rough sets applicable to this imperfect information enables fractional management, which together with multiaspect formalisms enables the derivation of the specificity of a certain domain from a common source of knowledge without interference from other domains. A case study illustrates the implementation of an intelligent communication service and network management system based on the contexts used for assisting service strategies. The implementation empirically justifies the proposed approach.

Discussion on Information Security Technology of Big Data System

This paper points out the importance of information security in big data systems and the importance of improving the equipment and equipment production standards, and builds the system architecture of trusted equipment system and security redundancy. The method of eliminating vulnerability and resisting virus threat of big data system software is discussed. Study on the prediction and analysis of intelligent network management system for security and safety inspection of pattern recognition and fault situation, with big data intelligent security technology to run the program and data on the internal flow path and the boundary interface channel for safety monitoring, virus attack source model analysis, mining and clean up the system to strengthen the anti-virus, data encryption and network identity research detection. Through the early warning technology of information security technology and mining analysis to analyze suspicious intrusion early warning, data acquisition, discovery, and all kinds of threats and attacks to avoid amputation of system risk and virus source, to achieve big data high efficiency range of information security system.

OFLoad: An OpenFlow-Based Dynamic Load Balancing Strategy for Datacenter Networks

The latest tremendous growth in the Internet traffic has determined the entry into a new era of mega-data centers meant to deal with this explosion of data traffic. However, this big data with its dynamically changing traffic patterns and flows might result in degradations of the application performance eventually affecting the network operators’ revenue. In this context, there is a need for an intelligent and efficient network management system that makes the best use of the available bisection bandwidth abundance to achieve high utilization and performance. This paper proposes OFLoad, an OpenFlow-based dynamic load balancing strategy for data center networks that enables the efficient use of the network resources capacity. A real experimental prototype is built and the proposed solution is compared against other solutions from the literature in terms of load-balancing. The aim of OFLoad is to enable the instant configuration of the network by making the best use of the available resources at the lowest cost and complexity.

Adaptive Management of Cognitive Radio Networks Employing Femtocells

Network planning and management are challenging issues in a two-tier network. Tailoring to cognitive radio networks (CRNs), network operations and transmissions become more challenging due to the dynamic spectrum availability. This paper proposes an adaptive network management system that provides switching between different CRN management structures in response to the spectrum availability and changes in the service time required for the radio access. The considered network management system includes conventional macrocell-only structure, and centralized/distributed structures overlaid with femtocells. Furthermore, analytical expressions of per-tier successful connection probability and throughput are provided to characterize the network performance for different network managements. Spectrum access in dynamic radio environments is formulated according to the quality of service (QoS) constraint that is related to the connection probability and outage probability. Results show that the proposed intelligent network management system improves the maximum capacity and reduces the number of blocked connections by adapting between various network managements in response to free spectrum transmission slots. A road map for the deployment and management of cognitive macro/femto networks is also presented.

A Heterogeneous Service-Oriented Deep Packet Inspection and Analysis Framework for Traffic-Aware Network Management and Security Systems

A variety of Web-based applications, mobile apps, and other over the top data services with affordable 3G/4G enabled smart devices are major factors for enormous increase in heterogeneous data traffic at enterprise and mobile networks. This creates challenges regarding traffic management and requires traffic-aware intelligent network management to deliver sustained quality of experience for subscribers. Deep packet inspection and analysis (DPIA) provides base platform for development of traffic-aware intelligent network management and security systems. However, computationally complex DPIA-related packet processing for high speed data traffic makes these systems expensive. Furthermore, conventionally these traffic-aware network management and security systems are deployed in enterprise networks with independent and dedicated DPIA-related processing resources and require multiple copies of passively provisioned high speed data from network, while performing similar DPIA operations over the same data again and again. This duplicate deployment of expensive software and hardware resources for DPIA processing eventually results in higher capital expenditures as well as operational expenditures for network operators. We have proposed a novel service-oriented framework for heterogeneous deep packet inspection and analysis (SoDPI) that simultaneously provides diversified DPIA services to multiple client applications for network management and security operations in high-speed networks. Proposed framework provides flexible and comprehensive API-based service interface for client applications to register required DPIA services. SoDPI framework implementation is based on commodity hardware and deploys shared set of DPIA-related packet processing components, requiring only single copy of passive data provisioned from network. Experimental evaluations show that novel SoDPI framework requires considerably reduced amount of software and hardware resources to fulfill heterogeneous DPIA packet processing requirements for multiple client applications in comparison with conventional network management and security applications with dedicated DPIA components. This results in lower cost impacts for network operators with more network manageability.

IMANetMS - An Intelligent Mobile Agent-Based Network Management Approach for a Real Scenario

 Abstract—Current Network Management paradigms are rigid and lack flexibility. Therefore, a new kind of management system and strategy must be provided to enhance the reliability and performance of Network Management. This paper presents the results of our work on Mobile Agent technology as a new paradigm for developing Network Management applications. Problems existing in traditional Network Management are discussed and a distributed solution is proposed. In this new approach, Mobile agents are the lead characters, in a world where networks grow in a larger and complicated way. Finally, we present the results from an implemented architecture for a real network scenario. Our efforts resulted in IMANetMS, an Intelligent Mobile Agent Network Management System.

Vehicle Access Intelligent Monitoring and Network Management System Based on RFID Technology

Now, Internal and external vehicles are artificially queried and identified by a specially-assigned person in most of schools and enterprises, so the workload of vehicle management is very heavy, what’s more the vehicles information can not be effectively preserved. So it is not convenient for vehicles access query in the furture. Using RFID intelligent sensor network technology, the intelligent monitoring and identifing of vehicles access was realized and vehicles access was better controlled. The system can provide real-time effective data for enterprises management. Through the unit LAN system, the remote transmission and perservation of the vehicle information and photos were completed, so the network management was realized and the information can be conveniently queried in the future.

An active and intelligent network management system with ontology-based and multi-agent techniques

This paper presents a system to collect information through the cooperation of intelligent agent software, in addition to providing warnings after analysis to monitor and predict some possible error indications among controlled objects in the network. This technique derived from the ontology combining Ethereal and Cacti, which store the operating information of network management perfectly into the backend database. The system could sketch the four main components of network management systems with the technique of graphic monitoring multi-agent: an Interface Agent, a Proxy Agent, a Monitoring Agent, and a Search Agent. This architecture can effectively enhance and improve the network monitoring performance to be an active and intelligent network management system. It can present related quantification figures of dynamic information through graphic network monitoring system to provide fast, convenient, and profound network solutions to the users. The experimental outcomes proved that the techniques could not only precisely recognize error alarms but also indeed reduce the recovery time to 61% of traditional processing time for network troubleshooting.

An architectural model for intelligent network management

Traditional network management approach involves the management of each vendor’s equipment and network segment in isolation through its own proprietary element management system. It is necessary to set up a new network management architecture that calls for operation consolidation across vendor and technology boundaries. In this paper, an architectural model for Intelligent Network Management (INM) is presented. The INM system includes a manager system, which controls all subsystems and coordinates different management tasks; an expert system, which is responsible for handling particularly difficult problems, and intelligent agents, which bring the management closer to applications and user requirements by spreading intelligent agents through network segments or domain. In the expert system model proposed, especially an intelligent fault management system is given. The architectural model is to build the INM system to meet the need of managing modern network systems.