A Methodology for Performance Management of Networks (original) (raw)
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Network monitoring and analysis are significant components in successfully functioning networks because they offer real-time data and information about the performance of the network. The following literature review gives an overview on how network monitoring tools have developed, speaking of the shift from simple availability and connection tests, to the use of Machine Learning and Artificial intelligence. To support the provided key areas of concern, an analytical overview of performance indicators like uptime, response time, packet loss, and bandwidth are provided with live examples of their importance in a network. Present-day approaches are discussed, with focus made on the most popular service solutions such as SolarWinds, Nagios, or PRTG. Network Monitor is provided and examined through case studies illustrating its efficient usage in various contexts. The paper also examines the latest methods improving the effective monitoring of the network, the security aspects, the problems arising from the increasing trends in scalability, integration, and varied forms of cyber threats. Possible advances, specifically automation and ai solutions are proposed as crucial for combating these challenges. This review has highlighted the necessity to have strong monitoring process in managing a complex network to address the emergent technology needs in the future.
For the last few years, we have been consulting a project which develops Network Management systems (NMSs). In NMS development, requirements about performance are rigid and various performance problems arise. To avoid these problems, we try to establish a performance design method in which we estimate the system performance based on the actual measurement. In this method, it is important which modules should be chosen as measurement targets to estimate the whole system performance accurately. In order to identify target modules for the measurement properly, it should be considered what relationships the modules have with other modules in view of performance. That is, we should identify measurement targets considering the software architecture from a performance perspective. In this paper, first we define the software architecture for the performance design, and then we describe a method for identifying the appropriate target modules to estimate performance. For this method, we also ...
Performance Evaluation of Network Management Operations
In this paper we present a newly begun research project about the performance evaluation of network management operations using static and mobile agent approach. The general objectives of this research project are to study using simulation the behaviour of performance of a range of network management concepts in order to find out their operation under a number of different situations. The expected outcome of this project is to provide recommendations on the appropriateness of different agent designs for different network management operations in different circumstances, specifications of management information required supporting these agents, and identification of the protocol and operational requirements necessary to support mobile network management agents.
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Packet-based data networks such as British Telecommunications (BT) plc's switched multimegabit data service (SMOS) have performance that varies with customer behavior, network design, and network provision. This paper describes a system researched to monitor such networks from the customer's perspective, but on behalf of the operator. The information generated allows the operator to determine whether the network is performing correctly or whether changes or customer load will require the network to be changed in some way. Such networks are increasingly important as many parts of the Internet are built on similar technologies. The paper specifically considers an architecture that encompasses all the main functionality involved in performance management of networks. Consideration is given to the management and dissemination of the data collected. A database to enhance network data mining performance is described. A method to identify the periods of significance in the measurement data based on a statistical test and a neural network is incorporated into a realization of the architecture. In addition, a novel mechanism for the real-time presentation of the network performance data in an operator-friendly manner is given.