Simulation and Monitoring of a University Network for Bandwidth Efficiency Utilization
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As organization networks grow, it is essential that network administrators have knowledge of the different types of traffic traversing their networks and the methods of monitoring such traffic. Traffic monitoring and analysis is essential in order to troubleshoot and resolve issues as they occur in order not to bring the network to a total collapse. There are numerous tools and methods available for network traffic monitoring and analysis, no administrator can effectively carry out such activities without in-depth knowledge of the traffic on the network. The inefficient management of the network traffic may result into network collapse or degradation and these may negatively affect the network performance of the Corporate or University networks. This paper therefore, proposed a developed network topology and simulation to monitor the network performance. Therefore, achieving an effective management and controlling of the increase traffic flows in the network. The result obtained shows a better network performance in the bandwidth usage and utilization of the University network.Keywords:
Network traffic simulation
Network monitoring
Network Performance
Traverse
Network administrator
Bandwidth management
Trouble shooting
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With the increase of Internet users and the needs of the user change constantly,the type of application on the Internet is also undergoing rapid changes.Various types of traffic are growing,and the burden of the network becomes worse and worse,so the difficulties of network management have increased.In order to coordinate the relations between application and security,bandwidth growth and business gains,network expansion and user experience,there is a key challenge to the network managers and operators that how to use the appropriate traffic management techniques,such as network application protocol identification and bandwidth management technology.This paper was focus on this,and introduced the basic concepts and key technologies of network traffic management first.Then it introduced the mainstream open source traffic management systems and commercial traffic management systems.Finally,it proposed a collaborative distributed traffic management system,which deployed the traffic management subsystems dispersedly,detected and managed the traffic collaboratively through the analysis and operation center.It could effectively improve the efficiency of network traffic management and the recognition rate of unknown network protocol,and it also could effectively detect and prevent DDoS attacks.
Bandwidth management
Traffic classification
Traffic policing
Network monitoring
Deep Packet Inspection
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A communication infrastructure is not always easy to manage and the level of difficulty increases with the size and number of devices present in the network. Thus, the monitoring of a network is a fundamental process in that it may prevent or detect possible problems, also offering several auxiliary tools for the work of a computer network administrator. In this context, this work presents a novel platform for the monitoring and optimization of network infrastructures, which interface is easy and intuitive to analyze even for those who do not have high skills in the area of computer networks. Furthermore, and unlike most of traditional monitoring systems, the developed platform has an additional optimization module allowing the recommendation of possible changes/configurations in order to optimize the network resources.
Network monitoring
Interface (matter)
Network administrator
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Maldistribution of network traffic widely exists because of the connectionless and incompact management of network resources in current IP network.This problem causes low usage rate of network resources and hard response to sudden QoS requirements by ISPs.Reconfigurable network with features of network resource concentration management solves this problem,but the lack of specific service optimization and network resources reconstruction capability causes that resource allocation and QoS are still to be further improved especially the P2P traffic and unexpected high-priority service.The current P2P optimization and traffic engineering technology not only have their own problems,but also cannot be directly used in the reconfigurable network environment efficiently.Therefore,this article standing on the global design level of network resources,propose a dynamically reconfigurable technology based on P2P traffic planning and fits for the reconfigurable network environment.This technology makes reconfigurable network resource management mechanisms have the ability to schedule the P2P traffic of the entire network,especially in the short of network resources circumstances,by adjusting the P2P traffic to release the specified network resources in response to the unexpected high priority needs.The emulations show that the traffic burden,P2P node output degree and input degree are more improved.This can establish a flexible reconfigurable network environment and give a service adjusting instrument to ISPs.
Network information system
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Presence of a logically centralized controller in software-defined networks enables smart and fine-grained management of network traffic. Generally, traffic management includes measurement, analysis and control of traffic in order to improve resource utilization. This is done by inspecting corresponding performance requirements using metrics such as packet delay, jitter, loss rate and bandwidth utilization from global network view. There has been many works regarding traffic management of software-defined networks and how it could help to efficiently allocate resources. However, the vast majority of these solutions are bounded to indirect information retrieved within the border of ingress and egress switches. This means that the three stage loop of measurement, analysis and control is performed on switches in between this border while the traffic flowing in network originates from applications on end hosts. In this work, we present a framework for incorporating network applications into the task of traffic management using the concept of software-defined networking. We demonstrate how this could help applications to receive desired level of quality of service by implementing a prototype of an API for flow bandwidth reservation using OpenFlow and OVSDB protocols.
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The volume, and density of computer network traffic are increasing dramatically with the technology advancements, which has led to the emergence of various new protocols. Analyzing the huge data in large business networks has become important for the owners of those networks. As the majority of the developed applications need to guarantee the network services, while some traditional applications may work well enough without a specific service level. Therefore, the performance requirements of future internet traffic will increase to a higher level. Increasing pressure on the performance of computer networks requires addressing several issues, such as maintaining the scalability of new service architectures, establishing control protocols for routing, and distributing information to identified traffic streams. The main concern is flow detection and traffic detection mechanisms to help establish traffic control policies. A cost-sensitive deep learning approach for encrypted traffic classification has been proposed in this research, to confront the effect of the class imbalance problem on the low-frequency traffic data detection. The developed model can attain a high level of performance, particularly for low-frequency traffic data. It outperformed the other traffic classification methods.
Traffic classification
Traffic policing
Internet traffic engineering
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Traffic engineering has been used in IP and MPLS networks for a number of years as a tool for making more efficient use of capacity by explicitly routing traffic demands where there is available network capacity that would otherwise be unused. Deployment of traffic engineering imposes an additional layer of complexity to network design and operations, however, which has constrained its adoption for capacity optimisation. The rise of Software Defined Networks has renewed interest in the use of traffic engineering approaches leveraging centralised network controllers for capacity optimisation. We argue that future networks can realise the network optimisation benefits of traffic engineering without incurring additional network complexity through closer coupling between the network and the applications and services using the network. This can be achieved through leveraging a network- and traffic-aware controller to directly influence where applications and services site or locate service instances, i.e. which implicitly impacts the paths that the applications or services traffic demands take through the network. We call this technique Demand Engineering. Demand Engineering has the additional benefit of providing an admission control capability, i.e. which can provide an assurance that network SLAs can be met. In this paper we describe the concept of Demand Engineering, give examples of its use and present simulation results indicating its potential benefits. We also compare demand engineering to traffic engineering.
On demand
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Traffic engineering has been used in IP and MPLS networks for a number of years as a tool for making more efficient use of capacity by explicitly routing traffic demands where there is available network capacity that would otherwise be unused. Deployment of traffic engineering imposes an additional layer of complexity to network design and operations, however, which has constrained its adoption for capacity optimisation. The rise of Software Defined Networks has renewed interest in the use of traffic engineering approaches leveraging centralised network controllers for capacity optimisation. We argue that future networks can realise the network optimisation benefits of traffic engineering without incurring additional network complexity through closer coupling between the network and the applications and services using the network. This can be achieved through leveraging a network- and traffic-aware controller to directly influence where applications and services site or locate service instances, i.e. which implicitly impacts the paths that the applications or services traffic demands take through the network. We call this technique Demand Engineering. Demand Engineering has the additional benefit of providing an admission control capability, i.e. which can provide an assurance that network SLAs can be met. In this paper we describe the concept of Demand Engineering, give examples of its use and present simulation results indicating its potential benefits. We also compare demand engineering to traffic engineering.
Network traffic simulation
Internet traffic engineering
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Internet traffic engineering
Resilience
Network traffic simulation
Upgrade
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As our modern life is very much dependent on the Internet, measurement and
management of network reliability is critical. Understanding the health of a network via
outage and failure analysis is especially essential to assess the reliability of a network,
identify problem areas for network reliability improvement, and characterize the network
behavior accurately. However, little has been known on characteristics of node outages
and link failures in access networks. In this dissertation, we carry out an in-depth outage
and failure analysis of a university campus network using a rich set of node outage and
link failure data and topology information over multiple years. We investigated the diverse
statistical characteristics of both wired and wireless networks using big data analytic tools
for network management. Furthermore,we classify the different types of network failures
and management issues and their strategic resolution.
While the recent adoption of Software-Defined Networking (SDN) and softwarization of network functions and controls ease network reliability, management, and various network-level service deployments, the task of monitoring network reliability is still
very challenging. We find it challenging because it not only requires vast measuring and
processing resources but also introduces an additional intermediate network, so-called a
’control-path network’, that physically connects the control and data plane networks. We
proposed a topology-aware network management framework that utilizes Link Layer Discovery Protocol (LLDP) messages via prudent control of the frequency of LLDP messages
and considering tier-based network architecture. It provides fast and effective reliability
information for faster recovery from failures. The topology-aware analysis also enables
us to explore the economic impact and the cost of various types of network failures with
regards to Capital Expenditure (CapEx) and Operational Expenditure (OpEx).
Wireless LAN (Local Area Network) or Wi-Fi has become the primary mode of
network access for most users; thus, its performance measurement becomes a critical part
of network management in access networks. Through large-scale, extensive analysis of
a university campus Wi-Fi network, we found its performance behavior and management
issues are very distinctive from awired network. The study also informs a strategic Wi-Fi
Access Point deployment and enhanced Wi-Fi association scheme for better coverage and
enhanced user experience.
Most of the current and future networks would involve both wired and wireless
subnets. Our work of understanding the unique issues of each one and their interplay
would shed light on managing and improving network reliability in a holistic manner.
Network monitoring
Network element
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Proactive Problem Avoidance and Quality of Service (QOS) Guarantees for Large Heterogeneous Networks
Abstract : The two primary objectives of this research are: 1) To develop innovative, real-time early warning techniques to detect performance anomalies in large scale, heterogeneous networks that would not be detected by current single element network monitoring/alarm techniques, or to detect those anomalies before current techniques would detect them; and 2) To develop adaptive routing and traffic management methods which enable traffic to proactively avoid these potential problem areas before the problems become serious. This will not only improve the network performance seen by this traffic, but it will also prevent additional traffic from compounding whatever local problems were detected.
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