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Network management

About: Network management is a research topic. Over the lifetime, 17859 publications have been published within this topic receiving 234520 citations. The topic is also known as: computer network management & NM.


Papers
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Patent
Ariel Pashtan1, Raymond M. Liss1
08 Mar 2000
TL;DR: In this paper, a network (300) collects performance data associated with each network element and passes the performance data to a network management element (330), creating a global traffic conditioning control.
Abstract: Network (300) collects performance data associated with each network element, passes the performance data associated with each network element to a network management element (330), creating a global traffic conditioning control, communicates the global traffic conditioning control to at least one of the plurality of network elements, and re-shapes an internal control of at least one of the plurality of network elements based on the global traffic conditioning control. In another aspect, a network (400) detects congestion of a micro communication flow associated with at least one of a plurality of communication traffic flows at a first network element, detects a communication traffic flow priority at a first level associated with the congested micro communication flow, changes at a second network element, in an upstream communication flow in relation with the first network element, the priority from the first level to a second level.

126 citations

Patent
Koji Nishi1
29 Mar 2007
TL;DR: In this article, the authors proposed a quality assured network services in a multi-domain network and comprises a network service management device for managing device clusters incorporated within the operations management network of each provider network and receiving service orders, and a multisource service broker for providing a broker function for achieving agreement between a plurality of providers.
Abstract: The invention provides quality assured network services in a multi-domain network and comprises a network service management device for managing device clusters incorporated within the operations management network of each provider network and receiving service orders, and a multi-domain service broker for providing a broker function for achieving agreement between a plurality of providers, and the multi-domain service broker further comprises a device for collecting domain information and information relating to the services each provider is able to provide from the network service management devices, and a device which on receipt of a network service request from a customer, extracts the network service management device of the domain which is able to satisfy the required quality level, and then issues instructions for the setting of the required information within the extracted network service management device.

125 citations

Book ChapterDOI
31 Mar 2005
TL;DR: This work proposes a framework for application classification using an unsupervised machine learning (ML) technique and proposes a systematic approach to identify an optimal set of flow attributes to use and evaluates the effectiveness of the approach using captured traffic traces.
Abstract: A number of key areas in IP network engineering, management and surveillance greatly benefit from the ability to dynamically identify traffic flows according to the applications responsible for their creation. Currently such classifications rely on selected packet header fields (e.g. destination port) or application layer protocol decoding. These methods have a number of shortfalls e.g. many applications can use unpredictable port numbers and protocol decoding requires high resource usage or is simply infeasible in case protocols are unknown or encrypted. We propose a framework for application classification using an unsupervised machine learning (ML) technique. Flows are automatically classified based on their statistical characteristics. We also propose a systematic approach to identify an optimal set of flow attributes to use and evaluate the effectiveness of our approach using captured traffic traces.

125 citations

Proceedings ArticleDOI
David Lee1, A.N. Netravali, K.K. Sabnani, B. Sugla, Ajita John 
28 Oct 1997
TL;DR: This paper model the network as a finite state machine and develops procedures for passive testing including the required data structure, efficient implementations and the complexity of the procedures, and applies the techniques to management of a signaling network operating under the Signaling System 7 (SS7).
Abstract: An important aspect of network management is fault management-determining, locating, isolating and correcting faults in the network. The paper deals with the algorithms for detecting faults, i.e., behavior of the network different from specifications. It is important for communication networks to detect faults "in-process" i.e., while the network is in its normal operation. Thus, we detect faults by examining the input-output behavior without forcing the system to specialized inputs explicitly for testing. Such testing is commonly called passive testing. We model the network as a finite state machine and develop procedures for passive testing including the required data structure, efficient implementations and the complexity of our procedures. We start with fully observable and deterministic machines and then study more realistic models: partially observable and nondeterministic machines. We also discuss extensions to communicating finite state machines and machines extended with parameters and variables. We apply our techniques to management of a signaling network operating under the Signaling System 7 (SS7) and report experimental results, which show the feasibility of applying passive testing to practical systems.

125 citations

Proceedings ArticleDOI
Yang Xu1, Yong Liu1
10 Apr 2016
TL;DR: This paper proposes methods to detect DDoS attacks leveraging on SDN's flow monitoring capability and demonstrates that these methods can quickly locate potential DDoS victims and attackers by using a constrained number of flow monitoring rules.
Abstract: Software Defined Networking (SDN) has recently emerged as a new network management platform. The centralized control architecture presents many new opportunities. Among the network management tasks, measurement is one of the most important and challenging one. Researchers have proposed many solutions to better utilize SDN for network measurement. Among them, how to detect Distributed Denial-of-Services (DDoS) quickly and precisely is a very challenging problem. In this paper, we propose methods to detect DDoS attacks leveraging on SDN's flow monitoring capability. Our methods utilize measurement resources available in the whole SDN network to adaptively balance the coverage and granularity of attack detection. Through simulations we demonstrate that our methods can quickly locate potential DDoS victims and attackers by using a constrained number of flow monitoring rules.

124 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202348
2022147
2021446
2020649
2019774
2018842