Topic
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.
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TL;DR: By improving the coordination of the system operator function, it may be achieved that the actual bottlenecks, both as regards to the location and capacity, form the basis for the definition of price areas, which may result in a better partition of the grid.
72 citations
TL;DR: A service-oriented network architecture is proposed to support the effective management of 5G-enabled IoT systems and effectively reduces the traffic load and simplifies network management by introducing a service aggregation and caching (SAaC) scheme.
72 citations
20 Oct 2008
TL;DR: A context-aware clustering methodology is described that is applied to DNS query-responses to generate the desired aggregates and enables the analysis to be scaled to expose the desired level of detail of each traffic type, and to expose their time varying characteristics.
Abstract: The Domain Name System (DNS) is a one of the most widely used services in the Internet. In this paper, we consider the question of how DNS traffic monitoring can provide an important and useful perspective on network traffic in an enterprise. We approach this problem by considering three classes of DNS traffic: canonical (i.e., RFC-intended behaviors), overloaded (e.g.,black-list services), and unwanted (i.e., queries that will never succeed). We describe a context-aware clustering methodology that is applied to DNS query-responses to generate the desired aggregates. Our method enables the analysis to be scaled to expose the desired level of detail of each traffic type, and to expose their time varying characteristics. We implement our method in a tool we call TreeTop, which can be used to analyze and visualize DNS traffic in real-time. We demonstrate the capabilities of our methodology and the utility of TreeTop using a set of DNS traces that we collected from our campus network over a period of three months. Our evaluation highlights both the coarse and fine level of detail that can be revealed by our method. Finally, we show preliminary results on how DNS analysis can be coupled with general network traffic monitoring to provide a useful perspective for network management and operations.
72 citations
07 Aug 2002
TL;DR: A new approach to building network management solutions that is based on a new version of the DEN information model, called DEN-ng, which holistically binds business rules to the construction and deployment of configuration changes and their management.
Abstract: Existing network management architectures suffer from a set of architectural and integration problems. Policy-based management was targeted to solve most of these problems, but its promises have not yet been fully realized. This paper presents a new approach to building network management solutions that is based on a new version of the DEN information model, called DEN-ng. DEN-ng is being designed to solve these problems by providing facilities to translate the business rules and procedures of an organization to the policies that configure and control its networks. Accordingly, the case is made for policy to become more than "just" a means for executing a change in a configuration file. Rather, it should be used to tie together configuration changes with how the changes should be done using a workflow system. This holistically binds business rules to the construction and deployment of configuration changes and their management.
72 citations
09 Sep 2007
TL;DR: In this paper, the authors analyzed wireless users' behavioral patterns by mining wireless network logs from two major university campuses and utilized unsupervised learning (clustering) to classify trends in user behavior using novel similarity metrics.
Abstract: Recent years have witnessed significant growth in the adoption of portable wireless communication and computing devices (e.g., laptops, PDAs, smart phones) and large-scale deployment of wireless networks (e.g., cellular, WLANs). We envision that future usage of mobile devices and services will be highly personalized. Users will incorporate these new technologies into their daily lives, and the way they use new devices and services will reflect their personality and lifestyle. Therefore it is imperative to study and characterize the fundamental structure of wireless user behavior in order to model, manage, leverage and design efficient mobile networks and services. In this study, using our systematic TRACE approach, we analyze wireless users' behavioral patterns by extensively mining wireless network logs from two major university campuses. We represent the data using location-preference vectors, and utilize unsupervised learning (clustering) to classify trends in user behavior using novel similarity metrics. Matrix decomposition techniques are used to identify (and differentiate between) major patterns. We discover multi-modal user behavior and hundreds of distinct groups with unique behavioral patterns in both campuses, and their sizes follow a power-law distribution. Our methods and findings might provide new directions in network management and behavior-aware network protocols and applications, to name a few.
72 citations