Automation of Network Management with Multidisciplinary Concepts

In todays growing and ever changing world of computer networks, management systems need to have the abilitiesof intellectual reasoning, dynamic real time decision making,experience based self-adaptation and improvement. Furthermore,ever increasing size and complexity of computer networks requireautomation for their management systems. Automation minimizeshuman involvement which produces effective and time savingsolutions for proper and dynamic supervision of these largeand heterogeneous networks. In the light of above discussion,the design of an ef cient, dynamic and automated networkmanagement framework requires support from the eld ofarti cial intelligence. As the techniques based on the principles ofarti cial intelligence provide sophisticated abilities of intelligentdecision making, experience based improvement and creativeproblem solving. This paper provides a survey of some importantmultidisciplinary research efforts that propose the use of moderntechniques from the elds of Distributed Arti cial Intelligence,Machine Learning and Neural Networks for improving networkmanagement.Keywords: Network Management, Distributed Arti cial Intelligence, Machine Learning, Arti cial Neural Networks