TY - GEN
T1 - Effectiveness of autonomous network monitoring based on intelligent-agent-mediated status information
AU - Konno, Susumu
AU - Abar, Sameer
AU - Iwaya, Yukio
AU - Kinoshita, Tetsuo
PY - 2007/12/24
Y1 - 2007/12/24
N2 - The growing complexity of communication networks and their associated information overhead have made network management considerably difficult. This paper presents a novel Network Management Scheme based on the novel concept of Active Information Resources (AIRs). Many types of information are distributed in the complex network, and they are changed dynamically. Under the AIR scheme, each piece of information in a network is activated as an intelligent agent: an I-AIR. An I-AIR has knowledge and functionality related to its information. The I-AIRs autonomously detect run-time operational obstacles occurring in the network system and specify the failures' causes to the network administrator with their cooperation. Thereby, some network management tasks are supported. The proposed prototype system (AIR-NMS) was implemented. Experimental results indicate that it markedly reduces the network administrator workload, compared to conventional network management methods.
AB - The growing complexity of communication networks and their associated information overhead have made network management considerably difficult. This paper presents a novel Network Management Scheme based on the novel concept of Active Information Resources (AIRs). Many types of information are distributed in the complex network, and they are changed dynamically. Under the AIR scheme, each piece of information in a network is activated as an intelligent agent: an I-AIR. An I-AIR has knowledge and functionality related to its information. The I-AIRs autonomously detect run-time operational obstacles occurring in the network system and specify the failures' causes to the network administrator with their cooperation. Thereby, some network management tasks are supported. The proposed prototype system (AIR-NMS) was implemented. Experimental results indicate that it markedly reduces the network administrator workload, compared to conventional network management methods.
UR - http://www.scopus.com/inward/record.url?scp=37249009192&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=37249009192&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:37249009192
SN - 9783540733225
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 1078
EP - 1087
BT - New Trends in Applied Artificial Intelligence - 20th International Conference on Industrial, Engineering, and Other Applications of Applied Intelligent Systems, lEA/AlE 2007, Proceedings
T2 - 20th International Conference on Industrial, Engineering, and Other Applications of Applied Intelligent Systems, lEA/AlE-2007
Y2 - 26 June 2007 through 29 June 2007
ER -