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On the Robustness of a Congestion Control Algorithm for Signaling Networks Based on a State Machine
Responsible organisation
1996 (English)Conference paper (Refereed) Published
Abstract [en]

Sessions of a signaling service with high real time demands which are subject to unaccept-able delays may be obsolete or prematurely terminated by the customer; in either way, they are a burden to the signaling network. It would ease the load of the network and im-prove the performance of all sessions in progress, if such delayed sessions could be abort-ed as quickly as possible. By measuring the network delay on individual signals of a service session, it is possible to perform signaling network congestion control that consid-ers the state in the entire signaling network. Under the assumption that a session comprises a sequence of signals between one originating node and an arbitrary number of destination nodes, it is possible to predict the total duration of a session. The prediction is calculated from previously completed signals using a state machine, which is defined per signaling link. The annihilation of sessions, for which the prediction exceeds a predefined time limit, is an embryo of a simple signaling network congestion control mechanism (CCM). This simple CCM increases the number of successfully completed services with a few hundred percent under favorable circumstances. The state machine approach has been proven to function well in all types of environments. The robustness and stability of the proposed CCM is demonstrated and the fairness in the admission of signaling services into the net-work at very high loads are also shown.

Place, publisher, year, edition, pages
Trondheim: Department of Telematics, Norwegian Univ. of Science and Technology , 1996.
Keyword [en]
Network overload, Intelligent networks
National Category
URN: urn:nbn:se:bth-9959Local ID: 82-993980-0-2OAI: diva2:837961
Thirteenth Nordic Teletraffic Seminar
This article is written under the Project "Overload Control in Intelligent Networks"Available from: 2012-09-18 Created: 2000-03-15 Last updated: 2015-06-30Bibliographically approved

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