Title :
An implementation of on-line management of livelock type feature interaction in NGN
Author :
Lu Yiqin ; Yang Xiaodong ; Fang, Fang ; Wang Shuoran
Author_Institution :
Sch. of Electron. & Inf. Eng., South China Univ. of Technol., Guangzhou, China
Abstract :
Under the competition pressure and driven by the technology development, the number of value-added services will increase very rapidly to improve the ARPU (average revenue per user) of the telecom industries. That makes the feature interaction (FI) problem more serious in the emerging telecom system. Besides, to make the creation of a feature easier, service design is open to the third party in a next generation network (NGN). The feature logic will be kept private for business purpose, which makes it hard to detect FI off-line with formal languages. On-line methods are regarded to be suitable for FI detection in NGNs. An on-line method is proposed to detect and manage a common kind of FI- livelock type FIs. In the method, a functional entity called feature interaction manager (FIM) is added into the network. When a SIP message is transferred between softswitch (SS) and application server (AS), its copy will be sent to FIM. From the SIP messages, the signalings related to the livelock type FI are extracted and form a signaling set. The signaling sets are then used to form a signaling chain. If the chain has a ring, it means there is signaling circle. A livelock may exist and a FI will occur. Once a livelock FI is detected, an instant message is sent as SIP message extension to user terminal, AS, or SS to warn the abnormity. The livelock then can be broken by modifying the header field of SIP message between the AS and SS.
Keywords :
commerce; signalling protocols; telecommunication industry; telecommunication networks; NGN; SIP messages; application server; business purpose; feature interaction manager; feature logic; formal language; livelock type feature interaction; online management; signaling circle; softswitch; telecom industry; value added service; Artificial neural networks; Educational institutions; Feature extraction; Logic gates; Next generation networking; XML; NGN; feature Interaction; livelock; on-line detection;
Conference_Titel :
Computer Science and Information Technology (ICCSIT), 2010 3rd IEEE International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-5537-9
DOI :
10.1109/ICCSIT.2010.5564483