Practical Fuzzy-CAC Realization for Effective Traffic Engineering in MPLS-TE Networks

Voice over IP (VoIP), and especially IPTV and Video on Demand (VoD) applications are gaining an ever increasing popularity these days [1], reinforced by the massive deployment of wide range of the fast access technologies. Supporting these applications requires the effective QoS provisioning at all the relevant points in the Internet. The application driven traffic control is needed to achieve fully dynamic resource management manner, as it is defined as a basic concept of the NGN. MPLS-TE could serve as the brilliant solution for the future networks development strategy, which is mentioned to be QoS aware and concerning end-to-end provisioning, if the RSVP-TE were able to take into consideration possible application QoS requirements and network QoS potentialities. Today RSVP-TE uses classical threshold CAC algorithm while making decision whether to set-up new LSP or not, and is not able to provide selective flow control for dynamic LSP set-up. As the CAC decisions are reliable for such traffic oriented performance objectives as packet loss, delays, throughput maximization, enforcement of service level agreements (SLA), packet delay jitter etc., we have to pay great attention to the CAC decision making mechanisms which are utilized in MPSL-TE networks. The threshold CAC is not capable of making decisions in uncertain conditions, which are prevailingly persistent in the modern broadband networks [2]. The dynamic traffic demand in the fast changing environment and bursty background traffic practically eliminate the possibility of fast online reasoning, which in case of CAC decision making is even in the sub-second time scale [3]. Fuzzy logic serves as the excellent tool to cope with uncertain and multivariable data, this giving the flexibility and robustness for decision making while using IF-THEN fuzzy rules [4]. In this paper, we propose the practical fuzzy-CAC implementation to RSVP-TE protocol inside the MPLS-TE network, using fuzzy-CAC mechanism, which was introduces by authors of the current paper in multiple previous publications [5–7]. In papers mentioned above, one can find comprehensive description of fuzzy-CAC implementation based on simulation results, as well as fuzzy-CAC adaptation method descriptions for effective traffic control in MPLS/GMPLS network domains. In this paper we focus purely on fuzzy-CAC practical realization in MPLS-TE test network and provide experimental testbed description as well as the summary of the general practical results.