Dynamic provisioning with availability guarantee for differentiated services in survivable mesh networks

Survivability is a key concern in modern network design in order to achieve fast service restorability against network failures. This paper investigates the problem of survivable dynamic connection provisioning in general telecom backbone networks, which are mesh structured. These networks employ optical fibers, which may fail due to network outages such as fiber cuts, etc. Our study applies to survivability of optical wavelength-division multiplexing (WDM) as well as multi-protocol label switching (MPLS) networks. For survivability study, we assume differentiated services where connections may have different availability requirements, so they may be provisioned differently with protection (if needed) based on their availability requirements and current network state. Therefore, it may be possible that connections with the same source, destination, and availability requirement are provisioned differently (unprotected, shared-path protected, or dedicated-path protected) at different times based on current network state. Such differentiated provisioning can provide diverse levels of service performance and achieve network resource optimization flexibly. Our main contributions are as follows. First, we develop an analytical model to quantify the availabilities of connections with various protection modes, i.e., unprotected, dedicated-path protected, and shared-path protected. Particular emphasis is placed on computing a connection's availability with shared-path protection by employing the link-vector technique, because this technique can maximally explore the sharing potential among backup paths and achieve bandwidth-assignment flexibility. Based on the mathematical model, we then present a novel provisioning strategy for dynamic connection requests in which multiple levels of services are provided and different protection schemes may be applied to different connections. The strategy jointly considers both connection availability satisfaction and resource optimization. Numerical results show very good accuracy of our model and high effectiveness of our provisioning strategy

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