JAVA- Fast Simulation of services availability in mesh network with dynamic path restoration

JAVA- Fast Simulation of services availability in mesh network with dynamic path restoration

ABSTRACT

A fast simulation technique based on importance sampling is developed for the analysis of path service availability in mesh networks with dynamic path restoration. The method combines the simulation of the path rerouting algorithm with a “dynamic path failure importance sampling” (DPFS) scheme to estimate path availabilities efficiently. In DPFS, the failure rates of network elements are biased at increased rates until path failures are observed under rerouting. The simulated model uses “failure equivalence groups,” with finite/infinite sources of failure events and finite/infinite pools of repair personnel, to facilitate the modeling of bidirectional link failures, multiple in-series link cuts, optical amplifier failures along links, node failures, and more general geographically distributed failure scenarios. The analysis of a large mesh network example demonstrates the practicality of the technique. JAVA- Fast Simulation of services availability in mesh network with dynamic path restoration

EXISTING SYSTEM:

• The concept of mesh network architecture is being adopted increasingly in the field in the development and deployment of new networks or in the replacement, migration, or evolution of existing networks.
• Existing link sharing between a primary path and backup path(s) in order to achieve better capacity utilization, a connection can share some highly reliable links in common among its primary and backup paths.
• Multiple backup paths are provided to an availability-stringent connection, compared to the traditional scheme which may have to block some high-availability connections.

PROPOSED SYSTEM:

We consider the general problem of analyzing path availability in mesh networks with dynamic path restoration, where failover paths are determined dynamically, “on the fly,” by an algorithm in real-time based on the current state of the network. In this general problem, the size of the state-space and the structural complexity of the system generally preclude the use of analytical modeling techniques. Direct simulation can also be very challenging, or even impractical, when the sets of network element failure events that lead to loss of end-to-end path service occur very rarely.

We develop a fast efficient Markov Monte Carlo simulation technique for the analysis of service availability in a general mesh network model with a general dynamic path restoration method. In the model, it is assumed that there is a given set of initial end-to-end paths that carry end-to-end traffic demands.

One or more network element failures, the affected paths are rerouted dynamically by a given rerouting algorithm that generates alternate routes to use. As element repairs are made and the initial routes become available again for use, the rerouted paths may revert to their respective original routes.

The model also uses the concept of a “failure equivalence group” (FEG), consisting of failure event sources and pools of repair personnel, to account for multiple in-series link cuts, optical amplifier failures along each link, as well as bidirectional link failures, node failures, or more general geographically distributed failure scenarios.

The DPFS simulation technique developed here is a practical and effective method for estimating service availability in mesh networks with dynamic path restoration. It enables one to obtain useful confidence interval widths on path service availabilities in reasonable simulation run times. The developed failure and repair modeling with FEG is sufficiently general so that it can be used to faithfully represent many of the types of failure and repair mechanisms that appear in practice.