Hybrid Multi-constrained Optimal Path QoS Routing with Inaccurate Link State

Many applications in the Internet today demand high end-to-end Quality of Service (QoS) assurance, such as bandwidth, delay, jitter and packet loss constraints. Also they seek better utilization of the network resources, while satisfying customer needs. Multi-constrained optimal path (MCOP) QoS routing problem attempts to find a feasible path that satisfies the requested QoS constraints, while maintaining high utilization of network resources. This problem is known to be intractable and several heuristic and approximation algorithms have been proposed. In practice, the network state information available for making the routing decisions at each node is often inaccurate. The effectiveness and performance of the routing algorithms can significantly be degraded by this outdated information and should not be treated as exact when selecting feasible paths. This research proposes an efficient heuristic algorithm called Distributed Heuristic Multi-Constrained Optimal Path (DHMCOP) for the MCOP problem, when the link state information is inaccurate. The proposed algorithm incorporates the aspects of both source and distributed routing. It attempts to minimize the computational complexity and protocol overhead while ensuring that the QoS guarantees are satisfied. The algorithm consists of a k-shortest path algorithm, a control message structure for resource reservation and a cost function for path optimization. The extensive simulation results show that the proposed algorithm outperforms the existing ones in terms of success ratio and control overhead.