Currently, the service provider network capacity utilization is low due to the shortest multipath based routing protocols Opens Shortest Path First (OSPF) and Intermediate System-to-Intermediate System (ISIS). Due to inefficient routing approach, certain paths can be overloaded and link capacity is required while alternative paths are unused. The overall network has to be dimensioned with higher link bandwidth requirements introducing additional line, linecard, routing engine and overall solution cos. This paper provides improved Congestion Aware Multipath Routing (CAMRv2) algorithm overview. The new network routing algorithm allows higher throughput, network load-balancing and stability to ensure lower congestion and data drop on critical links. The algorithm discovers unused network resources and dynamically adapts to the actual traffic load and displacement. The focus in this paper is on new parameters for path computation performance improvement. Additionally, detailed IPv6 source routing CAMRv2 implementation for parallel coexistence with present networks is presented. Finally, the new routing algorithm is simulated in several scenarios over aggregation network. The result of simulations have proved better performance and resource utilization of the proposed algorithm in sparse aggregation network in terms of load-balancing between uplinks to the core network.

In this paper we present a new packet scheduling method based on parallel usage of multiple WRR schedulers, rate limiters and output bandwidth calculation for modern NGN networks. The main idea of the presented method is to provide queueing fairness within queues. The method provides the same results in output bandwidth allocation as the compared algorithm, while within one queue flows with different packet size and arrival rates gets the same output bandwidth. With this method we are able to achieve the overall result of bandwidth assignment as algorithms like WRR, WFQ, WRRPQ and LLQ by only changing the mathematical model used to calculate the bandwidth assignment. We call this method Weighted Round Robin and Rate Limiter based Fair Queuing (WRRRLbFQ). We prove the model outcome with simulation results using NS2 simulator and compare the behavior with the WRR scheduler.