Matej Kultan

Work place: Institute of Telecommunications, Faculty of Electrical Engineering and Information Technology, Slovak University of Technology in Bratislava, Slovakia

E-mail: matej.kultan@ut.fei.stuba.sk

Website:

Research Interests: Engineering

Biography

Matej Kultan: was born in 1989. He received the B.E. and M.E. degrees in Faculty of Electrical Engineering and Information Technology of Slovak University of Technology (FEI STU) Bratislava in 2007 and 2009, respectively. At present he is a PhD student at the Institute of Telecommunications of FEI STU Bratislava and IP Technical Pre-Sales Engineer at Alcatel-Lucent Slovakia.

Author Articles
Congestion Aware Multipath Routing: Aggregation Network Applicability and IPv6 Implementation

By Matej Kultan Martin Medvecky

DOI: https://doi.org/10.5815/ijitcs.2015.11.02, Pub. Date: 8 Oct. 2015

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.

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