The Therefore, to efficiently and effectively route

The current growth of the internet resulting in IPv4 address space
exhaustion has

given IPv6 the legitimacy and inevitability that cannot be ignored. IPv6
is the next–

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generation Internet Protocol, with a large addressing space, and will be
used to replace the legacy IPv4 in the near future. Demand for IPv6 deployment
is rising gradually and will no longer be an optional task but mandatory,
especially for organizations that will require expansion in the future.

IPv6 was completely designed on the basis of IPv4. However, some
existing features

in IPv4 are replaced with newly enhanced features in IPv6, and this has
changed the packet layout of IPv6 making it different from IPv4 packet layout.
The difference in packet structure between the two protocols means that routing
traffic in IPv6 will no longer be supported by conventional routing protocols
used in IPv4; hence new routing protocols that are compatible with IPv6 must be

Besides, even though there are different IPv6 supported routing
protocols like RIPng,

EIGRPv6, IS–IS and OSPFv3 that keep track of routes in communication
networks using different algorithms for better performance, when large networks
increase, routed traffic also increases leading to a reduction in network
stability. Routing instability is found to be one of the major causes of
network degradation in internet service performance. For example any
disturbance in a network within a few hundreds of milliseconds is sufficient to
disrupt voice or video transmission during protocol convergence. Voice packets
for instance can be lost, delayed or suffer from jitter causing the network to
degrade in performance.

Therefore, to efficiently and effectively route data in communication

implementation of a suitable routing protocol is a critical success
factor to achieve high performance.

In this thesis, performance of OSPFv3 and IS–IS has been evaluated and

for some applications such as database query,
remote login, file transfer, email and web browsing using Riverbed Modeler
Academic Edition. Performance evaluation is based on network convergence
duration, IPv6 packets dropped, throughput, link utilization, database query
response time, remote login response time, file download/upload response times,

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