2,816 research outputs found
Modeling Routing Overhead Generated by Wireless Proactive Routing Protocols
In this paper, we present a detailed framework consisting of modeling of
routing overhead generated by three widely used proactive routing protocols;
Destination-Sequenced Distance Vector (DSDV), Fish-eye State Routing (FSR) and
Optimized Link State Routing (OLSR). The questions like, how these protocols
differ from each other on the basis of implementing different routing
strategies, how neighbor estimation errors affect broadcast of route requests,
how reduction of broadcast overhead achieves bandwidth, how to cope with the
problem of mobility and density, etc, are attempted to respond. In all of the
above mentioned situations, routing overhead and delay generated by the chosen
protocols can exactly be calculated from our modeled equations. Finally, we
analyze the performance of selected routing protocols using our proposed
framework in NS-2 by considering different performance parameters; Route
REQuest (RREQ) packet generation, End-to-End Delay (E2ED) and Normalized
Routing Load (NRL) with respect to varying rates of mobility and density of
nodes in the underlying wireless network
Performance Comparison of the RPL and LOADng Routing Protocols in a Home Automation Scenario
RPL, the routing protocol proposed by IETF for IPv6/6LoWPAN Low Power and
Lossy Networks has significant complexity. Another protocol called LOADng, a
lightweight variant of AODV, emerges as an alternative solution. In this paper,
we compare the performance of the two protocols in a Home Automation scenario
with heterogenous traffic patterns including a mix of multipoint-to-point and
point-to-multipoint routes in realistic dense non-uniform network topologies.
We use Contiki OS and Cooja simulator to evaluate the behavior of the
ContikiRPL implementation and a basic non-optimized implementation of LOADng.
Unlike previous studies, our results show that RPL provides shorter delays,
less control overhead, and requires less memory than LOADng. Nevertheless,
enhancing LOADng with more efficient flooding and a better route storage
algorithm may improve its performance
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