A Comparison of Mamdani and Sugeno Fuzzy Based Packet Scheduler for MANET with a Realistic Wireless Propagation Model

The mobile nature of the nodes in a wireless mobile ad-hoc network (MANET) and the error prone link connectivity
between nodes pose many challenges. These include frequent route changes, high packet loss, etc. Such problems increase the end-toend
delay and decrease the throughput. This paper proposes two adaptive priority packet scheduling algorithms for MANET based
on Mamdani and Sugeno fuzzy inference system. The fuzzy systems consist of three input variables: data rate, signal-to-noise ratio
(SNR) and queue size. The fuzzy decision system has been optimised to improve its efficiency. Both fuzzy systems were verified
using the Matlab fuzzy toolbox and the performance of both algorithms were evaluated using the riverbed modeler (formally known
as OPNET modeler). The results were compared to an existing fuzzy scheduler under various network loads, for constant-bit-rate
(CBR) and variable-bit-rate (VBR) traffic. The measuring metrics which form the basis for performance evaluation are end-to-end
delay, throughput and packet delivery ratio. The proposed Mamdani and Sugeno scheduler perform better than the existing scheduler
for CBR traffic. The end-to-end delay for Mamdani and Sugeno scheduler was reduced by an average of 52% and 54%, respectively.
The performance of the throughput and packet delivery ratio for CBR traffic are very similar to the existing scheduler because of the
characteristic of the traffic. The network was also at full capacity. The proposed schedulers also showed a better performance for VBR
traffic. The end-to-end delay was reduced by an average of 38% and 52%, respectively. Both the throughput and packet delivery
ratio (PDR) increased by an average of 53% and 47%, respectively. The Mamdani scheduler is more computationally complex than
the Sugeno scheduler, even though they both showed similar network performance. Thus, the Sugeno scheduler is more suitable for
real-time applications.