1 research outputs found
Comprehensive Analysis of AggSessAC Method for Revenue Maximization Using OMNeT++
The growing demand for Internet connection of
various devices with an ability to provide smarter online services
and the rapid growth of mobile applications significantly
increases the number of processed data flows. All the generated
flows require selective and priority-based flow admission
strategy. Network operators are interested in effective utilization
of their infrastructure as well as in minimizing rejection
probability of higher priority flows while maximizing their
revenue, especially in peak hours. The existing connection
admission control (CAC) schemes are largely based on serialized
processing strategies of new flows without any comparison
among consequent requests. However, evolution of Internet and
present performance capabilities of routers allows us to offer a
new approach for admission control – our developed Aggregated
Session Admission Control (AggSessAC). We propose to handle
service requests using a new operation paradigm of CAC, where
requests are temporarily collected and processed using mutually
comparisons among them, thus facilitating selectivity and
ensuring network revenue maximization as well as operator gain.
In order to evaluate the proposed algorithm, OMNeT++
simulation platform with the INET Framework was used and a
new output queue of router has been developed including all
relevant entities of proposed admission control. Simulation
results are compared with conventional threshold admission
control method, which only uses available link bandwidth for
decision-making process and serialized flow processing strategy.
The proposed method shows that selective and comparative flow
control allows maximizing the number of accepted higher
priority flows and is able to significantly increase the total
network revenues in peak hours, compared to the standard
threshold based approach. We assume that AggSessAC can be
effectively used as the potential admission control mechanism in
Next Generation Networks (NGN)