Page 253 - DCAP601_SIMULATION_AND_MODELING

Unit 13: Simulation Languages (I)

decided to explore the transfer of algorithmic engineering technology in that area by specializing Notes
and focusing the ALCOM-IT produced DSS tool in the above direction. The new DSS tool aims to
provide:
1. An abstract, clean and semantically correct high level model of any ATM network and of
the on-line calls for connections.

2. A library of Call Admission Control algorithms in a form that allows them to him easily
used by non - experts or to be used and tested by algorithms and networks designers.
3. The capability for the user Industry to design new Call Control protocols and/or test such
designs.
The ATM technology is considered as the state of the art network technology that is expected to
play an important role in the future networks. The ATM networks are fast packet switching
networks achieving their speed by avoiding flow control and error checking at the intermediate
nodes in a transmission. ATM operates in a connected mode, but a connection can only be set up
and serviced if sufficient resources are available in order to preserve the quality of service to the
previous accepted connections. This function is controlled by the Call Admission Control
algorithms running in the ATM switches.
DSS provides an abstract model for the description of any ATM network which is independent
of details of the underlying technology. It simulates the basic functionality of an ATM network
which IS that in each time unit cells are produced from traffic generators or forwarded from the
switches to their destination.
Under the scope of DSS an ATM network topology consists of links, ATM switches, terminals
(workstation) and call/traffic generators (network applications). The critical characteristics of
the topology such as the size of the buffers of the ATM switch, the bandwidth of the links, the
virtual paths and virtual circuits over the links and the traffic parameters can be defined by the
user to approach the behavior of the today’s and the future network components. Each ATM
switch is modelled as a Communicating Finite State Machine. A receipt of a CAC cell combined
with its current state activates an action routine of the CAC algorithm.
Emphasis is given in the abstract modelling of traffic generation. Adversarial traffic leads the
on-line algorithms to their worst case competitive ratio of performance (measured against ideal
off-line algorithms that know the future). The DSS cannot simulate worst-case adversaries but
can approximate their behaviour by exploiting certain distribution of call request of high
Kolmogorov complexity.

Notes The DSS can of course use externally (pragmatic) generate call sequences.
13.1.3 Example of Discrete-event Simulation (DES) – Models of
Plasmodium Falciparum Malaria

We develop discrete-event simulation models using a single “timeline” variable to represent
the Plasmodium falciparum lifecycle in individual hosts and vectors within interacting host and
vector populations. Where they are comparable our conclusions regarding the relative importance
of vector mortality and the durations of host immunity and parasite development are congruent
with those of classic differential-equation models of malaria, epidemiology. However, our
results also imply that in regions with intense perennial transmission, the influence of mosquito
mortality on malaria prevalence in humans may be rivaled by that of the duration of host
infectivity.

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