Abstract:
Cloud provides a shared computing space on a pay-as-you-go model. Due
to this sharing, it is di cult to execute the task e ciently in terms of time.
Several factors play its parts such as process scheduling and computing requirement
of other processes sharing the system. Moreover, network usage
is highly depended on processes, typically processes are categorized computing
and communication intensive. Such sharing of platform often degrade
the performance of parallel and distributed simulations (PDS). The growth
and advancements in the eld of Cloud Computing has presented its users
with new challenges. Cloud Computing o ers resources to its consumers on
pay-as-you-go basis. Cloud computing o ers storage, virtual machines, memory,
processor and network as resources to its consumers. The more you use
these resources, the costly it becomes. Parallel and distributed simulation
(PDS) involves a number of logical processes (LPs) executing simultaneously
while communicating with each other by interchanging small messages called
packets using network. Since network is also o ered as a resource in cloud
computing if a PDS involves exchanging a huge number of messages over a
network, the procedure becomes expensive. In this dissertation a new way
of simulating huge networks is presented that focuses on reducing network
traffic.
