Title: Amazon cloud computing platform EC2 and VANET simulations

Authors: Muhammad Azhar Iqbal; Muhammad Aleem; Muhammad Ibrahim; Saleem Anwar; Muhammad Arshad Islam

Addresses: Department of Computer Science, Capital University of Science and Technology, Islamabad 44000, Pakistan ' Department of Computer Science, Capital University of Science and Technology, Islamabad 44000, Pakistan ' Department of Computer Science, Capital University of Science and Technology, Islamabad 44000, Pakistan ' Department of Computer Science, Capital University of Science and Technology, Islamabad 44000, Pakistan ' Department of Computer Science, Capital University of Science and Technology, Islamabad 44000, Pakistan

Abstract: Network simulations are resource and time intensive tasks due to the involvement of a number of factors attributable to scalability with respect to computation time, cost, and energy. Academic clouds are employed for large-scale network simulations, which require extensive capacity and intelligent resource management. This paper explores the performance efficiency of cloud solution to facilitate network researchers by proposing the utilisation of network simulator configured virtual machines. The prototype framework is executed using Amazon elastic computing cloud (EC2) Windows' instances configured with OPNET simulator. Simulation results show three significant benefits i.e., i) for scalable network simulations, consumption of considerably fewer resources in terms of simulation elapsed time, hardware resources and usage costs; ii) reduction of carbon emission leading towards sustainable IT; iii) promotion of network research by making complicated issues like simulation scalability and setup (installation or configuration) of network simulators to facilitate researchers and students.

Keywords: academic clouds; VANET simulations; Amazon EC2; large-scale simulations.

DOI: 10.1504/IJAHUC.2019.098472

International Journal of Ad Hoc and Ubiquitous Computing, 2019 Vol.30 No.3, pp.127 - 136

Received: 28 Jun 2016
Accepted: 06 Mar 2017

Published online: 25 Mar 2019 *

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