BigDataSDNSim: A Simulator for Analyzing Big Data Applications in Software-Defined Cloud Data Centers
Khaled Alwasel, Rodrigo N. Calheiros, Saurabh Garg, Rajkumar Buyya,, Rajiv Ranjan

TL;DR
BigDataSDNSim is a simulation tool designed to model and analyze big data applications and SDN-enabled networks in cloud data centers, enabling cost-effective performance evaluation.
Contribution
The paper introduces BigDataSDNSim, a novel simulation platform for modeling big data systems and SDN networks within cloud environments, addressing the need for scalable testing tools.
Findings
SDN networks outperform legacy networks in performance.
SDN networks consume less energy.
Simulation results validate the effectiveness of BigDataSDNSim.
Abstract
Emerging paradigms of big data and Software-Defined Networking (SDN) in cloud data centers have gained significant attention from industry and academia. The integration and coordination of big data and SDN are required to improve the application and network performance of big data applications. While empirical evaluation and analysis of big data and SDN can be one way of observing proposed solutions, it is often impractical or difficult to apply for several reasons, such as expensive undertakings, time consuming, and complexity; in addition, it is beyond the reach of most individuals. Thus, simulation tools are preferable options for performing costeffective, scalable experimentation in a controllable, repeatable, and configurable manner. To fill this gap, we present a new, self-contained simulation tool named BigDataSDNSim that enables the modeling and simulating of big data management…
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