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Sensors 2014, 14(3), 5392-5414; doi:10.3390/s140305392
Article

Maestro: An Orchestration Framework for Large-Scale WSN Simulations

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Received: 25 December 2013; in revised form: 10 March 2014 / Accepted: 12 March 2014 / Published: 18 March 2014
(This article belongs to the Section Physical Sensors)
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Abstract: Contemporary wireless sensor networks (WSNs) have evolved into large and complex systems and are one of the main technologies used in cyber-physical systems and the Internet of Things. Extensive research on WSNs has led to the development of diverse solutions at all levels of software architecture, including protocol stacks for communications. This multitude of solutions is due to the limited computational power and restrictions on energy consumption that must be accounted for when designing typical WSN systems. It is therefore challenging to develop, test and validate even small WSN applications, and this process can easily consume significant resources. Simulations are inexpensive tools for testing, verifying and generally experimenting with new technologies in a repeatable fashion. Consequently, as the size of the systems to be tested increases, so does the need for large-scale simulations. This article describes a tool called Maestro for the automation of large-scale simulation and investigates the feasibility of using cloud computing facilities for such task. Using tools that are built into Maestro, we demonstrate a feasible approach for benchmarking cloud infrastructure in order to identify cloud Virtual Machine (VM)instances that provide an optimal balance of performance and cost for a given simulation.
Keywords: wireless sensor networks; simulations; cloud computing; Amazon AWS wireless sensor networks; simulations; cloud computing; Amazon AWS
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Riliskis, L.; Osipov, E. Maestro: An Orchestration Framework for Large-Scale WSN Simulations. Sensors 2014, 14, 5392-5414.

AMA Style

Riliskis L, Osipov E. Maestro: An Orchestration Framework for Large-Scale WSN Simulations. Sensors. 2014; 14(3):5392-5414.

Chicago/Turabian Style

Riliskis, Laurynas; Osipov, Evgeny. 2014. "Maestro: An Orchestration Framework for Large-Scale WSN Simulations." Sensors 14, no. 3: 5392-5414.



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