With the resource-constrained nature of mobile devices and the resource-abundant offerings of the cloud, several promising optimisation techniques have been proposed by the green computing research community. Prominent techniques and unique methods have been developed to offload resource intensive tasks from mobile devices to the cloud. Although these schemes address similar questions within the same domain of mobile cloud application (MCA) optimisation, evaluation is tailored to the scheme and also solely mobile focused, thus making it difficult to clearly compare with other existing counterparts. In this work, we first analyse the existing/commonly adopted evaluation technique, then with the aim to fill the above gap, we propose the behaviour-driven full-tier green evaluation approach, which adopts the behaviour-driven concept for evaluating MCA performance and energy usage—ie, green metrics. To automate the evaluation process, we also present and evaluate the effectiveness of a resultant application program interface and tool driven by the behaviour-driven full-tier green evaluation approach. The application program interface is based on Android and has been validated with Elastic Compute Cloud instance. Experiments show that Beftigre is capable of providing a more distinctive, comparable, and reliable green test results for MCAs.
Chinenyeze, S. J., Liu, X., & Al-Dubai, A. (2017). BEFTIGRE: Behaviour-driven full-tier green evaluation of mobile cloud applications. Journal of Software: Evolution and Process, 29(2), e1848. https://doi.org/10.1002/smr.1848