Modeling, Estimating, and Optimizing Software Energy Consumption in Mobile Cloud Computing - Li; Zheng (2023)
2 Formulate a scientific knowledge framework of software energy consumption in mobile Cloud computing, based on a generic energy concern architecture. PARCIAL After identifying the factor-to-factor dynamics, we realized that building up a full-scope scientific knowledge framework of software energy consumption would be too ambitious. To make this project finish-able within reasonable and predefined time window (i.e. three years), I had to focus on particular application characteristics and energy consumption factors. For example, the data communication with respect to network energy consumption has been particularly emphasized. On the other hand, I still managed to investigate the knowledge architecture in a generic sense. To make this part of work publishable, I intentionally changed the context into "data science" for a publication, although this work was actually done in the context of "energy consumption": - Zheng Li. On a Factorial Knowledge Architecture for Data Science-powered Software Engineering. Proceedings of the 4th International Conference on Software and e-Business (ICSEB 2020), pp. 20-24, Osaka, Japan, December 18-20, 2020. 3 Develop and validate model-driven approaches to estimating software energy consumption for particular types of mobile Cloud applications. TOTAL After analyzing the software activities that have influences on the energy consumption, I focused on the data communication within a mobile cloud application. According to our empirical investigation, the energy consumption of data communication has a strong positive proportional relationship with the time consumption. Therefore I have focused on the time efficienty to study the energy efficiency. The representative publications include: - Zheng Li and Francisco Millar-Bilbao. Characterizing the Cloud's Outbound Network Latency: An Experimental and Modeling Study. Proceedings of the 2020 IEEE Cloud Summit (CloudSummit 2020), pp. 172-173, Harrisburg, PA, USA, October 21-22, 2020. - Zheng Li, Francisco Millar-Bilbao, Gonzalo Rojas-Durán ...