Combining Automated Measurement-Based Cost Modeling With Static Worst-Case Execution-Time and Energy-Consumption Analyses

2019 ◽  
Vol 11 (2) ◽  
pp. 38-41 ◽  
Author(s):  
Volkmar Sieh ◽  
Robert Burlacu ◽  
Timo Honig ◽  
Heiko Janker ◽  
Phillip Raffeck ◽  
...  
Author(s):  
Qingzhu Wang ◽  
Xiaoyun Cui

As mobile devices become more and more powerful, applications generate a large number of computing tasks, and mobile devices themselves cannot meet the needs of users. This article proposes a computation offloading model in which execution units including mobile devices, edge server, and cloud server. Previous studies on joint optimization only considered tasks execution time and the energy consumption of mobile devices, and ignored the energy consumption of edge and cloud server. However, edge server and cloud server energy consumption have a significant impact on the final offloading decision. This paper comprehensively considers execution time and energy consumption of three execution units, and formulates task offloading decision as a single-objective optimization problem. Genetic algorithm with elitism preservation and random strategy is adopted to obtain optimal solution of the problem. At last, simulation experiments show that the proposed computation offloading model has lower fitness value compared with other computation offloading models.


2021 ◽  
Author(s):  
Jessica Junia Santillo Costa ◽  
Romulo Silva de Oliveira ◽  
Luis Fernando Arcaro

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