Energy-Aware Edge-Cloud Computation Offloading for Smart Connected Health

Author(s):  
Huned Materwala ◽  
Leila Ismail
IEEE Access ◽  
2017 ◽  
Vol 5 ◽  
pp. 23947-23957 ◽  
Author(s):  
Yucen Nan ◽  
Wei Li ◽  
Wei Bao ◽  
Flavia C. Delicato ◽  
Paulo F. Pires ◽  
...  

Author(s):  
Xiaobo Zhao ◽  
Minoo Hosseinzadeh ◽  
Nathaniel Hudson ◽  
Hana Khamfroush ◽  
Daniel E. Lucani

2015 ◽  
Vol 9 (2) ◽  
pp. 393-405 ◽  
Author(s):  
Ying-Dar Lin ◽  
Edward T.-H. Chu ◽  
Yuan-Cheng Lai ◽  
Ting-Jun Huang

Author(s):  
Byoung-Dai Lee ◽  
Kwang-Ho Lim ◽  
Namgi Kim

Smart connected devices such as smartphones and tablets are battery-operated to facilitate their mobility. Therefore, low power consumption is a critical requirement for mobile hardware and for the software designed for such devices. In addition to efficient power management techniques and new battery technologies based on nanomaterials, cloud computing has emerged as a promising technique for reducing energy consumption as well as augmenting the computational and memory capabilities of mobile devices. In this study, we designed and implemented a framework that allows for the energy-efficient execution of mobile applications by partially offloading the workload of a mobile device onto a resourceful cloud. This framework comprises a development toolkit, which facilitates the development of mobile applications capable of supporting computation offloading, and a runtime infrastructure for deployment in the cloud. Using this framework, we implemented three different mobile applications and demonstrated that considerable energy savings can be achieved compared with local processing for both resource-intensive and lightweight applications, especially when using high-speed networks such as Wi-Fi and Long-Term Evolution.


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