An Energy-Efficient Middleware for Computation Offloading in Real-Time Embedded Systems

2016 ◽  
Author(s):  
Anas Toma ◽  
Santiago Pagani ◽  
Jian-Jia Chen ◽  
Wolfgang Karl ◽  
Jorg Henkel
Keyword(s):  
Embedded Systems ◽  
Real Time ◽  
Energy Efficient ◽  
Computation Offloading

Designing energy-efficient NoC for real-time embedded systems through slack optimization

2013 ◽  
Author(s):  
Jia Zhan ◽  
Nikolay Stoimenov ◽  
Jin Ouyang ◽  
Lothar Thiele ◽  
Vijaykrishnan Narayanan ◽  
...  
Keyword(s):  
Embedded Systems ◽  
Real Time ◽  
Energy Efficient

Energy efficient scheduler of aperiodic jobs for real-time embedded systems

2016 ◽  
Vol 17 (5) ◽  
pp. 733-743 ◽  
Author(s):  
Hussein El Ghor ◽  
El-Hadi M. Aggoune
Keyword(s):  
Embedded Systems ◽  
Real Time ◽  
Energy Efficient

A Computation Offloading Framework for Soft Real-Time Embedded Systems

2015 ◽  
Author(s):  
Yuchuan Liu ◽  
Cong Liu ◽  
Xia Zhang ◽  
Wei Gao ◽  
Liang He ◽  
...  
Keyword(s):  
Embedded Systems ◽  
Real Time ◽  
Computation Offloading

scholarly journals Energy Efficient and Real-Time Remote Sensing in AI-Powered Drone

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Bongjae Kim ◽  
Jinman Jung ◽  
Hong Min ◽  
Junyoung Heo
Keyword(s):  
Remote Sensing ◽  
Energy Consumption ◽  
Data Analysis ◽  
Real Time ◽  
Energy Efficient ◽  
Urban Areas ◽  
Computation Offloading ◽  
Time Constraints ◽  
Time Data ◽  
Real Time Data

Remote sensing using drones has the advantage of being able to quickly monitor large areas such as rivers, oceans, mountains, and urban areas. In the case of applications dealing with large sensing data, it is not possible to send data from a drone to the server online, so it must be copied to the server offline after the end of the flight. However, online transmission is essential for applications that require real-time data analysis. The existing computation offloading scheme enables online transmission by processing large amounts of data in a drone and transferring it to the server, but without consideration for real-time constraints. We propose a novel computation offloading scheme which considers real-time constraints while minimizing the energy consumption of drones. Experimental results showed that the proposed scheme satisfied real-time constraints compared to the existing computation offloading scheme. Furthermore, the proposed technique showed that real-time constraints were satisfied even in situations where delays occurred on the server due to the processing of requests from multiple drones.

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