Deadline Aware and Energy-Efficient Scheduling Algorithm for Fine-Grained Tasks in Mobile Edge Computing

2022 ◽  
Vol 18 (2) ◽  
pp. 1
Author(s):  
Seifedine Kadry ◽  
Karrar Hameed Abdulkareem ◽  
Abdullah Lakhan ◽  
Mazin Abed Mohammed ◽  
Ahmed N. Rashid
Keyword(s):  
Energy Efficient ◽  
Scheduling Algorithm ◽  
Edge Computing ◽  
Mobile Edge Computing ◽  
Fine Grained ◽  
Energy Efficient Scheduling

Mobile Edge Computing-Enabled Internet of Vehicles: Toward Energy-Efficient Scheduling

IEEE Network ◽  
2019 ◽  
Vol 33 (5) ◽  
pp. 198-205 ◽  
Author(s):  
Zhaolong Ning ◽  
Jun Huang ◽  
Xiaojie Wang ◽  
Joel J. P. C. Rodrigues ◽  
Lei Guo
Keyword(s):  
Energy Efficient ◽  
Edge Computing ◽  
Mobile Edge Computing ◽  
Internet Of Vehicles ◽  
Energy Efficient Scheduling

scholarly journals A cost efficient model for minimizing energy consumption and processing time for IoT tasks in a Mobile Edge Computing environment

2020 ◽  
Author(s):  
João Luiz Grave Gross ◽  
Cláudio Fernando Fernando Resin Geyer
Keyword(s):  
Energy Consumption ◽  
Cost Minimization ◽  
Cost Model ◽  
Scheduling Algorithm ◽  
Edge Computing ◽  
Mobile Edge Computing ◽  
Total Energy Consumption ◽  
Data Intensive ◽  
Battery Capacity ◽  
Cost Efficient

In a scenario with increasingly mobile devices connected to the Internet, data-intensive applications and energy consumption limited by battery capacity, we propose a cost minimization model for IoT devices in a Mobile Edge Computing (MEC) architecture with the main objective of reducing total energy consumption and total elapsed times from task creation to conclusion. The cost model is implemented using the TEMS (Time and Energy Minimization Scheduler) scheduling algorithm and validated with simulation. The results show that it is possible to reduce the energy consumed in the system by up to 51.61% and the total elapsed time by up to 86.65% in the simulated cases with the parameters and characteristics defined in each experiment.

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