TY - JOUR
T1 - An Energy Aware Offloading Scheme for Interdependent Applications in Software-Defined IoV with Fog Computing Architecture
AU - Zhai, Yanlong
AU - Sun, Wenxin
AU - Wu, Jianqing
AU - Zhu, Liehuang
AU - Shen, Jun
AU - Du, Xiaojiang
AU - Guizani, Mohsen
N1 - Publisher Copyright:
© 2000-2011 IEEE.
PY - 2021/6
Y1 - 2021/6
N2 - The Internet of Vehicles (IoV) is one important application scenarios for the development of the Internet of things. The software-defined network (SDN) and fog computing could effectively improve the IoV network dynamics, which enables the application to achieve better performance by offloading some tasks to fog node or cloud center. Current computation offloading approaches for IoV and fog computing mostly focus on resource utilization. However, the energy-aware offloading has not been adequately addressed, especially for IoV systems with many battery-powered roadside units (RSU) and electric vehicles (EV). In this paper, we study the offloading problem in SDN and fog computing-based IoV systems. An energy-aware dynamic offloading scheme is proposed to prolong the running time of the IoV system by leveraging available battery power to execute more applications. The remaining battery power is defined as a dynamic weight factor in the execution cost model to adjust the optimization objective. Meanwhile, the dependence between applications is also taken into consideration in the cost model. A heuristic optimization algorithm is designed to solve the optimization problem. We conducted comprehensive experiments and results have shown that the offloading scheme could execute more applications with the available battery power under the constraints of application dependence.
AB - The Internet of Vehicles (IoV) is one important application scenarios for the development of the Internet of things. The software-defined network (SDN) and fog computing could effectively improve the IoV network dynamics, which enables the application to achieve better performance by offloading some tasks to fog node or cloud center. Current computation offloading approaches for IoV and fog computing mostly focus on resource utilization. However, the energy-aware offloading has not been adequately addressed, especially for IoV systems with many battery-powered roadside units (RSU) and electric vehicles (EV). In this paper, we study the offloading problem in SDN and fog computing-based IoV systems. An energy-aware dynamic offloading scheme is proposed to prolong the running time of the IoV system by leveraging available battery power to execute more applications. The remaining battery power is defined as a dynamic weight factor in the execution cost model to adjust the optimization objective. Meanwhile, the dependence between applications is also taken into consideration in the cost model. A heuristic optimization algorithm is designed to solve the optimization problem. We conducted comprehensive experiments and results have shown that the offloading scheme could execute more applications with the available battery power under the constraints of application dependence.
KW - Fog computing
KW - IoV
KW - SDN
KW - battery life
KW - offloading
UR - http://www.scopus.com/inward/record.url?scp=85099098343&partnerID=8YFLogxK
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U2 - 10.1109/TITS.2020.3044177
DO - 10.1109/TITS.2020.3044177
M3 - Article
AN - SCOPUS:85099098343
SN - 1524-9050
VL - 22
SP - 3813
EP - 3823
JO - IEEE Transactions on Intelligent Transportation Systems
JF - IEEE Transactions on Intelligent Transportation Systems
IS - 6
M1 - 9310716
ER -