Proactive load balancing mechanism for fog computing supported by parked vehicles in IoV-SDN

Internet of Vehicles (IoV) is a new style of vehicular ad hoc network that is used to connect the sensors of each vehicle with each other and with other vehicles' sensors through the internet. These sensors generate different tasks that should be analyzed and processed in some given period of t...

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Bibliographic Details
Published in:China communications 2021-02, Vol.18 (2), p.271-289
Main Authors: Kadhim, Ahmed Jawad, Naser, Jaber Ibrahim
Format: Article
Language:English
Subjects:
Bandwidth
Cloud computing
Edge computing
fog computing
IoV
load balancing
Load management
parked vehicles
SDN
Sensors
Servers
Task analysis
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Summary:Internet of Vehicles (IoV) is a new style of vehicular ad hoc network that is used to connect the sensors of each vehicle with each other and with other vehicles' sensors through the internet. These sensors generate different tasks that should be analyzed and processed in some given period of time. They send the tasks to the cloud servers but these sending operations increase bandwidth consumption and latency. Fog computing is a simple cloud at the network edge that is used to process the jobs in a short period of time instead of sending them to cloud computing facilities. In some situations, fog computing cannot execute some tasks due to lack of resources. Thus, in these situations it transfers them to cloud computing that leads to an increase in latency and bandwidth occupation again. Moreover, several fog servers may be fuelled while other servers are empty. This implies an unfair distribution of jobs. In this research study, we shall merge the software defined network (SDN) with IoV and fog computing and use the parked vehicle as assistant fog computing node. This can improve the capabilities of the fog computing layer and help in decreasing the number of migrated tasks to the cloud servers. This increases the ratio of time sensitive tasks that meet the deadline. In addition, a new load balancing strategy is proposed. It works proactively to balance the load locally and globally by the local fog managers and SDN controller, respectively. The simulation experiments show that the proposed system is more efficient than VANET-Fog-Cloud and IoV-Fog-Cloud frameworks in terms of average response time and percentage of bandwidth consumption, meeting the deadline, and resource utilization.
ISSN:1673-5447
DOI:10.23919/JCC.2021.02.019