EC-MOPSO: an edge computing-assisted hybrid cluster and MOPSO-based routing protocol for the Internet of Vehicles

Author(s):  
Melody Jamalzadeh ◽  
Mohsen Maadani ◽  
Mojdeh Mahdavi
2021 ◽  
Vol 59 (8) ◽  
pp. 52-57
Author(s):  
Jie Xu ◽  
F. Richard Yu ◽  
Jingyu Wang ◽  
Qi Qi ◽  
Haifeng Sun ◽  
...  

Author(s):  
Laizhong Cui ◽  
Ziteng Chen ◽  
Shu Yang ◽  
Zhongxing Ming ◽  
Qi Li ◽  
...  

IEEE Network ◽  
2021 ◽  
Vol 35 (3) ◽  
pp. 72-73
Author(s):  
Jun Huang ◽  
Jalel Ben Othman ◽  
Shiqiang Wang ◽  
Ricky Y. K. Kwok ◽  
Victor C. M. Leung ◽  
...  

2021 ◽  
pp. 47-64
Author(s):  
Yan Zhang

AbstractThe advancement of cyber physical information has led to the pervasive use of smart vehicles while enabling various types of powerful mobile applications, which usually require high-intensity processing under strict delay constraints. Given their limited on-board computing capabilities, smart vehicles can offload these processing tasks to edge servers for execution. However, a highly dynamic topology, a complex vehicular communication environment, and edge node heterogeneity pose significant challenges in vehicular edge computing management. To address these challenges, in this chapter we investigate the characteristics of edge computing from both the application and service perspectives and introduce a hierarchical edge computing framework. Moreover, we leverage artificial intelligence technology to propose efficient task offloading and resource scheduling schemes.


IEEE Network ◽  
2019 ◽  
Vol 33 (4) ◽  
pp. 48-53 ◽  
Author(s):  
Celimuge Wu ◽  
Xianfu Chen ◽  
Tsutomu Yoshinaga ◽  
Yusheng Ji ◽  
Yan Zhang

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3785
Author(s):  
Ali Tufail ◽  
Abdallah Namoun ◽  
Adnan Ahmed Abi Sen ◽  
Ki-Hyung Kim ◽  
Ahmed Alrehaili ◽  
...  

Recently, the concept of combining ‘things’ on the Internet to provide various services has gained tremendous momentum. Such a concept has also impacted the automotive industry, giving rise to the Internet of Vehicles (IoV). IoV enables Internet connectivity and communication between smart vehicles and other devices on the network. Shifting the computing towards the edge of the network reduces communication delays and provides various services instantly. However, both distributed (i.e., edge computing) and central computing (i.e., cloud computing) architectures suffer from several inherent issues, such as high latency, high infrastructure cost, and performance degradation. We propose a novel concept of computation, which we call moisture computing (MC) to be deployed slightly away from the edge of the network but below the cloud infrastructure. The MC-based IoV architecture can be used to assist smart vehicles in collaborating to solve traffic monitoring, road safety, and management issues. Moreover, the MC can be used to dispatch emergency and roadside assistance in case of incidents and accidents. In contrast to the cloud which covers a broader area, the MC provides smart vehicles with critical information with fewer delays. We argue that the MC can help reduce infrastructure costs efficiently since it requires a medium-scale data center with moderate resources to cover a wider area compared to small-scale data centers in edge computing and large-scale data centers in cloud computing. We performed mathematical analyses to demonstrate that the MC reduces network delays and enhances the response time in contrast to the edge and cloud infrastructure. Moreover, we present a simulation-based implementation to evaluate the computational performance of the MC. Our simulation results show that the total processing time (computation delay and communication delay) is optimized, and delays are minimized in the MC as apposed to the traditional approaches.


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