Computation Offloading and Resource Allocation For Cloud Assisted Mobile Edge Computing in Vehicular Networks

By Junhui Zhao, Qiuping Li, Yi Gong, Ke Zhang. IEEE Transactions on Vehicular Technology, 2019

697 citations recorded by the source corpus.

Computation offloading services provide required computing resources for vehicles with computation-intensive tasks. Past computation offloading research mainly focused on mobile edge computing (MEC) or cloud computing, separately. This paper presents a collaborative approach based on MEC and cloud computing that offloads services to automobiles in vehicular networks. A cloud-MEC collaborative computation offloading problem is formulated through jointly optimizing computation offloading decision and computation resource allocation. Since the problem is non-convex and NP-hard, we propose a collaborative computation offloading and resource allocation optimization (CCORAO) scheme, and design a distributed computation offloading and resource allocation algorithm for CCORAO scheme that achieves the optimal solution. The simulation results show that the proposed algorithm can effectively improve the system utility and computation time, especially for the scenario where the MEC servers fail to meet demands due to insufficient computation resources.

Subfields: Artificial Intelligence, Computer Networks and Communications, Information Systems

View Paper: https://www.semanticscholar.org/paper/4f940cfbfa70c67ecb026478a8607fa7ec376220

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Ricky Y. K. Kwok
2. Lei Guo
3. Xiaojie Wang
4. Bin Hu
5. Kaiyuan Zhang
6. Xiping Hu
7. Zhaolong Ning
8. Weisong Shi

In Computer Networks and Communications

1. Mugen Peng
2. Zhaolong Ning
3. Weisong Shi

In Information Systems

1. Mugen Peng
2. Weisong Shi

Citations in the corpus

• Resource Scheduling in Edge Computing: A Survey (2021, methodology): “Finally, effective optimization algorithms are designed to maximize the utility [91], [108], [249], [252], [253].”
• Intelligent Edge Computing in Internet of Vehicles: A Joint Computation Offloading and Caching Solution (2021, background): “Road Side Units (RSUs) equipped with edge servers are able to serve vehicles within their coverages, which alleviate computing and backhaul pressures of the cloud server [4].”
• Toward Edge Intelligence: Multiaccess Edge Computing for 5G and Internet of Things (2020, background): “[68] designed a collaborative computation offloading scheme for an MECassisted connected vehicle scenarios.”