Abstract
In vehicular edge computing (VEC), resource-intensive tasks are offloaded to computing nodes at the network edge. Owing to high mobility and distributed nature, optimal task offloading in vehicular environments is still a challenging problem. In this paper, we first introduce a software-defined vehicular edge computing (SD-VEC) architecture where a controller not only guides the vehicles' task offloading strategy but also determines the edge cloud resource allocation strategy. To obtain the optimal strategies, we formulate a problem on the edge cloud selection and resource allocation to maximize the probability that a task is successfully completed within a pre-specified time limit. Since the formulated problem is a well-known NP-hard problem, we devise a mobility-aware greedy algorithm (MGA) that determines the amount of edge cloud resources allocated to each vehicle. Trace-driven simulation results demonstrate that MGA provides near-optimal performance and improves the successful task execution probability compared with conventional algorithms.
Original language | English |
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Title of host publication | 9th International Conference on Information and Communication Technology Convergence |
Subtitle of host publication | ICT Convergence Powered by Smart Intelligence, ICTC 2018 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 251-256 |
Number of pages | 6 |
ISBN (Electronic) | 9781538650400 |
DOIs | |
Publication status | Published - 2018 Nov 16 |
Event | 9th International Conference on Information and Communication Technology Convergence, ICTC 2018 - Jeju Island, Korea, Republic of Duration: 2018 Oct 17 → 2018 Oct 19 |
Publication series
Name | 9th International Conference on Information and Communication Technology Convergence: ICT Convergence Powered by Smart Intelligence, ICTC 2018 |
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Other
Other | 9th International Conference on Information and Communication Technology Convergence, ICTC 2018 |
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Country/Territory | Korea, Republic of |
City | Jeju Island |
Period | 18/10/17 → 18/10/19 |
Bibliographical note
Funding Information:ACKNOWLEDGMENT This research was supported in part by National Research Foundation (NRF) of Korea Grant funded by the Korean Government (MSIP) (No. 2017R1E1A1A01073742) and in part by the MSIT(Ministry of Science and ICT), Korea, under the ITRC(Information Technology Research Center) support program (IITP-2018-2017-0-01633) supervised by the IITP(Institute for Information & communications Technology Promotion).
Publisher Copyright:
© 2018 IEEE.
Keywords
- software-defined network (SDN)
- task offloading
- vehicular edge computing (VEC)
ASJC Scopus subject areas
- Computer Networks and Communications
- Computer Science Applications
- Information Systems
- Information Systems and Management
- Artificial Intelligence