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Collaborative Task Offloading for Overloaded Mobile Edge Computing in Small-Cell Networks
- Source :
- ICOIN
- Publication Year :
- 2020
- Publisher :
- IEEE, 2020.
-
Abstract
- Mobile Edge Computing (MEC) enhances mobile cloud computing capabilities by fetching services close to the edge of the network, which adds 4C (Computing, Communication, Control and Caching) to the edges. MEC-enabled small cell network is regarded as the key technology in future 5G networks where for rapid task execution, a user offloads their tasks to the nearest small BS (SBS). The research work regarding MEC-enabled small cell network is still in its infancy. Recently, some researchers are trying to integrate MEC with small cell networks (SCNs) while ignoring the unlimited computation resource in a remote cloud and the computational capability of a single SBS-MEC server, which has the limited capacity for handling huge number of user request. To effectively handle latency-sensitive tasks and resources-hungry mobile applications in small-cell networks, two collaborative task offloading schemes of our proposed model is introduced in this paper. Our proposed collaborative model can make decision dynamically where the SBS-MEC server collaborate with mobile devices or remote cloud for executing the computation tasks. The simulation results confirm that collaborative task offloading between mobile with SBS-MEC scheme will reduce the average number of task failure more efficiently than other schemes and the collaborative task offloading between SBS-MEC with cloud scheme will provide lower task execution latency than others in small-cell networks.
- Subjects :
- 020203 distributed computing
Mobile edge computing
Computer science
business.industry
020206 networking & telecommunications
Cloud computing
02 engineering and technology
Mobile cloud computing
0202 electrical engineering, electronic engineering, information engineering
Computation offloading
Small cell
business
Mobile device
5G
Computer network
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2020 International Conference on Information Networking (ICOIN)
- Accession number :
- edsair.doi...........8c0454cf25689dfe43f8629287a9a7f0