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Edge-CoCaCo: Toward Joint Optimization of Computation, Caching, and Communication on Edge Cloud
Abstract
With the development of recent innovative applications (e.g., augmented reality, natural language processing, and various cognitive applications), more and more computation-intensive and rich-media tasks are delay-sensitive. Edge cloud computing is expected to be an effective solution to meet the demand for low latency. By the use of content offloading and/or computation offloading, users' quality of experience is improved with shorter delay. Compared to existing edge computing solutions, this article introduces a new concept of computing task caching and gives the optimal computing task caching policy. Furthermore, joint optimization of computation, caching, and communication on the edge cloud, dubbed Edge-CoCaCo, is proposed. Then we give the solution to that optimization problem. Finally, the simulation experimental results show that compared to the other schemes, Edge-CoCaCo has shorter delay.
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Cites
Edge computing: Vision and challenges
Shi, W., Cao, J., Zhang, Q., Li, Y., & Xu, L. (2016) · IEEE Internet of Things Journal · doi:10.1109/jiot.2016.2579198 · Cited by 8,733
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Metadata
- Authors
- Chen, M., Hao, Y., Hu, L., Hossain, M. S., & Ghoneim, A.
- Venue
- IEEE Wireless Communications
- Published
- 2018-06
- Volume
- 25
- Issue
- 3
- Pages
- 21-27
- ISSN
- 1536-1284 (ISSN-L)
- 1558-0687
- OpenAlex
- W2845644909
- Cited by
- 158
- References
- 1
- FWCI
- 16.96
- Type
- journal article
- Language
- en
- Open access
- closed
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- Chen, M., Hao, Y., Hu, L., Hossain, M. S., & Ghoneim, A. (2018). Edge-CoCaCo: Toward Joint Optimization of Computation, Caching, and Communication on Edge Cloud. IEEE Wireless Communications. https://doi.org/10.1109/mwc.2018.1700308
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
