The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Mobile-Edge Computing: Partial Computation Offloading Using Dynamic Voltage Scaling
Abstract
The incorporation of dynamic voltage scaling technology into computation offloading offers more flexibilities for mobile edge computing. In this paper, we investigate partial computation offloading by jointly optimizing the computational speed of smart mobile device (SMD), transmit power of SMD, and offloading ratio with two system design objectives: energy consumption of SMD minimization (ECM) and latency of application execution minimization (LM). Considering the case that the SMD is served by a single cloud server, we formulate both the ECM problem and the LM problem as nonconvex problems. To tackle the ECM problem, we recast it as a convex one with the variable substitution technique and obtain its optimal solution. To address the nonconvex and nonsmooth LM problem, we propose a locally optimal algorithm with the univariate search technique. Furthermore, we extend the scenario to a multiple cloud servers system, where the SMD could offload its computation to a set of cloud servers. In this scenario, we obtain the optimal computation distribution among cloud servers in closed form for the ECM and LM problems. Finally, extensive simulations demonstrate that our proposed algorithms can significantly reduce the energy consumption and shorten the latency with respect to the existing offloading schemes.
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Boyd, S., & Vandenberghe, L. (2004) · doi:10.1017/cbo9780511804441 · Cited by 56,601
MAUI: making smartphones last longer with code offload
Cuervo, E., Balasubramanian, A., Cho, D.-K., Wolman, A., Saroiu, S., Chandra, R., & Bahl, P. (2010) · Proceedings of the 8th international conference on Mobile systems, applications, and services · doi:10.1145/1814433.1814441 · Cited by 2,281
(2011) · doi:10.1145/1966445.1966473 · Cited by 1,870
Cited by
A Survey on Mobile Edge Computing: The Communication Perspective
Mao, Y., You, C., Zhang, J., Huang, K., & Letaief, K. B. (2017) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2017.2745201 · Cited by 5,607
Mobile Edge Computing: A Survey on Architecture and Computation Offloading
Mach, P., & Becvar, Z. (2017) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2017.2682318 · Cited by 3,258
A Survey on the Edge Computing for the Internet of Things
Yu, W., Liang, F., He, X., Hatcher, W. G., Lu, C., Lin, J., & Yang, X. (2018) · IEEE Access · doi:10.1109/access.2017.2778504 · Cited by 1,520
A Survey on Mobile Edge Networks: Convergence of Computing, Caching and Communications
Wang, S., Zhang, X., Zhang, Y., Wang, L., YANG, J., & Wang, W. (2017) · IEEE Access · doi:10.1109/access.2017.2685434 · Cited by 952
Self-citationCollaborative Cloud and Edge Computing for Latency Minimization
Ren, J., Yu, G., He, Y., & Li, G. Y. (2019) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2019.2904244 · Cited by 685
Metadata
- Authors
- Wang, Y., Sheng, M., Wang, X., Wang, L., & Li, J.
- Venue
- IEEE Transactions on Communications
- Published
- 2016
- Pages
- 1-1
- ISSN
- 0090-6778 (ISSN-L)
- OpenAlex
- W2516316490
- Cited by
- 1,002
- References
- 3
- FWCI
- 74.85
- Type
- journal article
- Language
- en
- Open access
- closed
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- Wang, Y., Sheng, M., Wang, X., Wang, L., & Li, J. (2016). Mobile-Edge Computing: Partial Computation Offloading Using Dynamic Voltage Scaling. IEEE Transactions on Communications. https://doi.org/10.1109/tcomm.2016.2599530
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