The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
Delay-optimal computation task scheduling for mobile-edge computing systems
Open accessAbstract
Mobile-edge computing (MEC) emerges as a promising paradigm to improve the quality of computation experience for mobile devices. Nevertheless, the design of computation task scheduling policies for MEC systems inevitably encounters a challenging two-timescale stochastic optimization problem. Specifically, in the larger timescale, whether to execute a task locally at the mobile device or to offload a task to the MEC server for cloud computing should be decided, while in the smaller timescale, the transmission policy for the task input data should adapt to the channel side information. In this paper, we adopt a Markov decision process approach to handle this problem, where the computation tasks are scheduled based on the queueing state of the task buffer, the execution state of the local processing unit, as well as the state of the transmission unit. By analyzing the average delay of each task and the average power consumption at the mobile device, we formulate a power-constrained delay minimization problem, and propose an efficient one-dimensional search algorithm to find the optimal task scheduling policy. Simulation results are provided to demonstrate the capability of the proposed optimal stochastic task scheduling policy in achieving a shorter average execution delay compared to the baseline policies.
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Self-citationConstrained Markov Decision Processes: Stochastic Modeling
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A Survey of Computation Offloading for Mobile Systems
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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
Self-citationMobile Edge Computing: A Survey on Architecture and Computation Offloading
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Dynamic computation offloading for mobile-edge computing with energy harvesting devices
Mao, Y., Zhang, J., & Letaief, K. B. (2016) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2016.2611964 · Cited by 1,705
Self-citationA Survey on the Edge Computing for the Internet of Things
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A Survey on Mobile Edge Networks: Convergence of Computing, Caching and Communications
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Metadata
- Authors
- Liu, J., Mao, Y., Zhang, J., & Letaief, K. B.
- Venue
- 2016 IEEE International Symposium on Information Theory (ISIT)
- Publisher
- IEEE
- Published
- 2016-07
- Pages
- 1451-1455
- OpenAlex
- W2344423009
- Cited by
- 759
- References
- 13
- FWCI
- 73.62
- Type
- conference paper
- Language
- en
- Open access
- green
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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).
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