The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Energy-optimal mobile application execution: Taming resource-poor mobile devices with cloud clones
Abstract
In this paper, we propose to leverage cloud computing to tame resource-poor mobile devices. Specifically, mobile applications can be executed in the mobile device (known as mobile execution) or offloaded to the cloud clone for execution (known as cloud execution), with an objective to conserve energy for mobile device. The energy-optimal execution policy is obtained by solving two constrained optimization problems, i.e., how to optimally configure the clock frequency to complete CPU cycles for mobile execution, and how to optimally schedule the data transmission for cloud execution in order to achieve the minimal energy within time delay. Closed-form solutions are obtained for both cases and applied to decide the optimal condition under whether the local execution or the remote execution is more energy-efficient for the mobile device. Moreover, numerical results illustrate that a significant amount of energy (e.g., up to 13 times for a typical mobile application profile) can be saved by optimally offloading the mobile application to the cloud clone.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The case for vm-based cloudlets in mobile computing
Satyanarayanan, M., Bahl, P., Caceres, R., & Davies, N. (2009) · IEEE Pervasive Computing · doi:10.1109/mprv.2009.82 · Cited by 3,660
(2011) · doi:10.1145/1966445.1966473 · Cited by 1,870
Cited by
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
Efficient multi-user computation offloading for mobile-edge cloud computing
Chen, X., Jiao, L., Li, W., & Fu, X. (2016) · IEEE/ACM Transactions on Networking · doi:10.1109/tnet.2015.2487344 · Cited by 2,675
Joint Task Offloading and Resource Allocation for Multi-Server Mobile-Edge Computing Networks
Tran, T. X., & Pompili, D. (2019) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2018.2881191 · Cited by 1,046
Decentralized Computation Offloading Game for Mobile Cloud Computing
Chen, X. (2015) · IEEE Transactions on Parallel and Distributed Systems · doi:10.1109/tpds.2014.2316834 · Cited by 872
Deep reinforcement learning based computation offloading and resource allocation for MEC
Li, J., Gao, H., Lv, T., & Lu, Y. (2018) · 2018 IEEE Wireless Communications and Networking Conference (WCNC) · doi:10.1109/wcnc.2018.8377343 · Cited by 548
Metadata
- Authors
- Wen, Y., Zhang, W., & Luo, H.
- Venue
- 2012 Proceedings IEEE INFOCOM
- Publisher
- IEEE
- Published
- 2012-03
- Pages
- 2716-2720
- OpenAlex
- W2069211379
- Cited by
- 394
- References
- 2
- FWCI
- 21.82
- Type
- conference paper
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Energy-optimal mobile application execution: Taming resource-poor mobile devices with cloud clones. https://app.cochat.ai/papers/10.1109/infcom.2012.6195685
- The paper
- Wen, Y., Zhang, W., & Luo, H. (2012). Energy-optimal mobile application execution: Taming resource-poor mobile devices with cloud clones. 2012 Proceedings IEEE INFOCOM. https://doi.org/10.1109/infcom.2012.6195685
Data sources
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.
