The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.
Mobile-Edge Computation Offloading for Ultradense IoT Networks
Abstract
The emergence of massive Internet of Things (IoT) mobile devices (MDs) and the deployment of ultradense 5G cells have promoted the evolution of IoT toward ultradense IoT networks. In order to meet the diverse quality-of-service and quality of experience demands from the ever-increasing IoT applications, the ultradense IoT networks face unprecedented challenges. Among them, a fundamental one is how to address the conflict between the resource-hungry IoT mobile applications and the resource-constrained IoT MDs. By offloading the IoT MDs’ computation tasks to the edge servers deployed at the radio access infrastructures, including macro base station (MBS) and small cells, mobile-edge computation offloading (MECO) provides us a promising solution. However, note that available MECO research mostly focused on single-tier base station scenario and computation offloading between the MDs and the edge server connected to the MBS. Little works can be found on performing MECO in ultradense IoT networks, i.e., a multiuser ultradense edge server scenario. Toward this end, we provide this paper to study the MECO problem in ultradense IoT networks, and propose a two-tier game-theoretic greedy offloading scheme as our solution. Extensive numerical results corroborate the superior performance of conducting computation offloading among multiple edge servers in ultradense IoT networks.
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Cites
Equilibrium points in n -person games
Nash, J. F. (1950) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.36.1.48 · Cited by 7,560
Monderer, D., & Shapley, L. S. (1996) · Games and Economic Behavior · doi:10.1006/game.1996.0044 · Cited by 3,543
Mobile Edge Computing: A Survey
Abbas, N., Zhang, Y., Taherkordi, A., & Skeie, T. (2018) · IEEE Internet of Things Journal · doi:10.1109/jiot.2017.2750180 · Cited by 2,474
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
Research Directions for the Internet of Things
Stankovic, J. A. (2014) · IEEE Internet of Things Journal · doi:10.1109/jiot.2014.2312291 · Cited by 1,920
(2011) · doi:10.1145/1966445.1966473 · Cited by 1,870
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-citationTask Offloading for Mobile Edge Computing in Software Defined Ultra-Dense Network
Chen, M., & Hao, Y. (2018) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2018.2815360 · Cited by 1,068
Ultra-Dense Networks: A Survey
Kamel, M., Hamouda, W., & Youssef, A. (2016) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2016.2571730 · Cited by 919
Joint Optimization of Radio and Computational Resources for Multicell Mobile-Edge Computing
Sardellitti, S., Scutari, G., & Barbarossa, S. (2015) · IEEE Transactions on Signal and Information Processing over Networks · doi:10.1109/tsipn.2015.2448520 · Cited by 891
Cited by
Wu, Y., Ni, K., Zhang, C., Qian, L. P., & Tsang, D. H. K. (2018) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2018.2875337 · Cited by 292
When Machine Learning Meets Privacy in 6G: A Survey
Sun, Y., Liu, J., Wang, J., Cao, Y., & Kato, N. (2020) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2020.3011561 · Cited by 211
Self-citationLin, X., Li, J., Wu, J., Liang, H., & Yang, W. (2019) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2019.2917307 · Cited by 192
Privacy-preserved task offloading in mobile blockchain with deep reinforcement learning
Nguyen, D. C., Pathirana, P. N., Ding, M., & Seneviratne, A. (2020) · IEEE Transactions on Network and Service Management · doi:10.1109/tnsm.2020.3010967 · Cited by 178
HetMEC: Heterogeneous Multi-Layer Mobile Edge Computing in the 6 G Era
Zhang, Y., Di, B., Wang, P., Lin, J., & Song, L. (2020) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2020.2975559 · Cited by 74
Metadata
- Authors
- Guo, H., Liu, J., Zhang, J., Sun, W., & Kato, N.
- Venue
- IEEE Internet of Things Journal
- Published
- 2018-12
- Volume
- 5
- Issue
- 6
- Pages
- 4977-4988
- ISSN
- 2327-4662 (ISSN-L)
- 2372-2541
- OpenAlex
- W2804985843
- Cited by
- 308
- References
- 36
- FWCI
- 30.03
- Type
- journal article
- Language
- en
- Open access
- closed
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- Guo, H., Liu, J., Zhang, J., Sun, W., & Kato, N. (2018). Mobile-Edge Computation Offloading for Ultradense IoT Networks. IEEE Internet of Things Journal. https://doi.org/10.1109/jiot.2018.2838584
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