Skip to main content

2020 | OriginalPaper | Buchkapitel

Efficient Multi-user Computation Scheduling Strategy Based on Clustering for Mobile-Edge Computing

verfasst von : Qing-Yan Lin, Guang-Shun Li, Jun-Hua Wu, Ying Zhang, JiaHe Yan

Erschienen in: Cloud Computing, Smart Grid and Innovative Frontiers in Telecommunications

Verlag: Springer International Publishing

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

The Mobile Edge Computing (MEC) is a new paradigm that can meet the growing computing needs of mobile applications. Terminal devices can transfer tasks to MEC servers nearby to improve the quality of computing. In this paper, we investigate the multi-user computation offloading problem for mobile-edge computing. We study two different computation models, local computing and edge computing. First, we drive the expressions for time delay and energy consumption for local and edge computing. Then, we propose a server partitioning algorithm based on clustering. We propose a task scheduling and offloading algorithm in a multi-users MEC system. We formulate the tasks offloading decision problem as a multi-user game, which always has a Nash equilibrium. Our proposed algorithms are finally verified by numerical results, which show that the scheduling strategy based on clustering can significantly reduce the energy consumption and overhead.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literatur
1.
Zurück zum Zitat Mao, Y., Zhang, J., Letaief, K.B.: Dynamic computation offloading for mobile-edge computing with energy harvesting devices. IEEE J. Sel. Areas Commun. 34, 3590–3605 (2016)CrossRef Mao, Y., Zhang, J., Letaief, K.B.: Dynamic computation offloading for mobile-edge computing with energy harvesting devices. IEEE J. Sel. Areas Commun. 34, 3590–3605 (2016)CrossRef
2.
Zurück zum Zitat Wang, S., et al.: A survey on mobile edge networks: convergence of computing, caching and communications. IEEE Access 5, 6757–6779 (2017)CrossRef Wang, S., et al.: A survey on mobile edge networks: convergence of computing, caching and communications. IEEE Access 5, 6757–6779 (2017)CrossRef
3.
Zurück zum Zitat Jin, L., Li, S., Yu, J.G., He, J.B.: Robot manipulator control using neural networks: a survey. Neurocomputing 285, 23–34 (2018)CrossRef Jin, L., Li, S., Yu, J.G., He, J.B.: Robot manipulator control using neural networks: a survey. Neurocomputing 285, 23–34 (2018)CrossRef
4.
Zurück zum Zitat Shahzadi, S., Iqbal, M., Dagiuklas, T., Qayyum, Z.U.: Multi-access edge computing: open issues, challenges and future perspective. J. Cloud Comput. 6(1), 30 (2017)CrossRef Shahzadi, S., Iqbal, M., Dagiuklas, T., Qayyum, Z.U.: Multi-access edge computing: open issues, challenges and future perspective. J. Cloud Comput. 6(1), 30 (2017)CrossRef
5.
Zurück zum Zitat Zhang, K., et al.: Energy-efficient offloading for mobile edge computing in 5G heterogeneous networks. IEEE Access 4, 5896–5907 (2016)CrossRef Zhang, K., et al.: Energy-efficient offloading for mobile edge computing in 5G heterogeneous networks. IEEE Access 4, 5896–5907 (2016)CrossRef
6.
Zurück zum Zitat Corcoran, P., Datta, S.K.: Mobile-edge computing and the internet of things for consumers: extending cloud computing and services to the edge of the network. IEEE Consum. Electron. Mag. 5(4), 73–74 (2016)CrossRef Corcoran, P., Datta, S.K.: Mobile-edge computing and the internet of things for consumers: extending cloud computing and services to the edge of the network. IEEE Consum. Electron. Mag. 5(4), 73–74 (2016)CrossRef
7.
Zurück zum Zitat Qi, L.Y., et al.: A two-stage locality-sensitive hashing based approach for privacy-preserving mobile service recommendation in cross-platform edge environment. Futur. Gener. Comp. Syst. 88, 636–643 (2018)CrossRef Qi, L.Y., et al.: A two-stage locality-sensitive hashing based approach for privacy-preserving mobile service recommendation in cross-platform edge environment. Futur. Gener. Comp. Syst. 88, 636–643 (2018)CrossRef
8.
Zurück zum Zitat Li, Y., Wang, S.: An energy-aware edge server placement algorithm in mobile edge computing. In: 2018 IEEE International Conference on Edge Computing (EDGE), San Francisco, pp. 66–73 (2018) Li, Y., Wang, S.: An energy-aware edge server placement algorithm in mobile edge computing. In: 2018 IEEE International Conference on Edge Computing (EDGE), San Francisco, pp. 66–73 (2018)
9.
Zurück zum Zitat Zeng, D., Gu, L., Guo, S., Cheng, Z., Yu, S.: Joint optimization of task scheduling and image placement in fog computing supported software-defined embedded system. IEEE Trans. Comput. 65(12), 3702–3712 (2016)MathSciNetCrossRef Zeng, D., Gu, L., Guo, S., Cheng, Z., Yu, S.: Joint optimization of task scheduling and image placement in fog computing supported software-defined embedded system. IEEE Trans. Comput. 65(12), 3702–3712 (2016)MathSciNetCrossRef
10.
Zurück zum Zitat Song, N., Gong, C., Xingshuo, A.N., Zhan, Q.: Fog computing dynamic load balancing mechanism based on graph repartitioning. China Commun. 13(3), 156–164 (2016)CrossRef Song, N., Gong, C., Xingshuo, A.N., Zhan, Q.: Fog computing dynamic load balancing mechanism based on graph repartitioning. China Commun. 13(3), 156–164 (2016)CrossRef
11.
Zurück zum Zitat Mebrek, A., Merghem-Boulahia, L., Esseghir, M.: Efficient green solution for a balanced energy consumption and delay in the IoT-Fog-Cloud computing. In: IEEE International Symposium on Network Computing and Applications, pp. 1–4 (2017) Mebrek, A., Merghem-Boulahia, L., Esseghir, M.: Efficient green solution for a balanced energy consumption and delay in the IoT-Fog-Cloud computing. In: IEEE International Symposium on Network Computing and Applications, pp. 1–4 (2017)
12.
Zurück zum Zitat Chen, X., Jiao, L., Li, W., Fu, X.: Efficient multi-user computation offloading for mobile-edge cloud computing. IEEE/ACM Trans. Networking 24(5), 2795–2808 (2016)CrossRef Chen, X., Jiao, L., Li, W., Fu, X.: Efficient multi-user computation offloading for mobile-edge cloud computing. IEEE/ACM Trans. Networking 24(5), 2795–2808 (2016)CrossRef
13.
Zurück zum Zitat Qi, L.Y., Yu, J.G., Zhou, Z.L.: An invocation cost optimization method for web services in cloud environment. Sci. Program. 2017, 9 (2017) Qi, L.Y., Yu, J.G., Zhou, Z.L.: An invocation cost optimization method for web services in cloud environment. Sci. Program. 2017, 9 (2017)
14.
Zurück zum Zitat Chen, M.H., Liang, B., Min, D.: Joint offloading decision and resource allocation for multi-user multi-task mobile cloud. In: IEEE International Conference on Communications, Kuala Lumpur, pp. 1–6 (2016) Chen, M.H., Liang, B., Min, D.: Joint offloading decision and resource allocation for multi-user multi-task mobile cloud. In: IEEE International Conference on Communications, Kuala Lumpur, pp. 1–6 (2016)
15.
Zurück zum Zitat Zhu, T., Shi, T., Li, J., Cai, Z., Zhou, X.: Task scheduling in deadline-aware mobile edge computing systems. IEEE Internet Things J. 6(3), 4854–4866 (2019)CrossRef Zhu, T., Shi, T., Li, J., Cai, Z., Zhou, X.: Task scheduling in deadline-aware mobile edge computing systems. IEEE Internet Things J. 6(3), 4854–4866 (2019)CrossRef
16.
Zurück zum Zitat Deng, R., Lu, R., Lai, C., Luan, T.H., Liang, H.: Optimal workload allocation in fog-cloud computing toward balanced delay and power consumption. IEEE Internet Things J. 3(6), 1171–1181 (2016) Deng, R., Lu, R., Lai, C., Luan, T.H., Liang, H.: Optimal workload allocation in fog-cloud computing toward balanced delay and power consumption. IEEE Internet Things J. 3(6), 1171–1181 (2016)
17.
Zurück zum Zitat Pham, Q.V., Leanh, T., Tran, N.H., Hong, C.S.: Decentralized computation offloading and resource allocation in heterogeneous networks with mobile edge computing (2018) Pham, Q.V., Leanh, T., Tran, N.H., Hong, C.S.: Decentralized computation offloading and resource allocation in heterogeneous networks with mobile edge computing (2018)
18.
Zurück zum Zitat Zheng, J., Cai, Y., Yuan, W., Shen, X.S.: Stochastic computation offloading game for mobile cloud computing. In: IEEE/CIC International Conference on Communications in China, Chengdu, pp. 1–6 (2016) Zheng, J., Cai, Y., Yuan, W., Shen, X.S.: Stochastic computation offloading game for mobile cloud computing. In: IEEE/CIC International Conference on Communications in China, Chengdu, pp. 1–6 (2016)
Metadaten
Titel
Efficient Multi-user Computation Scheduling Strategy Based on Clustering for Mobile-Edge Computing
verfasst von
Qing-Yan Lin
Guang-Shun Li
Jun-Hua Wu
Ying Zhang
JiaHe Yan
Copyright-Jahr
2020
DOI
https://doi.org/10.1007/978-3-030-48513-9_22

Premium Partner