[1] Du Peng, Ba Teer, Zhang Yuan,. Delay-performance optimization resource schedulingin many-to-one multi-server cellular edge computing systems [J]. Journal of Southeast University (English Edition), 2019, 35 (3): 325-331. [doi:10.3969/j.issn.1003-7985.2019.03.008]

Copy

Delay-performance optimization resource schedulingin many-to-one multi-server cellular edge computing systems()

Share：

Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:

35

Issue:

2019 3

Page:

325-331

Research Field:

Information and Communication Engineering

Publishing date:

2019-09-30

Info

Title:

Delay-performance optimization resource schedulingin many-to-one multi-server cellular edge computing systems

Author(s):

Du Peng¹;  Ba Teer²;  Zhang Yuan²

¹College of Automation & College of Artificial Intelligence, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
²National Mobile Communications Research Laboratory, Southeast University, Nanjing 210096, China

Keywords:

cellular system;  delay;  edge computing;  resource scheduling

PACS:

TN929.5

DOI:

10.3969/j.issn.1003-7985.2019.03.008

Abstract:

To further reduce the delay in cellular edge computing systems, a new type of resource scheduling algorithm is proposed. Without assuming the knowledge of the statistics of user task arrival traffic, the analytical formulae of the communication and computing queueing delays in many-to-one multi-server cellular edge computing systems are derived by using the arriving curve and leaving curve. Based on the analytical formulae, an optimization problem of delay minimization is directly formulated, and then a novel scheduling algorithm is designed. The delay performance of the proposed algorithm is evaluated via simulation experiments. Under the considered simulation parameters, the proposed algorithm can achieve 12% less total delay, as compared to the traditional algorithms. System parameters including the weight, the amount of computing resources provided by servers, and the average user task arrival rate have impact on the percentage of delay reduction. Therefore, compared with the queue length optimization based traditional scheduling algorithms, the proposed delay optimization-based scheduling algorithm can further reduce delay.

References:

[1] Checko A, Christiansen H L, Yan Y, et al. Cloud RAN for mobile networks: A technology overview[J]. IEEE Communications Surveys & Tutorials, 2015, 17(1): 405-426. DOI:10.1109/comst.2014.2355255.
[2] Peng M G, Sun Y H, Li X L, et al. Recent advances in cloud radio access networks: System architectures, key techniques, and open issues[J]. IEEE Communications Surveys & Tutorials, 2016, 18(3): 2282-2308. DOI:10.1109/comst.2016.2548658.
[3] Tran T X, Hajisami A, Pandey P, et al. Collaborative mobile edge computing in 5G networks: New paradigms, scenarios, and challenges[J]. IEEE Communications Magazine, 2017, 55(4): 54-61. DOI:10.1109/mcom.2017.1600863.
[4] Guo H Z, Liu J J, Zhang J. Computation offloading for multi-access mobile edge computing in ultra-dense networks[J]. IEEE Communications Magazine, 2018, 56(8): 14-19. DOI:10.1109/mcom.2018.1701069.
[5] Dinh T Q, La Q D, Quek T Q S, et al. Learning for computation offloading in mobile edge computing[J]. IEEE Transactions on Communications, 2018, 66(12): 6353-6367. DOI:10.1109/tcomm.2018.2866572.
[6] Wang F, Xu J, Wang X, et al. Joint offloading and computing optimization in wireless powered mobile-edge computing systems [J]. IEEE Transactions on Wireless Communications, 2018, 17(3): 1784-1797. DOI: 10.1109/TWC.2017.2785305.
[7] Zhou J Z, Zhang X, Wang W B. Joint resource allocation and user association for heterogeneous services in multi-access edge computing networks[J]. IEEE Access, 2019, 7: 12272-12282. DOI:10.1109/access.2019.2892466.
[8] Du J B, Zhao L Q, Chu X L, et al. Enabling low-latency applications in LTE-A based mixed fog/cloud computing systems[J]. IEEE Transactions on Vehicular Technology, 2019, 68(2): 1757-1771. DOI:10.1109/tvt.2018.2882991.
[9] Chen L X, Zhou S, Xu J. Computation peer offloading for energy-constrained mobile edge computing in small-cell networks[J]. ACM Transactions on Networking, 2018, 26(4): 1619-1632. DOI:10.1109/tnet.2018.2841758.
[10] Ko S W, Han K F, Huang K B.Wireless networks for mobile edge computing: Spatial modeling and latency analysis[J]. IEEE Transactions on Wireless Communications, 2018, 17(8): 5225-5240. DOI:10.1109/twc.2018.2840120.
[11] Fan Q, Ansari N. Application aware workload allocation for edge computing-based IoT[J]. IEEE Internet of Things Journal, 2018, 5(3): 2146-2153. DOI:10.1109/jiot.2018.2826006.
[12] Yang L C, Zhang H L, Li M, et al. Mobile edge computing empowered energy efficient task offloading in 5G[J]. IEEE Transactions on Vehicular Technology, 2018, 67(7): 6398-6409. DOI:10.1109/tvt.2018.2799620.
[13] Lyu X C, Ni W, Tian H, et al. Optimal schedule of mobile edge computing for Internet of Things using partial information[J]. IEEE Journal on Selected Areas in Communications, 2017, 35(11): 2606-2615. DOI:10.1109/jsac.2017.2760186.
[14] Kim Y, Kwak J, Chong S. Dual-side optimization for cost-delay tradeoff in mobile edge computing[J]. IEEE Transactions on Vehicular Technology, 2018, 67(2): 1765-1781. DOI:10.1109/tvt.2017.2762423.
[15] Feng H, Llorca J, Tulino A M, et al. Optimal control of wireless computing networks[J]. IEEE Transactions on Wireless Communications, 2018, 17(12): 8283-8298. DOI:10.1109/twc.2018.2875740.
[16] Kim Y, Lee H W, Chong S. Mobile computation offloading for application throughput fairness and energy efficiency[J]. IEEE Transactions on Wireless Communications, 2019, 18(1): 3-19. DOI:10.1109/twc.2018.2868679.
[17] Neely M J. Stochastic network optimization with application to communication and queueing systems[M]//Synthesis Lectures on Communication Networks.Morgan & Claypool, 2010: 1-211. DOI:10.2200/s00271ed1v01y201006cnt007.

Memo

Memo:

Biographies: Du Peng(1971—), male, doctor, lecturer; Zhang Yuan(corresponding author), male, doctor, associate professor, y.zhang@seu.edu.cn.
Foundation item: The National Natural Science Foundation of China(No.61571111).
Citation: Du Peng, Ba Teer, Zhang Yuan.Delay-performance optimization resource scheduling in many-to-one multi-server cellular edge computing systems[J].Journal of Southeast University(English Edition), 2019, 35(3):325-331.DOI:10.3969/j.issn.1003-7985.2019.03.008.

Common functions