Yoğun Hesaplama ve Zaman Gerektiren İşlemlerin Sunucularda Yapılması

Abstract

Günden güne artan mobil cihaz sayısı, birçok büyük veya küçük ölçekli kullanıcı isteklerinin mobil cihazlara kaymasına sebep olmuştur. Bu artış cihazların sahip olduğu iş yükünü de buna bağlı olarak arttırmıştır. Ancak sınırlı kaynakları olan mobil cihazların, bazı büyük işlemleri lokal olarak kendi bünyesinde çalıştırması bazen uzun bekleme sürelerine sebep olmakta, bazen de kullanıcı deneyimini kötü etkilemektedir. Mobil cihazların sahip olduğu bu tarz işlemlerin daha hızlı ve etkili bir şekilde çalıştırılması ve sonuçlarının cihaza tekrar döndürülmesini sağlayan mobil uç hesaplama (Mobile Edge Computing) sistemi günümüzde çeşitli ağ teknolojileri ile mümkün hale gelmiştir. Bu çalışma kapsamında yoğun şekilde CPU kullanımına ihtiyaç duyan ve uzun gecikme sürelerine sebep olan multi-thread yapılı bir mobil uygulama geliştirilmiş ve bu mobil uygulamanın lokal ve MEC sistemindeki performanslarının karşılaştırılması yapılmıştır.

Keywords

• Mobil Uç Hesaplama
• Veri Boşaltma
• Mobil Bulut Hesaplama
• Hücresel Ağlar

Performing CPU-intensive and Long Time Consuming Tasks on Servers

Abstract

The increasing number of mobile devices day by day has caused many large and small scale user requests to shift to mobile devices. This increase has raised the workload of devices accordingly. However, Mobile devices with limited resources sometimes evaluate some large processes locally, causing long waiting times and sometimes adversely affecting the user experience. The MEC (Mobile Edge Computing) system, which enables such processes to be evaluated faster and more effectively and the results are returned to the device, that mobile devices have, has been developed with various network technologies today. In this study, a multi-thread mobile application that requires heavy CPU usage and has long delay has been developed and the performance of this mobile application in local and MEC systems has been compared.

Keywords

• Mobile Edge Computing
• Offloading
• Mobile Cloud Computing
• Cellular Network

References

1. [1] Fernando, N., Loke, S. W., & Rahayu, W. (2013). Mobile cloud computing: A survey. Future Generation Computer Systems, 29(1), 84-106. doi:10.1016/j.future.2012.05.023
2. [2] A. U. R. Khan, M. Othman, S. A. Madani, and S. U. Khan, “A survey of mobile cloud computing application models,” IEEE Commun. Surveys Tuts., vol. 16, no. 1, pp. 393–413, 1st Quart., 2014.M. Armbrust et al., “A view of cloud computing,” Commun. ACM, vol. 53, no. 4, pp. 52–58, Apr. 2010.
3. [3] Y. Mao, C. You, J. Zhang, K. Huang, and K. B. Letaief, “A servey on mobile edge computing: The communication perspective,” to appear IEEE Commun. Survey Tuts. 2017. [Online]. Available: https://arxiv.org/ abs/1701.01090
4. [4] M. Agiwal, A. Roy and N. Saxena, “Next Generation 5G Wireless Networks: A Comprehensive Survey," IEEE Communications Surveys & Tutorials, vol. 18, no. 3, pp. 1617- 1655, Third Quarter 2016.
5. [5] J. G. Andrews et al., “What will 5G be?” IEEE J. Sel. Areas Commun., vol. 32, no. 6, pp. 1065–1082, Jun. 2014. [6] “Understanding 5G: Perspectives on future technological advancements in mobile,” GSMA Intell.,London,U.K.,Dec.2014.[Online].Available:https://www.gs maintelligence.com/research/?file=141208-5g.pdf&download
6. [7] “Mobile-edge computing—Introductory technical white paper,” White Paper, ETSI, Sophia Antipolis, France,Sep.2014.[Online].Available:https://portal.etsi.org/portals /0/tbpages/mec/docs/mobileedge_computing_introductory_techn ical_white_paper_v1%2018-09-14.pdf
7. [8] S. Wang et al., “A survey on mobile edge networks: Convergence of computing, caching and communications,” IEEE Access, vol.5, pp. 6757–6779, 2017.
8. [9] P. Mach and Z. Becvar, “Mobile edge computing: A survey on architecture and computation offloading,” IEEE Commun. Surveys Tuts., vol. 19, no. 3, pp. 1628–1656, 3rd Quart., 2017.

9. [10] Y. C. Hu, M. Patel, D. Sabella, N. Sprecher, and V. Young, “Mobile edge computing—A key technology towards 5G,” White Paper, ETSI, Sophia Antipolis, France, 2015.
10. [11] “Mobile edge computing use cases & deployment options,” White Paper, Juniper, Sunnyvale,CA,USA,Jul.2016.[Online]Available:https://www.jun iper.net/assets/us/en/local/pdf/whitepapers/000642- en.pdf
11. [12] C.-Y. Chang, K. Alexandris, N. Nikaein, K. Katsalis, and T. Spyropoulos, “MEC architectural implications for LTE/LTE-A networks,” in Proc. ACM Workshop Mobility Evol. Internet Archit. (MobiArch), New York, NY, USA, Oct. 2016, pp. 13–18.
12. [13] C.-Y. Chang, K. Alexandris, N. Nikaein, K. Katsalis, and T. Spyropoulos, “MEC architectural implications for LTE/LTE-A networks,” in Proc. ACM Workshop Mobility Evol. Internet Archit. (MobiArch), New York, NY, USA, Oct. 2016, pp. 13–18.
13. [14] “Mobile edge computing use cases & deployment options,” White Paper, Juniper, Sunnyvale,CA,USA,Jul.2016.[Online]Available:https://www.jun iper.net/assets/us/en/local/pdf/whitepapers/2000642- en.pdf
14. [15] X. Chen, L. Jiao, W. Li, and X. Fu, “Efficient multi-user computation offloading for mobile-edge cloud computing,” IEEE/ACM Trans. Netw., vol. 24, no. 5, pp. 2795–2808, Oct. 2016.
15. [16] B. Shi, J. Yang, Z. Huang, and P. Hui, “Offloading guidelines for augmented reality applications on wearable devices,” in Proc. ACM Int. Symp. Multimedia, Brisbane, QLD, Australia, Oct. 2015, pp. 1271–1274.
16. [17] S. Melendez and M. P. McGarry, “Computation offloading decisions for reducing completion time,” in Proc. IEEE Annu. Consum. Commun. Netw. Conf. (CNCC), Las Vegas, NV, USA, Jan. 2017, pp. 160–164.
17. [18] S. E. Mahmoodi, R. N. Uma, and K. P. Subbalakshmi, “Optimal joint scheduling and cloud offloading for mobile applications,” IEEE Trans. Cloud Comput., to be published.
18. [19] A. Al-Shuwaili and O. Simeone, “Energy-efficient resource allocation for mobile edge computing-based augmented reality applications,” IEEE Wireless Commun. Lett., vol. 6, no. 3, pp. 398–401, Jun. 2017
19. [20] H. Liu et al., “Mobile edge cloud system: Architectures, challenges,and approaches,” IEEE Syst. J., to be published. [21] S. Vakilinia, M. M. Ali, and D. Qiu, “Modeling of the resource allocation in cloud computing centers,” Comput. Netw., vol. 91, pp. 453–470, Nov. 2015.
20. [22] S. Tekinay and B. Jabbary, “Handover and channel assignment in mobile cellular networks,” IEEE Commun. Mag., vol. 29, pp. 42–46, Nov. 1991.
21. [23] G. P. Pollini, “Trends in handover design,” IEEE Commun.Mag., vol. 34, pp. 82–90, Mar. 1996.
22. [24] V.Ateş and M. A. Akcayol, “Kablosuz Ağlarda Tahmine Dayalı Hücreler Arası GeçiĢ Algoritmaları”, International journal of informatics technologies, 3.3, 2010.
23. [25] S. Wang et al., “Mobility-induced service migration in mobile microclouds,” in Proc. IEEE Mil. Commun. Conf. (MILCOM), Baltimore, MD, USA, Oct. 2014, pp. 835–840
24. [26] R. Urgaonkar et al., “Dynamic service migration and workload scheduling in edge-clouds,” Perform. Eval., vol. 91, pp. 205–228, Sep. 2015.
25. [27] N. Vastardis and K. Yang, “An enhanced communitybased mobility model for distributed mobile social networks,” J. Ambient Intell.Humanized Comput., vol. 5, no. 1, pp. 65–75, Feb. 2014.
26. [28] Google (2020). gRPC. Retrieved 23 October 2020, from https://grpc.io/
27. [29] Google.( 2015, March 1 ). gRPC.GRPC. https://developers.google.com/protocol-buffer