Method for Effective Use of Cloudlet Network Resources

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Rashid G. Alakbarov 1,*

1. Institute of Information Technology of ANAS, Baku, Azerbaijan

* Corresponding author.


Received: 7 Oct. 2019 / Revised: 12 Feb. 2020 / Accepted: 24 Jun. 2020 / Published: 8 Oct. 2020

Index Terms

Mobile cloud computing, mobile devices, cloudlet, communication channel, multimedia software applications, wireless communication channel, energy consumption


The article addresses the issue of balanced placement of mobile software applications of mobile users in cloudlets deployed near base stations of Wireless Metropolitan Area Networks (WMAN), taking into account their technical capabilities. It is noted that the proposed model is more efficient in meeting the demand for computing and memory resources of mobile devices, eliminating network delays and using a reliable communication channel. At the same time, a minimum of cloudlet-based communication channels with a mobile user was suggested, reducing the network load and reliability of the communication channel when using multimedia software on mobile devices. The article reviews the balanced distribution of the tasks in the cloudlet network. If a user offloads the task to the nearest cloud and resolves it there, then the delays and energy consumption will be less. When the cloudlet is far from the mobile device, as the number of communication channels increases the delays are observed. Moreover, the article discusses the issue of selecting the cloudlets that meet some of the user requirements. Using the possible values that determine the importance of cloudlets (vacant resources in cloudlets, closeness of cloudlets to the user, high reliability, etc.), the conditions, according to which the user's application is offloaded to the certain cloudlet, are studied and a method is proposed.

Cite This Paper

Rashid G. Alakbarov, "Method for Effective Use of Cloudlet Network Resources", International Journal of Computer Network and Information Security(IJCNIS), Vol.12, No.5, pp.46-55, 2020. DOI:10.5815/ijcnis.2020.05.04


[1]T. Diaby, B. B. Rad, “Cloud Computing: A review of the Concepts and Deployment Models,” International Journal of Information Technology and Computer Science, vol. 9, no. 6, pp. 50-58, 2017.
[2]M. Goyal, S. Singh, “Mobile Cloud Computing,” International Journal of Enhanced Research in Science Technology & Engineering, vol. 3, no. 4, pp. 517-521, 2014.
[3]Y. Hao, M. Chen, L. Hu, M. S. Hossain, A. Ghoniem, “Energy Efficient Task Caching and Offloading for Mobile Edge Computing,” IEEE Access, vol. 6, pp. 11365–11373. 2018.
[4]M. Zhao, K. Zhou, “Selective Offloading by Exploiting ARIMA-BP for Energy Optimization in Mobile Edge Computing Networks,” Algorithms, vol. 12, no. 2, pp.1-13, 2019.
[5]H. T. Dinh, C. Lee, D. Niyato, P. Wang, “A survey of mobile cloud computing: Architecture, applications, and approaches,” Wireless Communications and Mobile Computing, vol. 13, no. 18, pp. 1587-1611, 2013.
[6]R. Alakbarov, F. Pashayev, O. Alakbarov, “Forecasting Cloudlet Development on Mobile Computing Clouds” International Journal of Information Technology and Computer Science (IJITCS), vol. 9, no. 11, pp. 23-34, 2017.
[7]M. Mam, G. Leena, N. S. Saxena, “Improved K-means Clustering based Distribution Planning on a Geographical Network,” International Journal of Intelligent Systems and Applications (IJISA), vol. 9, no. 4, pp. 69-75, 2017.
[8]M. Jia, W. Liang, Z. Xu, and M. Huang, “Cloudlet Load Balancing in Wireless Metropolitan Area Networks,” IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications. p. 1-9, 2016.
[9]G. T. Hicham, E. A. Chaker, “Cloud Computing CPU Allocation and Scheduling Algorithms Using CloudSim Simulator,” International Journal of Electrical and Computer Engineering, vol. 6, no. 4, pp. 1866-1879, 2016.
[10]D. G. Roy, D. De, A. Mukherjee, R. Buyya, “Application-aware cloudlet selection for computation offloading in multi-cloudlet environment,” The Journal of Supercomputing, vol. 73, pp. 1672–1690, 2017.
[11]R. K. Alakbarov, F. Pashayev, M. Hashimov, “Development of the Method of Dynamic Distribution of Users’ Data in Storage Devices in Cloud Technology,” Advances in Information Sciences and Service Sciences, vol. 8, no. 1, pp. 16-21, 2016.
[12]O. P. Akomolafe, M. O. Abodunrin, “A Hybrid Cryptographic Model for Data Storage in Mobile Cloud Computing,” I. J. Computer Network and Information Security, no. 6, pp. 53-60, 2017.
[13]Y. C. Shim, “Effects of cloudlets on interactive applications in mobile cloud computing environments,” International Journal of Advanced Computer Technology, vol. 4, no.1, pp. 54-62, 2015.
[14]M. Satyanarayanan, P. Bahl, R. Caceres, N. Davies, “The case for vm-based cloudlets in mobile computing,” Pervasive Computing, IEEE, vol. 8, no .4, pp. 14-23, 2009.
[15]K. Ha, P. Pillai, W. Richter, Y. Abe, M. Satyanarayanan, “Just-in-time provisioning for cyber foraging,” in Proceeding of the 11th annual international conference on Mobile systems, applications, and services. ACM, pp. 153-166, 2013.
[16]Y. Jararweha, L. Tawalbehb, F. Ababneha, A. Khreishahc, F. Dosarib, “Scalable Cloudlet-based Mobile Computing Model,” The 11th International Conference on Mobile Systems and Pervasive Computing (MobiSPC-2014). Procedia Computer Science vol. 34, pp. 434-441, 2014.
[17]R. K. Alekberov, F. H. Pashayev, O. R. Alekperov, “Effective Use Method of Cloudlet Resources by Mobile Users,” 11th IEEE International Conference on Application of Information and Communication Technologies. Moscow, pp. 401-403, 2017.
[18]M. Jia, W. Liang, Z. Xu, M. Huang, “Cloudlet load balancing in wireless metropolitan area networks,” IEEE, INFOCOM, pp. 730-738, 10-14 April 2016.
[19]C. S Hi, V. Lakafosis, M. H. Ammar, E. W. Zegura, “Serendipity: enabling remote computing among intermittently connected mobile devices,” in Proc. of the ACM MobiHoc, pp. 145-154. 2012.
[20]R.K. Alekberov, O.R. Alekberov, “Procedure of effective use of cloudlets in wireless metropolitan area network environment,” International Journal of Computer Networks & Communications, vol. 11, no.1, pp. 93-107, 2019.
[21]D. Sarddar, R. Bose, “A Mobile Cloud Computing Architecture with Easy Resource Sharing,” International Journal of Current Engineering and Technology, vol. 4, no. 3, pp. 1249-1254, 2014.
[22]M. Jia, J. Cao, W. Liang, “Optimal Cloudlet Placement and User to Cloudlet Allocation in Wireless Metropolitan Area Networks,” IEEE Transactions on Cloud Computing, vol. 5, no .4, pp. 725-737, 2017.
[23]E. Gelenbe, R. Lent, and M. Douratsos, “Choosing a local or remote cloud,” Proceedings of 2nd International Symposium on Network Cloud Computing and Applications, pp.25-30, 2012.
[24]T. Verbelen, P. Simoens, F. D. Turck, and B. Dhoedt, “Cloudlets: Bringing the cloud to the mobile user,” Proceedings of 3rd workshop on Mobile Cloud Computing and Services, pp. 29-36, ACM, 2012.
[25]F. Liu, P. Shu, H. Jin, L. Ding, J. Yu, D. Niu, B. Li, “Gearing resource-poor mobile device with powerful clouds: architectures, challenges, and applications,” IEEE Wireless Communications. vol. 20, no. 3, pp. 14-22, 2013.
[26]Mikryukov A. A., Khantimirov R. I, “The task of initial resource allocation in cloud computing environments based on the hierarchy analysis method,” Applied Informatics. no.8, pp. 184-185, 2015.
[27]Nayyer M. Z., Raza I., Hussain S, “A Survey of Cloudlet-Based Mobile Augmentation Approaches for Resource Optimization,” ACM Computing Surveys. vol. 51, no. 5, pp. 1-28, 2018.
[28]Somula R. S., Ra S, A survey on mobile cloud computing: Mobile Computing + Cloud Computing (MCC = MC + CC). Scalable Computing: Practice and Experience, vol. 19, no.4, pp. 309–337, 2018.
[29]Ceselli A., Premoli M., Secci S, Mobile Edge Cloud Network Design Optimization. IEEE // ACM Transactions on Networking, vol. 25, no. 3, pp. 1818-1831, 2017.
[30]G. Huerta-Canepa, D. Lee, “A virtual cloud computing provider for mobile devices,” International Journal of Advance Research, Ideas and Innovations in Technology, vol. 3, no. 3, pp. 414, 2017.
[31]S. Abolfazli, “Cloud-based Augmentation for Mobile Devices: Motivation, Taxonomies, and Open Challenges,” IEEE Commun. Surv. Tutor., vol. 16, pp. 337-368, 2014.
[32]R. K. Alekberov, O. R. Alekberov, “Virtual Machine Selection Algorithm Based on User Requirements in Mobile Cloud Computing Environment,” International Journal of Computers & Technology, vol. 17, no. 2. pp.7 335-7349, 2018.