Research Article

Exploring Analytical Model to Performance Optimization for Mobile Application Using End-to-End Network Slicing in Cloud-Based Vehicular Networks

Volume: 23 Number: 1 February 1, 2019
EN

Exploring Analytical Model to Performance Optimization for Mobile Application Using End-to-End Network Slicing in Cloud-Based Vehicular Networks

Abstract

Today, many large usages of cloud-based vehicular networks and applications have rapidly increased. This rapid increase causes the requirement of systems to be reliable to share their resources without delay in order to ensure a better quality of service (QoS) for mobile users. Hence, network slicing is considered one of the key concepts to enhance QoS in 5G networks. At present, new architectures attempt to provide support for end-to-end server quality mechanisms. A key mechanism of network slicing supported by such modern architectures is able to either handover to better network or migrate services closer to the users as they move around. This can be done by advanced handover and server localization techniques. These sorts of advanced handover and server localization help to maintain the QoS for mobile application in heterogeneous environments. In order to obtain QoS measurements and get the network conditions in a specific area, a cloud-based vehicular network slicing management framework is proposed using an analytical modeling approach. The analytical model results obtained considering real scenarios from a Middlesex University VANET testbed. Using this framework, the mobile users will make a decision on which situation is better suited to obtain the service based on the latencies as well as queuing capacities of the networks.

Keywords

References

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  4. Ericsson white paper, 5G systems, http://www.ericsson.com/res/docs/whitepapers/whatis-a-5g-system.pdf, Jan. 2015. Accessed: 2015-05-29.
  5. Nokia, Dynamic end-to-end network slicing for 5G, White paper, Finland, 2016
  6. F. Sardis, G. Mapp, J. Loo, M. Aiash and A. Vinel, “On the Investigation of Cloud-Based Mobile Media Environments With Service-Populating and QoS-Aware Mechanisms," IEEE Transactions on Multimedia, vol. 15, no. 4, pp. 769-777, June 2013.
  7. F. Sardis, “Exploring Traffic and QoS Management mechanisms to support mobile cloud computing using service localization in heterogeneous environments", School of Science and Technology, Middlesex University, August 2014, PhD Thesis.
  8. G. Mapp, F. Katsriku, M. Aiash, N. Chinnam, R. Lopes, E. Moreira, R. P. Vanni, and M. Augusto, “Exploiting Location and Contextual Information to Develop a Comprehensive Framework for Proactive Handover in Heterogeneous Environments" Journal of Computer Networks and Communications, pp. 1-17, 2012.

Details

Primary Language

English

Subjects

Computer Software

Journal Section

Research Article

Publication Date

February 1, 2019

Submission Date

March 12, 2018

Acceptance Date

July 31, 2018

Published in Issue

Year 2019 Volume: 23 Number: 1

APA
Kırsal, Y. (2019). Exploring Analytical Model to Performance Optimization for Mobile Application Using End-to-End Network Slicing in Cloud-Based Vehicular Networks. Sakarya University Journal of Science, 23(1), 22-34. https://doi.org/10.16984/saufenbilder.404414
AMA
1.Kırsal Y. Exploring Analytical Model to Performance Optimization for Mobile Application Using End-to-End Network Slicing in Cloud-Based Vehicular Networks. SAUJS. 2019;23(1):22-34. doi:10.16984/saufenbilder.404414
Chicago
Kırsal, Yonal. 2019. “Exploring Analytical Model to Performance Optimization for Mobile Application Using End-to-End Network Slicing in Cloud-Based Vehicular Networks”. Sakarya University Journal of Science 23 (1): 22-34. https://doi.org/10.16984/saufenbilder.404414.
EndNote
Kırsal Y (February 1, 2019) Exploring Analytical Model to Performance Optimization for Mobile Application Using End-to-End Network Slicing in Cloud-Based Vehicular Networks. Sakarya University Journal of Science 23 1 22–34.
IEEE
[1]Y. Kırsal, “Exploring Analytical Model to Performance Optimization for Mobile Application Using End-to-End Network Slicing in Cloud-Based Vehicular Networks”, SAUJS, vol. 23, no. 1, pp. 22–34, Feb. 2019, doi: 10.16984/saufenbilder.404414.
ISNAD
Kırsal, Yonal. “Exploring Analytical Model to Performance Optimization for Mobile Application Using End-to-End Network Slicing in Cloud-Based Vehicular Networks”. Sakarya University Journal of Science 23/1 (February 1, 2019): 22-34. https://doi.org/10.16984/saufenbilder.404414.
JAMA
1.Kırsal Y. Exploring Analytical Model to Performance Optimization for Mobile Application Using End-to-End Network Slicing in Cloud-Based Vehicular Networks. SAUJS. 2019;23:22–34.
MLA
Kırsal, Yonal. “Exploring Analytical Model to Performance Optimization for Mobile Application Using End-to-End Network Slicing in Cloud-Based Vehicular Networks”. Sakarya University Journal of Science, vol. 23, no. 1, Feb. 2019, pp. 22-34, doi:10.16984/saufenbilder.404414.
Vancouver
1.Yonal Kırsal. Exploring Analytical Model to Performance Optimization for Mobile Application Using End-to-End Network Slicing in Cloud-Based Vehicular Networks. SAUJS. 2019 Feb. 1;23(1):22-34. doi:10.16984/saufenbilder.404414

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