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Stefan cel Mare
University of Suceava
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Print ISSN: 1582-7445
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WorldCat: 643243560
doi: 10.4316/AECE


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  4/2018 - 2

 HIGHLY CITED PAPER 

Supporting Location Transparent Services in a Mobile Edge Computing Environment

GILLY, K. See more information about GILLY, K. on SCOPUS See more information about GILLY, K. on IEEExplore See more information about GILLY, K. on Web of Science, FILIPOSKA, S. See more information about  FILIPOSKA, S. on SCOPUS See more information about  FILIPOSKA, S. on SCOPUS See more information about FILIPOSKA, S. on Web of Science, MISHEV, A. See more information about MISHEV, A. on SCOPUS See more information about MISHEV, A. on SCOPUS See more information about MISHEV, A. on Web of Science
 
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Download PDF pdficon (1,495 KB) | Citation | Downloads: 972 | Views: 2,294

Author keywords
context-aware services, handover, mobile nodes, resource management, wireless networks

References keywords
computing(15), cloud(10), communications(9), internet(7), edge(6), migration(5), virtual(4), survey(4), resource(4), mobile(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2018-11-30
Volume 18, Issue 4, Year 2018, On page(s): 11 - 22
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2018.04002
Web of Science Accession Number: 000451843400002
SCOPUS ID: 85058806251

Abstract
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Emerging models such as mobile edge computing provide the necessary characteristics for the deployment of Internet of Things applications by supplying the connected devices with local computing facilities essential for latency sensitive applications. One of the major issues of the underlying edge computing architecture is to cope with the device mobility that imposes dynamically changing network requirements. In this paper, we propose a resource management approach that aims to improve the location transparency and provide high quality of experience for end users by optimising latencies perceived when nodes are accessing services hosted on the edge of the network. By managing the virtualised computing resources based on the node location area information, the main objective of the approach is to minimise the network latency perceived by mobile nodes for both the initial allocation and the dynamic resource migration during the service lifetime while the requester node is changing location areas. The system is trying to achieve the most accurate 'follow me' service where the assigned resources closely follow the current mobile node location. The presented results show the effectiveness of the proposed solution in comparison to traditional resource management techniques on the macro and micro scale.


References | Cited By  «-- Click to see who has cited this paper

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[2] R. Mahmud, R. Kotagiri, R. Buyya, "Fog Computing: A Taxonomy, Survey and Future Directions," In: Di Martino B., Li KC., Yang L., Esposito A. (eds) Internet of Everything. Internet of Things (Technology, Communications and Computing). Springer, Singapore, 2018.
[CrossRef] [SCOPUS Times Cited 583]


[3] L. Gao, T. H. Luan, B. Liu, W. Zhou, S. Yu, "Fog computing and its applications in 5G," 5G Mobile Communications, Springer, Oct. 2017, pp. 571-593.
[CrossRef] [SCOPUS Times Cited 25]


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[CrossRef] [SCOPUS Times Cited 10]


[5] O. Osanaiye, S. Chen, Z. Yan, R. Lu, K.-K. R. Choo, M. Dlodlo, "From cloud to fog computing: A review and a conceptual live VM migration framework," IEEE Access, vol. 5, pp. 8284-8300, April 2017.
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[7] A. Manzalini, R. Minerva, F. Callegati, W. Cerroni, A. Campi, "Clouds of virtual machines in edge networks," IEEE Communications Magazine vol. 51 no. 7 pp. 63-70, July 2013.
[CrossRef] [Web of Science Times Cited 55] [SCOPUS Times Cited 71]


[8] S. Clayman, E. Maini, A. Galis, A. Manzalini, N. Mazzocca, "The dynamic placement of virtual network functions," IEEE Network Operations and Management Symposium (NOMS), Krakow, Poland, May 2014.
[CrossRef] [Web of Science Times Cited 62] [SCOPUS Times Cited 176]


[9] L. F. Bittencourt, M. M. Lopes, I. Petri, O. F. Rana, "Towards virtual machine migration in fog computing," 10th IEEE International Conference on P2P, Parallel, Grid, Cloud and Internet Computing, Krakow, Poland, Nov. 2015.
[CrossRef] [Web of Science Times Cited 104] [SCOPUS Times Cited 132]


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[12] A. Machen, S. Wang, K. K. Leung, B. J. Ko, T. Salonidis, "Live service migration in mobile edge clouds," IEEE Wireless Communications, Feb. 2018, pp. 140-147.
[CrossRef] [Web of Science Times Cited 144] [SCOPUS Times Cited 182]


[13] H. Gupta, A. Vahid Dastjerdi, S. K. Ghosh, R. Buyya, "ifogsim: A toolkit for modeling and simulation of resource management techniques in the internet of things, edge and fog computing environments," Software: Practice and Experience vol. 47 no. 9, 2017, pp. 1275-1296.
[CrossRef] [Web of Science Times Cited 704] [SCOPUS Times Cited 892]


[14] M. Aazam, E.-N. Huh, "Dynamic resource provisioning through fog micro datacenter", IEEE International Conference on Pervasive Computing and Communication Workshops, USA, March 2015.
[CrossRef] [SCOPUS Times Cited 177]


[15] C. T. Do, N. H. Tran, C. Pham, M. G. R. Alam, J. H. Son, C. S. Hong, "A proximal algorithm for joint resource allocation and minimizing carbon footprint in geo-distributed fog computing," 2015 IEEE International Conference on Information Networking (ICOIN), Jan. 2015, pp. 324-329.
[CrossRef] [SCOPUS Times Cited 97]


[16] S. Wang, J. Xu, N. Zhang, Y. Liu, "A Survey on service migration in mobile edge computing," IEEE Access, vol. 6, 2018, pp. 23511-23528.
[CrossRef] [Web of Science Times Cited 174] [SCOPUS Times Cited 223]


[17] K. Velasquez, D. P. Abreu, M. R. M. Assis, C. Senna, D. F. Aranha, L. F. Bittencourt, N. Laranjeiro, M. Curado, M. Vieira, E. Monteiro, E. Madeira, "Fog orchestration for the Internet of Everything: state-of-the-art and research challenges," Journal of Internet Services and Applications 9:14, 2018.
[CrossRef] [Web of Science Times Cited 45] [SCOPUS Times Cited 58]


[18] C. Pahl, B. Lee, "Containers and clusters for edge cloud architectures-a technology review," 3rd IEEE International Conference on Future Internet of Things and Cloud (FiCloud), Rome, Italy, Aug. 2015.
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[19] M. Abo-Zahhad, N. Sabor, S. Sasaki, S. M. Ahmed, "A centralized immune-voronoi deployment algorithm for coverage maximization and energy conservation in mobile wireless sensor networks," Information Fusion vol. 30 issue C, July 2016, pp. 36-51.
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[20] E. G. Coffman Jr, J. Csirik, G. Galambos, S. Martello, D. Vigo, "Bin packing approximation algorithms: survey and classification," Handbook of Combinatorial Optimization, Springer NY, 2013, pp. 455-531.
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[22] R. N. Calheiros, R. Ranjan, A. Beloglazov, C. A. F. De Rose, R. Buyya, "Cloudsim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms," Software: Practice and experience 41 (1) (2011) 23-50.
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[CrossRef] [SCOPUS Times Cited 190]


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[CrossRef] [Web of Science Times Cited 1071] [SCOPUS Times Cited 1351]




References Weight

Web of Science® Citations for all references: 6,283 TCR
SCOPUS® Citations for all references: 9,714 TCR

Web of Science® Average Citations per reference: 251 ACR
SCOPUS® Average Citations per reference: 389 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2023-05-29 18:10 in 132 seconds.




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