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Supporting Location Transparent Services in a Mobile Edge Computing EnvironmentGILLY, K. , FILIPOSKA, S. , MISHEV, A.
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context-aware services, handover, mobile nodes, resource management, wireless networks
computing(15), cloud(10), communications(9), internet(7), edge(6), migration(5), virtual(4), survey(4), resource(4), mobile(4)
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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
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|
| X. Foukas, G. Patounas, A. Elmokashfi, M. K. Marina, "Network slicing in 5G: Survey and challenges," IEEE Communications Magazine, vol. 55(5), May 2017, pp. 94-100. |
[CrossRef] [Web of Science Times Cited 112] [SCOPUS Times Cited 173]
 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.
 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 15]
 P. H. Kuo, A. Mourad, C. Lu, M. Berg, S. Duquennoy, Y. Y. Chen, C. Y. Li, "An integrated edge and Fog system for future communication networks," IEEE Wireless Communications and Networking Conference Workshops (WCNCW), Barcelona, Spain, April 2018, pp. 338-343.
[CrossRef] [SCOPUS Times Cited 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.
[CrossRef] [Web of Science Times Cited 69] [SCOPUS Times Cited 99]
 V. Bahl, Cloud 2020: Emergence of micro data centers (cloudlets) for latency sensitive computing (keynote), Middleware April 2015.
 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 48] [SCOPUS Times Cited 61]
 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 78] [SCOPUS Times Cited 132]
 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 40] [SCOPUS Times Cited 61]
 S. Ningning, G. Chao, A. Xingshuo, Z. Qiang, "Fog computing dynamic load balancing mechanism based on graph repartitioning," China Communications vol. 13 issue 3, pp. 156-164, March 2016.
[CrossRef] [Web of Science Times Cited 45] [SCOPUS Times Cited 58]
 V. B. C. Souza, W. Ramirez, X. Masip-Bruin, E. Marin-Tordera, G. Ren, G. Tashakor, "Handling service allocation in combined fog-cloud scenarios," IEEE International Conference on Communications, Malaysia, May 2016.
[CrossRef] [SCOPUS Times Cited 59]
 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 29] [SCOPUS Times Cited 46]
 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 119] [SCOPUS Times Cited 219]
 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 93]
 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 52]
 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 27] [SCOPUS Times Cited 39]
 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 7] [SCOPUS Times Cited 14]
 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.
[CrossRef] [Web of Science Times Cited 58] [SCOPUS Times Cited 115]
 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.
[CrossRef] [Web of Science Times Cited 35] [SCOPUS Times Cited 51]
 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.
[CrossRef] [SCOPUS Times Cited 134]
 S. Filiposka, A. Mishev, K. Gilly, "Community-based allocation and migration strategies for fog computing," IEEE Wireless Communications and Networking Conference, WCNC, Barcelona, Spain, April 2018.
[CrossRef] [SCOPUS Times Cited 7]
 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.
[CrossRef] [Web of Science Times Cited 1907] [SCOPUS Times Cited 2676]
 M. Mishra, A. Sahoo, "On theory of vm placement: Anomalies in existing methodologies and their mitigation using a novel vector based approach," IEEE International Conference on Cloud Computing, Washington, USA, July 2011.
[CrossRef] [SCOPUS Times Cited 160]
 A. Beloglazov, R. Buyya, "Optimal online deterministic algorithms and adaptive heuristics for energy and performance efficient dynamic consolidation of virtual machines in cloud data centers," Concurrency and Computation: Practice and Experience vol. 24 issue 13, October 2011, pp. 1397-1420.
[CrossRef] [Web of Science Times Cited 698] [SCOPUS Times Cited 922]
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