Towards Bandwidth Optimization in Fog Computing using FACE Framework

Rosangela de Fátima Pereira Marquesone, Érico Augusto da Silva, Nelson Mimura Gonzalez, Karen Langona, Walter Akio Goya, Fernando Frota Redígolo, Tereza Cristina Melo de Brito Carvalho, Jan-Erik Mångs, Azimeh Sefidcon

2017

Abstract

The continuous growth of data created by Internet-connected devices has been posing a challenge for mobile operators. The increase in the network traffic has exceeded the network capacity to efficiently provide services, specially for applications that require low latency. Edge computing is a concept that allows lowering the network traffic by using cloud-computing resources closer to the devices that either consume or generate data. Based on this concept, we designed an architecture that offers a mechanism to reduce bandwidth consumption. The proposed solution is capable of intercepting the data, redirecting it to a processing node that is allocated between the end device and the server, in order to apply features that reduce the amount of data on the network. The architecture has been validated through a prototype using video surveillance. This area of application was selected due to the high bandwidth requirement to transfer video data. Results show that in the best scenario is possible to obtain about 97% of bandwidth gain, which can improve the quality of services by offering better response times.

References

  1. (2015). Ericsson Mobility Report. Technical report.
  2. Bonomi, F., Milito, R., Zhu, J., and Addepalli, S. (2012). Fog computing and its role in the internet of things. In Proceedings of the first edition of the MCC workshop on Mobile cloud computing, pages 13-16. ACM.
  3. Dastjerdi, A. V. and Buyya, R. (2016). Fog computing: Helping the internet of things realize its potential. Computer, 49(8):112-116.
  4. Gonzalez, N. M., Goya, W., Pereira, R., Langona, K., Silva, E., Carvalho, T., Miers, C., Ma°ngs, J., and Sefidcon, A. (2016). Fog computing: Data analytics and cloud distributed processing on the network edges. In 35th International Conference of the Chilean.
  5. Hu, W., Gao, Y., Ha, K., Wang, J., Amos, B., Chen, Z., Pillai, P., and Satyanarayanan, M. (2016). Quantifying the impact of edge computing on mobile applications.
  6. Margulius, D. (2002). Apps on the edge. InfoWorld, 24(2).
  7. Nilsson, F. and Axis, C. (2017). Intelligent Network Video: Understanding Modern Video Surveillance Systems. Taylor & Francis.
  8. Pang, H. and Tan, K.-L. (2004). Authenticating query results in edge computing. In Data Engineering, 2004. Proceedings. 20th International Conference on, pages 560-571. IEEE.
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Paper Citation


in Harvard Style

Marquesone R., da Silva É., Gonzalez N., Langona K., Goya W., Frota Redígolo F., Carvalho T., Mångs J. and Sefidcon A. (2017). Towards Bandwidth Optimization in Fog Computing using FACE Framework . In Proceedings of the 7th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER, ISBN 978-989-758-243-1, pages 491-498. DOI: 10.5220/0006303804910498


in Bibtex Style

@conference{closer17,
author={Rosangela de Fátima Pereira Marquesone and Érico Augusto da Silva and Nelson Mimura Gonzalez and Karen Langona and Walter Akio Goya and Fernando Frota Redígolo and Tereza Cristina Melo de Brito Carvalho and Jan-Erik Mångs and Azimeh Sefidcon},
title={Towards Bandwidth Optimization in Fog Computing using FACE Framework},
booktitle={Proceedings of the 7th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,},
year={2017},
pages={491-498},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006303804910498},
isbn={978-989-758-243-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 7th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,
TI - Towards Bandwidth Optimization in Fog Computing using FACE Framework
SN - 978-989-758-243-1
AU - Marquesone R.
AU - da Silva É.
AU - Gonzalez N.
AU - Langona K.
AU - Goya W.
AU - Frota Redígolo F.
AU - Carvalho T.
AU - Mångs J.
AU - Sefidcon A.
PY - 2017
SP - 491
EP - 498
DO - 10.5220/0006303804910498