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A Lightweight Service Placement Approach for Community Network Micro-Clouds

  • Mennan Selimi
  • Llorenç Cerdà-Alabern
  • Felix Freitag
  • Luís Veiga
  • Arjuna Sathiaseelan
  • Jon Crowcroft
Open Access
Article

Abstract

Community networks (CNs) have gained momentum in the last few years with the increasing number of spontaneously deployed WiFi hotspots and home networks. These networks, owned and managed by volunteers, offer various services to their members and to the public. While Internet access is the most popular service, the provision of services of local interest within the network is enabled by the emerging technology of CN micro-clouds. By putting services closer to users, micro-clouds pursue not only a better service performance, but also a low entry barrier for the deployment of mainstream Internet services within the CN. Unfortunately, the provisioning of these services is not so simple. Due to the large and irregular topology, high software and hardware diversity of CNs, a “careful” placement of micro-clouds services over the network is required to optimize service performance. This paper proposes to leverage state information about the network to inform service placement decisions, and to do so through a fast heuristic algorithm, which is critical to quickly react to changing conditions. To evaluate its performance, we compare our heuristic with one based on random placement in Guifi.net, the biggest CN worldwide. Our experimental results show that our heuristic consistently outperforms random placement by 2x in bandwidth gain. We quantify the benefits of our heuristic on a real live video-streaming service, and demonstrate that video chunk losses decrease significantly, attaining a 37% decrease in the packet loss rate. Further, using a popular Web 2.0 service, we demonstrate that the client response times decrease up to an order of magnitude when using our heuristic. Since these improvements translate in the QoE (Quality of Experience) perceived by the user, our results are relevant for contributing to higher QoE, a crucial parameter for using services from volunteer-based systems and adapting CN micro-clouds as an eco-system for service deployment.

Keywords

Service placement Community networks Micro-clouds Edge-clouds Wireless mesh networks 

Notes

Acknowledgements

This work was supported by the European H2020 framework program projects RIFE (H2020-644663), netCommons (H2020-688768), LightKone (H2020-732505), and by the Spanish government under contract TIN2016-77836-C2-2-R. This work was also supported by the national funds through Fundação para a Ciência e a Tecnologia in project ContexTWA with reference PTDC/EEI-SCR/6945/2014.

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© The Author(s) 2018

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  1. 1.University of CambridgeCambridgeUK
  2. 2.Universitat Politècnica de Catalunya, BarcelonaTechBarcelonaSpain
  3. 3.Instituto Superior Técnico (IST), INESC-ID LisboaLisbonPortugal

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