Gelly-scheduling: distributed graph processing for service placement in community networks
Document typeConference report
PublisherAssociation for Computing Machinery (ACM)
Rights accessOpen Access
European Commission's projectLightKone - Lightweight Computation for Networks at the Edge (EC-H2020-732505)
Community networks (CNs) have seen an increase in the last fifteen years. Their members contact nodes which operate Internet proxies, web servers, user file storage and video streaming services, to name a few. Detecting communities of nodes with properties (such as co-location) and assessing node eligibility for service placement is thus a key-factor in optimizing the experience of users. We present a novel solution for the problem of service placement as a two-phase approach, based on: 1) community finding using a scalable graph label propagation technique and 2) a decentralized election procedure to address the multi-objective challenge of optimizing service placement in CNs. Herein we: i) highlight the applicability of leader election heuristics which are important for service placement in community networks and scheduler-dependent scenarios; ii) present a parallel and distributed solution designed as a scalable alternative for the problem of service placement, which has mostly seen computational approaches based on centralization and sequential execution.
CitationCoimbra, M., Selimi, M., Francisco, A., Freitag, F., Veiga, L. Gelly-scheduling: distributed graph processing for service placement in community networks. A: ACM Symposium on Applied Computing. "The 33rd Annual ACM Symposium on Applied Computing: Pau, France: April 9-13, 2018". New York: Association for Computing Machinery (ACM), 2018, p. 151-160.
All rights reserved. This work is protected by the corresponding intellectual and industrial property rights. Without prejudice to any existing legal exemptions, reproduction, distribution, public communication or transformation of this work are prohibited without permission of the copyright holder