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Community networks (CNs) have seen an increase in the last fifteen years.Their members contact nodes which operate Internet proxies, web servers, userfile storage and video streaming services, to name a few. Detecting communitiesof nodes with properties (such as co-location) and assessing node eligibilityfor service placement is thus a key-factor in optimizing the experience ofusers. We present a novel solution for the problem of service placement as atwo-phase approach, based on: 1) community finding using a scalable graph labelpropagation technique and 2) a decentralized election procedure to address themulti-objective challenge of optimizing service placement in CNs. Herein we: i)highlight the applicability of leader election heuristics which are importantfor service placement in community networks and scheduler-dependent scenarios;ii) present a parallel and distributed solution designed as a scalablealternative for the problem of service placement, which has mostly seencomputational approaches based on centralization and sequential execution.

Gelly-Scheduling: Distributed Graph Processing for Network Service Placement in Community Networks