Towards network-aware service placement in community network micro-clouds
Document typeConference report
Rights accessRestricted access - publisher's policy
Cloud services in community networks have been enabled by micro-cloud providers. They form community network micro-clouds (CNMCs), which grow organically, i.e. without being planned and optimized beforehand. Services running in community networks face specific challenges intrinsic to these infrastructures, such as the limited capacity of nodes and links, their dynamics and geographic distribution. CNMCs are used to deploy distributed applications, such as streaming and storage services, which transfer significant amounts of data between the nodes on which they run. Currently there is no support given to users for enabling them to chose better or the best option for specific service deployments. This paper looks at the next step in community network cloud service deployments, by taking network characteristics into account when deciding placement of service instances. We propose a service placement algorithm (PASP) that minimizes the service overlay diameter, while fulfilling service specific criteria. First, we characterize with simulations the potential performance gains of our approach. Secondly, we apply our algorithm to deploy a distributed storage service currently used in Guifi.net, and evaluate it in the real production network, assessing the performance and effects of our algorithm. We find that our PASP algorithm reduces the client reading times by an average of 16% (with a max. improvement of 31 %) compared to the currently used organic placement scheme. Our results show how the choice of an appropriate set of nodes, taken from a larger resource pool, can influence service performance significantly.
CitationSelimi, M., Vega, D., Freitag, F., Veiga, L. Towards network-aware service placement in community network micro-clouds. A: International Conference on Parallel and Distributed Computing. "Euro-Par 2016: Parallel Processing 22nd International Conference on Parallel and Distributed Computing: Grenoble, France: August 24-26, 2016: proceedings". Grenoble: Springer, 2016, p. 376-388.