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dc.contributor.authorDev, Vishnu C.
dc.contributor.authorDas, Uddipan
dc.contributor.authorNamboodiri, Vinod
dc.identifier.citationV. C. Dev, U. Das and V. Namboodiri, "Opportunistic Network Sharing for Transporting Smart Grid Data Traffic," 2019 North American Power Symposium (NAPS), Wichita, KS, USA, 2019, pp. 1-6en_US
dc.descriptionClick on the DOI link to access the article (may not be free).en_US
dc.description.abstractWith the inception of smart grid technologies, electric utilities have been attempting multifarious mechanisms to transport information from data generating entities to their information control centers. One such approach for carrying application data is to lease communication network capacity from Internet service providers (ISPs). Such dedicated capacity reservations on communication networks can be a costly proposition for electric utilities. This work proposes an alternative paradigm that takes advantage of the elastic nature of smart grid data traffic flows to piggyback (with authorization) on ISP networks without impacting the QoS of the primary flows on that network. Such an opportunistic scheme is expected to reduce operational costs for utilities to carry smart grid data traffic while providing guarantees to ISPs that their primary flows will be unaffected. The proposed opportunistic network sharing scheme builds upon a software-defined networking (SDN) approach at an intermediate router to provide QoS guarantees for regular ISP traffic. To mitigate the inevitable throttling of smart grid traffic during times of high network utilization in the shared network, a data granularity management algorithm is proposed that gracefully reduces the data granularity of smart grid (SG) data traffic in preemptive fashion in an attempt to meet application QoS needs.en_US
dc.relation.ispartofseriesNorth American Power Symposium (NAPS);2019
dc.subjectData aggregationen_US
dc.subjectSmart gridsen_US
dc.subjectSoftware defined networkingen_US
dc.titleOpportunistic network sharing for transporting smart grid data trafficen_US
dc.typeConference paperen_US
dc.rights.holder© 2019 IEEEen_US

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