Please use this identifier to cite or link to this item: https://idr.nitk.ac.in/jspui/handle/123456789/14929
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dc.contributor.authorChakma A.
dc.contributor.authorKumar S.
dc.contributor.authorMahato P.K.
dc.contributor.authorSatpathy A.
dc.contributor.authorAddya S.K.
dc.date.accessioned2021-05-05T10:16:01Z-
dc.date.available2021-05-05T10:16:01Z-
dc.date.issued2021
dc.identifier.citation2021 International Conference on COMmunication Systems and NETworkS, COMSNETS 2021 , Vol. , , p. 127 - 130en_US
dc.identifier.urihttps://doi.org/10.1109/COMSNETS51098.2021.9352821
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/14929-
dc.description.abstractThe modern applications execute in the cloud via independent executable entities called virtual machines (VMs). In a typical multi-SP market with variable pricing and heterogeneous resource demands of VMs, resource allocation/placement is particularly challenging. To maximize the social welfare of the multi-SP markets, in this paper, we propose a resource allocation technique called MatchCloud formulated as a one-to-many matching game. Owing to the in-applicability of the classical deferred acceptance algorithm (DAA) due to size heterogeneity, we adopt a modified version of the algorithm. Moreover, preference generation is crucial for matching markets. Hence, we also present a simple yet efficient technique to assign preferences to two different stakeholders, i.e., VMs and SPs. Simulation results show that VM proposing RDA performs better compared to when SPs propose. © 2021 IEEE.en_US
dc.titleMatchCloud: Service Matching for Multi Cloud Marketplaceen_US
dc.typeConference Paperen_US
Appears in Collections:2. Conference Papers

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