Conference Papers

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    An approach for dynamic scaling of resources in enterprise cloud
    (IEEE Computer Society, 2013) Kanagala, K.; Chandra Sekaran, K.
    Elasticity is one of the key governing properties of cloud computing that has major effects on cost and performance directly. Most of the popular Infrastructure as a Service (IaaS) providers such as Amazon Web Services (AWS), Windows Azure, Rack space etc. work on threshold-based auto-scaling. In current IaaS environments there are various other factors like "Virtual Machine (VM)-turnaround time", "VM-stabilization time" etc. that affect the newly started VM from start time to request servicing time. If these factors are not considered while auto-scaling, then they will have direct effect on Service Level Agreement (SLA) implementations and users' response time. Therefore, these thresholds should be a function of load trend, which makes VM readily available when needed. Hence, we developed an approach where the thresholds adapt in advance and these thresholds are functions of all the above mentioned factors. Our experimental results show that our approach gives the better response time. © 2013 IEEE.
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    MatchCloud: Service Matching for Multi Cloud Marketplace
    (Institute of Electrical and Electronics Engineers Inc., 2021) Chakma, A.; Kumar, S.; Mahato, P.K.; Satpathy, A.; Addya, S.K.
    The 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.