• KIPS Transactions on Computer and Communication Systems
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• v.4 no.3
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• pp.81-84
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• 2015

Cloud service is one of major technologies in modern IT business. Due to the dynamics of user demands, service providers need VM(Virtual Machine) provisioning mechanism to predict the amount of resources demanded by cloud users for the next service and to prepare the resources. VM provisioning provides the QoS to cloud user and maximize the revenue of a service provider by minimizing the expense. In this paper, we propose a new VM provisioning technique to minimize the total expense of a service provider by minimizing the expected value of the expense based on the predicted demands of users. To evaluate the effectiveness of our prediction technique, we compare the total expense of our technique with these of the other prediction techniques with a series of real trace data.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.155-156
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• 2013

VM 간섭은 VM 프로비저닝을 할 때 예상된 VM 의 컴퓨팅 자원이 실제와 다르지 않도록 하기 위해 반드시 고려되어야 할 사항이다. 이에 본 논문에서는 예상된 VM 의 컴퓨팅 자원을 사용자가 보장받을 수 있도록 랜덤 워크를 이용해 간섭을 고려한 필요 자원을 구하는 방법에 대해 다루고 있다.

• Journal of Internet Computing and Services
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• v.14 no.5
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• pp.39-48
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• 2013

A cloud system has to deal with highly variable workloads resulting from dynamic usage patterns in order to keep the QoS within the predefined SLA. Aside from the aspects regarding services, another emerging concern is to keep the energy consumption at a minimum. This requires the cloud providers to consider energy and performance trade-off when allocating virtualized resources in cloud data centers. In this paper, we propose a resource provisioning approach based on dynamic thresholds to detect the workload level of the host machines. The VM selection policy uses utilization data to choose a VM for migration, while the VM allocation policy designates VMs to a host based on its service reputation. We evaluated our work through simulations and results show that our work outperforms non-power aware methods that don't support migration as well as those based on static thresholds and random selection policy.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.04a
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• pp.234-235
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• 2012

본 논문에서는 모바일 단말에 최적화원 VM(Virtual Machine)인 경량화된 PVI(Private Virtual Instance)를 프로비저닝하여 가상단발상의 Rich 앱에 고성능 컴퓨팅, 스토리지, 네트워크를 제공하고 모바일 클라우드 서비스를 위한 개방형 개발 환경 및 서비스 환경을 제공하는 새로운 모바일 클라우드 모델을 제안한다.

• Journal of Internet Computing and Services
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• v.15 no.3
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• pp.1-10
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• 2014

The cloud computing paradigm introduced pay-per-use models in which IT services can be created and scaled on-demand. However, service providers are still concerned about the constraints imposed by their physical infrastructures. In order to keep the required QoS and achieve the goal of upholding the SLA, virtualized resources must be efficiently consolidated to maximize system throughput while keeping energy consumption at a minimum. Using ANN, we propose a predictive SLA-aware approach for consolidating virtualized resources in a cloud environment. To maintain the QoS and to establish an optimal trade-off between performance and energy efficiency, the server's utilization threshold dynamically adapts to the physical machine's resource consumption. Furthermore, resource-intensive VMs are prevented from getting underprovisioned by assigning them to hosts that are both capable and reputable. To verify the performance of our proposed approach, we compare it with non-optimized conventional approaches as well as with other previously proposed techniques in a heterogeneous cloud environment setup.