• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권9호
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• pp.4320-4333
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• 2017

Energy-efficient virtual resource allocation algorithm has become a hot research topic in cloud computing. However, most of the existing allocation schemes cannot ensure each type of resource be fully utilized. To solve the problem, this paper proposes a virtual machine (VM) allocation algorithm on the basis of multi-dimensional resource, considering the diversity of user's requests. First, we analyze the usage of each dimension resource of physical machines (PMs) and build a D-dimensional resource state model. Second, we introduce an energy-resource state metric (PAR) and then propose an energy-aware multi-dimensional resource allocation algorithm called MRBEA to allocate resources according to the resource state and energy consumption of PMs. Third, we validate the effectiveness of the proposed algorithm by real-world datasets. Experimental results show that MRBEA has a better performance in terms of energy consumption, SLA violations and the number of VM migrations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권8호
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• pp.3203-3215
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• 2015

Due to the high growth of SNS population, service scalability is one of the critical issues to be addressed. The cloud environment provides the flexible computing and storage resources for services deployment, which fits the characteristics of scalable SNS deployment. However, if the SNS related information is not properly placed, it will cause unbalance load and heavy transmission cost on the storage virtual machine (VM) and cloud data center (CDC) network. In this paper, we characterize the SNS into a graph model based on the users' associations and interest correlations. The node weight represents the degree of associations, which can be indexed by the number of friends or data sources, and the link weight denotes the correlation between users/data sources. Then, based on the SNS graph, the two-step algorithm is proposed in this paper to determine the placement of SNS related data among VMs. Two k-means based clustering schemes are proposed to allocate social data in proper VM and physical servers for pre-configured VM and dynamic VM environment, respectively. The experimental example was conducted and to illustrate and compare the performance of the proposed schemes.

• International Journal of Computer Science & Network Security
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• 제22권4호
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• pp.147-158
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• 2022

Cloud Computing offers flexible, on demand, ubiquitous resources for cloud users. Cloud users are provided computing resources in a virtualized environment. In order to meet the growing demands for computing resources, data centres contain a large number of physical machines accommodating multiple virtual machines. However, cloud data centres cannot utilize their computing resources to their total capacity. Several policies have been proposed for improving energy proficiency and computing resource utilization in cloud data centres. Virtual machine placement is an effective method involving efficient mapping of virtual machines to physical machines. However, the availability of many physical machines accommodating multiple virtual machines in a data centre has made the virtual machine placement problem a non deterministic polynomial time hard (NP hard) problem. Metaheuristic algorithms have been widely used to solve the NP hard problems of multiple and conflicting objectives, such as the virtual machine placement problem. In this context, we presented essential concepts regarding virtual machine placement and objective functions for optimizing different parameters. This paper provides a taxonomy of metaheuristic algorithms for the virtual machine placement method. It is followed by a review of prominent research of virtual machine placement methods using meta heuristic algorithms and comparing them. Finally, this paper provides a conclusion and future research directions in virtual machine placement of cloud computing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권2호
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• pp.312-334
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• 2023

In large-scale computing, cloud computing plays an important role by sharing globally-distributed resources. The evolution of cloud has taken place in the development of data centers and numerous servers across the globe. But the cloud information centers incur huge operational costs, consume high electricity and emit tons of dioxides. It is possible for the cloud suppliers to leverage their resources and decrease the consumption of energy through various methods such as dynamic consolidation of Virtual Machines (VMs), by keeping idle nodes in sleep mode and mistreatment of live migration. But the performance may get affected in case of harsh consolidation of VMs. So, it is a desired trait to have associate degree energy-performance exchange without compromising the quality of service while at the same time reducing the power consumption. This research article details a number of novel algorithms that dynamically consolidate the VMs in cloud information centers. The primary objective of the study is to leverage the computing resources to its best and reduce the energy consumption way behind the Service Level Agreement (SLA)drawbacks relevant to CPU load, RAM capacity and information measure. The proposed VM consolidation Algorithm (PVMCA) is contained of four algorithms: over loaded host detection algorithm, VM selection algorithm, VM placement algorithm, and under loading host detection algorithm. PVMCA is dynamic because it uses dynamic thresholds instead of static thresholds values, which makes it suggestion for real, unpredictable workloads common in cloud data centers. Also, the Algorithms are adaptive because it inevitably adjusts its behavior based on the studies of historical data of host resource utilization for any application with diverse workload patterns. Finally, the proposed algorithm is online because the algorithms are achieved run time and make an action in response to each request. The proposed algorithms' efficiency was validated through different simulations of extensive nature. The output analysis depicts the projected algorithms scaled back the energy consumption up to some considerable level besides ensuring proper SLA. On the basis of the project algorithms, the energy consumption got reduced by 22% while there was an improvement observed in SLA up to 80% compared to other benchmark algorithms.

• 정보과학회 논문지
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• 제42권11호
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• pp.1322-1331
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• 2015

vCPU(virtual CPU)는 하이퍼바이저 스케줄러에 의해서 실행 상태와 정지 상태를 반복하는 특징을 갖는다. 정지 상태인 vCPU에게 전달된 이벤트는 vCPU가 실행 상태가 될 때까지 처리되지 못하고 지연 된다. 이러한 이벤트 지연 현상은 I/O 지연 현상으로 나타난다. SMP(symmetric multiprocessing) 가상 머신은 다수의 vCPU를 이용하기 때문에 이벤트를 어느 vCPU에게 전달하는지에 따라 SMP 가상 머신의 이벤트 지연 시간이 달라 질 수 있다. SMP 가상 머신의 이벤트 지연 시간을 줄이기 위해서 본 논문에서는 각 vCPU의 동작 상태에 따라서 이벤트를 전달하는 새로운 기법인 이벤트 라우팅 기법을 제안한다. 제안한 이벤트 라우팅 기법을 Xen ARM 하이퍼바이저에 적용하였고 다양한 실험 환경에서 네트워크 RTT(round trip time)와 TCP 대역폭 측정을 통해 I/O 지연 시간 감소를 확인하였다. 기존 Xen ARM과 비교하여 네트워크 RTT는 최대 94% 감소하였고, TCP 대역폭은 최대 35% 증가하였다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2017년도 춘계학술발표대회
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• pp.246-249
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• 2017

악성코드 분석을 실제머신에서 진행하는 도중 시스템이 손상될 경우 복원에 어려움이 있다. 이에 따라 역공학 분석가들은 일반적으로 가상환경에서 분석을 진행한다. 가상환경의 경우 실제머신 호스트 운영체제와는 독립되어 있고 악성코드를 발현하여 시스템이 손상이 되더라도 이전 스냅 샷으로 복원하는 것이 용이하기 때문에 가상환경에서 악성행위 동작을 분석한다. 하지만, 최근 들어 악성코드가 점점 지능화되고 있으며 이에 따라 악성코드가 VM(Virtual Machine)환경에서는 동작하지 않는 Anti-VM 기술이 적용된 악성코드가 증가하고 있다. 따라서, 본 논문에서는 가상환경에서 Anti-VM 기술이 적용된 악성코드를 분석할 수 있는 위한 환경 연구를 진행한다. 이에 따라, 악성코드가 가상환경을 탐지하는 기법을 분석하고 각 탐지기법을 방지할 수 있는 방안을 제안한다. 이를 통해 동적분석을 하지 못하도록 하는 분석 방해 지연 기술 중 하나인 Anti-VM 기술이 적용된 악성코드의 분석 결과를 향상 시키는 것을 목표로 한다.

• 정보처리학회논문지A
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• 제12A권5호
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• pp.333-340
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• 2005

본 논문에서는 KVM WabaVM의 네이티브 함수 연결 기법을 기반으로 보다 새로운 네이티브 함수 연결을 위한 테이블을 설계하고 구현하였다. 이를 위해 어댑터 모델을 설계하고 기존 네이티브 함수 연결 테이블을 구현하였으며 실제로 구현된 결과에 대한 다양한 실험 결과를 제시 하였다.

• ETRI Journal
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• 제36권5호
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• pp.741-751
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• 2014

Smart TV is expected to bring cloud services based on virtualization technologies to the home environment with hardware and software support. Although most physical resources can be shared among virtual machines (VMs) using a time sharing approach, allocating the proper amount of memory to VMs is still challenging. In this paper, we propose a novel mechanism to dynamically balance the memory allocation among VMs in virtualized Smart TV systems. In contrast to previous studies, where a virtual machine monitor (VMM) is solely responsible for estimating the working set size, our mechanism is symbiotic. Each VM periodically reports its memory usage pattern to the VMM. The VMM then predicts the future memory demand of each VM and rebalances the memory allocation among the VMs when necessary. Experimental results show that our mechanism improves performance by up to 18.28 times and reduces expensive memory swapping by up to 99.73% with negligible overheads (0.05% on average).

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권4호
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• pp.1302-1320
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• 2015

In cloud, everything can be provided as a service wherein a large number of users submit their jobs and wait for their services. hus, scheduling plays major role for providing the resources efficiently to the submitted jobs. The brainwave of the proposed ork is to improve user satisfaction, to balance the load efficiently and to bolster the resource utilization. Hence, this paper roposes an Adaptive Multilevel Scheduling System (AMSS) which will process the jobs in a multileveled fashion. The first level ontains Preprocessing Jobs with Multi-Criteria (PJMC) which will preprocess the jobs to elevate the user satisfaction and to itigate the jobs violation. In the second level, a Deadline Based Dynamic Priority Scheduler (DBDPS) is proposed which will ynamically prioritize the jobs for evading starvation. At the third level, Contest Mapping Jobs with Virtual Machine (CMJVM) is roposed that will map the job to suitable Virtual Machine (VM). In the last level, VM Scheduler is introduced in the two-tier VM rchitecture that will efficiently schedule the jobs and increase the resource utilization. These contributions will mitigate job iolations, avoid starvation, increase throughput and maximize resource utilization. Experimental results show that the performance f AMSS is better than other algorithms.

• 한국위성정보통신학회논문지
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• 제9권4호
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• pp.127-133
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• 2014

본 논문에서는 탑재운영절차서 실행환경을 위한 Lua 인터프리터 기반의 가상머신 설계와 기능 및 성능분석 결과를 나타낸다. 한국항공우주연구원에서 계획 중인 달 탐사 임무를 온보드상에서 자율적으로 운영하기 위해 탑재운영절차서 실행환경의 개발이 요구되어졌다. 탑재운영절차서는 위성에 탑재되어 지상 간섭없이 자율적으로 임무 수행을 가능케 함으로써 전파 지연과 제한된 데이터 통신용량을 갖는 심우주 임무들에서 이미 적용되고 있다. 가상머신의 실행엔진인 인터프리터는 고급언어로 작성된 원시코드를 한줄씩 번역하고 실행하므로 컴파일러에 의해 생성된 코드가 실행되는 것에 비해서 실행 속도가 현저하게 느리다. 이를 극복하기위해 레지스터 기반의 Lua 인터프리터를 적용하여 탑재운영절차서 실행환경 설계 및 구현하였으며 실험을 통해 여러 요소들에 따른 성능분석을 수행하였다. 성능분석 결과는 탑재운영절차서 스케줄링 방안 뿐 아니라 Lua 인터프리터를 적용하는 시스템에 적용될 수 있을 것으로 기대된다.