• Journal of Information Processing Systems
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• 제13권3호
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• pp.476-490
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• 2017

In the centralized cloud controlled environment, the decision-making and monitoring play crucial role where in the host controller (HC) manages the resources across hosts in data center (DC). HC does virtual machine (VM) and physical hosts management. The VM management includes VM creation, monitoring, and migration. If HC down, the services hosted by various hosts in DC can't be accessed outside the DC. Decentralized VM management avoids centralized failure by considering one of the hosts from DC as HC that helps in maintaining DC in running state. Each host in DC has many VM's with the threshold limit beyond which it can't provide service. To maintain threshold, the host's in DC does VM migration across various hosts. The data in migration is in the form of plaintext, the intruder can analyze packet movement and can control hosts traffic. The incorporation of security mechanism on hosts in DC helps protecting data in migration. This paper discusses an approach for dynamic HC selection, VM selection and secure VM migration over cloud environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권6호
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• pp.1892-1912
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• 2022

With the massive demand and growth of cloud computing, virtualization plays an important role in providing services to end-users efficiently. However, with the increase in services over Cloud Computing, it is becoming more challenging to manage and run multiple Virtual Machines (VMs) in Cloud Computing because of excessive power consumption. It is thus important to overcome these challenges by adopting an efficient technique to manage and monitor the status of VMs in a cloud environment. Reduction of power/energy consumption can be done by managing VMs more effectively in the datacenters of the cloud environment by switching between the active and inactive states of a VM. As a result, energy consumption reduces carbon emissions, leading to green cloud computing. The proposed Efficient Dynamic VM Scheduling approach minimizes Service Level Agreement (SLA) violations and manages VM migration by lowering the energy consumption effectively along with the balanced load. In the proposed work, VM Scheduling for Efficient Dynamically Migrated VM (VMS-EDMVM) approach first detects the over-utilized host using the Modified Weighted Linear Regression (MWLR) algorithm and along with the dynamic utilization model for an underutilized host. Maximum Power Reduction and Reduced Time (MPRRT) approach has been developed for the VM selection followed by a two-phase Best-Fit CPU, BW (BFCB) VM Scheduling mechanism which is simulated in CloudSim based on the adaptive utilization threshold base. The proposed work achieved a Power consumption of 108.45 kWh, and the total SLA violation was 0.1%. The VM migration count was reduced to 2,202 times, revealing better performance as compared to other methods mentioned in this paper.

• 인터넷정보학회논문지
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• 제17권6호
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• pp.103-111
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• 2016

모바일 기기로부터 클라우드 서버로 태스크를 오프로딩하는 방법은 클라우드랫(cloudlet)의 도입으로 인해 향상되었다. 동적 오프로딩 알고리즘을 통해 모바일 장비는 수행할 타스크에 적절한 서버를 선택할 수 있다. 하지만 현재의 태스크 분배 방식은 의사결정에서 중요한 VM의 수를 고려하지 않고 있다. 본 논문은 클러스터된 데이터 센터에서 동적인 타스크 분배 방법을 제시한다. 또한 서버에서 자원의 과부하를 방지하기 위해 할당된 CPU에 따라 VM을 균형있게 클라우드 서버에 이주시키는 VM이주 기법을 제안한다. 클라우드 서버의 이주 방법을 향상시키기 위해 최대 CPU 관점에서 데이터 센터의 자원 용량도 고려한다. 시뮬레이션 결과, 제시한 태스크 분배 기법이 전반적으로 시스템의 성능을 향상시켰음을 나타내었다.

• 인터넷정보학회논문지
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• 제14권5호
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• pp.39-48
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• 2013

정의된 SLA의 QoS를 지키기 위해서, 클라우드 시스템은 동적인 사용 패턴에서 발생하는 변화무쌍한 작업 부하를 처리해야 한다. 서비스 관점이외에도 에너지 소비를 최소화 하는 것이 또한 새로운 관심사이다. 이는 클라우드 데이타 센터에서 가상화된 자원을 할당할 때 클라우드 제공자들은 에너지와 성능의 상관관계를 고려해야 한다. 본 논문에서는 호스트 컴퓨터의 작업부하 수준을 탐지하기 위해 동적 임계치를 기반으로 한 자원 프로비저닝 방안을 제시한다. VM선정 정책은 이주할 VM을 선택하기 위해 활용 데이터를 사용하며, VM 할당 정책은 서비스 평판도에 따라 VM들을 호스트에 지정한다. 시뮬레이션을 통해 연구결과를 평가하였으며, 시뮬레이션 결과 이주를 지원하지 않는 비 전력 방법뿐만 아니라 동적 임계치, 임의 선정 정책보다 성능이 우수함을 보였다.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권9호
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• pp.4165-4187
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• 2016

As an emerging technology, cloud computing is a revolution in information technology that attracts significant attention from both public and private sectors. In this paper, we proposed a dynamic approach for live migration to obviate overloaded machines. This approach is applied on OpenStack, which rapidly grows in an open source cloud computing platform. We conducted a cost-aware dynamic live migration for virtual machines (VMs) at an appropriate time to obviate the violation of service level agreement (SLA) before it happens. We conducted a preemptive migration to offload physical machine (PM) before the overload situation depending on the predictive method. We have carried out a distributed model, a predictive method, and a dynamic threshold policy, which are efficient for the scalable environment as cloud computing. Experimental results have indicated that our model succeeded in avoiding the overload at a suitable time. The simulation results from our solution remarked the very efficient reduction of VM migrations and SLA violation, which could help cloud providers to deliver a good quality of service (QoS).

• 인터넷정보학회논문지
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• 제18권4호
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• pp.51-59
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• 2017

클라우드 컴퓨팅이 발전하면서, 전체적인 관리 비용을 최소화하기 위해 자원 관리 기술이 중요하다. 클라우드 환경에서 사용자 선호도에 기반한 호스트의 활용과 가상머신들의 요구사항은 본질적으로 자주 바뀐다. 이러한 문제를 해결하기 위해, 호스트와 가상 머신들이 분류가 되지 않은 상황에서 효율적인 자원 할당 방법을 연구할 필요가 있다. 에너지 소비를 절약하기 위해 액티브 호스트를 줄일 때, 가상머신들을 다른 호스트로 이주할때 임계값을 사용한다. 가상머신의 자원 요구량과 호스트의 자원 이용량을 분류할 때 Fuzzy Logic을 이용하여 적응성 가상머신 할당 및 이주 방법을 제안한다. 제안한 방법은 자원의 요구량에 따라 가상머신들을 분류한 뒤 가장 적은 자원활용도를 갖는 호스트에게 자원을 할당하며, 과부하된 호스트들로부터 가상머신을 이주시킬 때 상위 임계치를 설정하기 위해 각 호스트들의 자원 활용도가 사용된다. 이주하기 위한 후보 가상머신들을 선택할 때, 호스트에서 높은 자원을 가진 가상머신을 선택한다. 시뮬레이션을 통해 연구 결과를 평가하였고, 평가 결과 다른 가상머신 할당 방법들보다 효율적임을 증명하였다.

• 정보화연구
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• 제10권1호
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• pp.1-11
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• 2013

Various computing systems are used in naval ships. Since each system has a single purpose and its applications are tightly coupled with the physical machine, applications cannot share physical resources with each other. It is hard to utilize resources efficiently in conventional naval shipboard computing environment. In this paper, we present an integration architecture for virtualized naval shipboard computing systems based on open architecture. Our proposed architecture integrates individual computing resources into one single integrated hardware pool so that the OS and applications are encapsulated as a VM. We consider the issue of varying needs of all applications in a naval ship that have different purposes, priorities and requirements. We also present parallel VM migration algorithm that improves the process time of resource reallocation of given architecture. The evaluation results with the prototype system show that our algorithm performs better than conventional resource reallocation algorithm in process time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권8호
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• pp.1825-1842
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• 2013

Rapid growth of the IT industry has led to significant energy consumption in the last decade. Data centers swallow an enormous amount of electrical energy and have high operating costs and carbon dioxide excretions. In response to this, the dynamic consolidation of virtual machines (VMs) allows for efficient resource management and reduces power consumption through the live migration of VMs in the hosts. Moreover, each client typically has a service level agreement (SLA), this leads to stipulations in dealing with energy-performance trade-offs, as aggressive consolidation may lead to performance degradation beyond the negotiation. In this paper we propose a heuristic based resource allocation of VM selection and a VM allocation approach that aims to minimize the total energy consumption and operating costs while meeting the client-level SLA. Our experiment results demonstrate significant enhancements in cloud providers' profit and energy savings while improving the SLA at a certain level.

• 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.