• 디지털융복합연구
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• 제14권2호
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• pp.235-243
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• 2016

모바일 및 사물인터넷 기술의 발전, 대용량 빅데이터 처리, 그리고 클라우드 컴퓨팅 기술의 발전에 힘입어 기존 데이터센터는 클라우드 데이터센터로 변모하고 있다. 클라우드 데이터센터는 ICT 자원들을 가상화하여 운영함으로써 에너지 및 시설 자원을 효율적으로 관리하고 사용자들의 서비스 요구에 빠르게 대응하는 것을 목표로 하고 있다. 이에 따라 클라우드 데이터센터 네트워크는 가상화된 ICT 자원을 효율적으로 제공할 수 있도록 구성되어야 한다. 본 논문은 클라우드 데이터센터에 적합한 네트워크 구조 및 네트워킹 기술을 분석하고 이를 효과적으로 운용하기 위한 방안을 제시한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권11호
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• pp.5357-5381
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• 2018

Cloud computing offers a wide range of on-demand resources over the internet. Utility-based resource allocation in cloud data centers significantly increases the number of cloud users. Heavy usage of cloud data center encounters many problems such as sacrificing system performance, increasing operational cost and high-energy consumption. Therefore, the result of the system damages the environment extremely due to heavy carbon (CO2) emission. However, dynamic allocation of energy-efficient resources in cloud data centers overcomes these problems. In this paper, we have proposed Energy and Service Level Agreement (SLA) Aware Resource Allocation Heuristic Algorithms. These algorithms are essential for reducing power consumption and SLA violation without diminishing the performance and Quality-of-Service (QoS) in cloud data centers. Our proposed model is organized as follows: a) SLA violation detection model is used to prevent Virtual Machines (VMs) from overloaded and underloaded host usage; b) for reducing power consumption of VMs, we have introduced Enhanced minPower and maxUtilization (EMPMU) VM migration policy; and c) efficient utilization of cloud resources and VM placement are achieved using SLA-aware Modified Best Fit Decreasing (MBFD) algorithm. We have validated our test results using CloudSim toolkit 3.0.3. Finally, experimental results have shown better resource utilization, reduced energy consumption and SLA violation in heterogeneous dynamic cloud environment.

• 디지털융복합연구
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• 제11권12호
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• pp.467-477
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• 2013

클라우드 컴퓨팅 서비스가 대중적으로 보급됨에 따라 공공분야에서 해당 서비스의 도입에 대한 관심이 증가하고 있다. 이에 따라 국내에서는 클라우드 컴퓨팅을 공공분야에 도입하거나 계획하고 있으며 점차 구체적으로 구축하고 있다. 하지만 공공분야에서의 클라우드 도입 및 활성화를 위해서는 서비스 가용성 장애요인 및 인증 받지 않은 사용자의 무단 접근, 불분명한 출처로부터 다운로드 받은 데이터로 인한 클라우드 데이터센터의 신뢰성 저하 등의 보안 위협에 대한 해결방안을 모색할 필요성이 있다. 따라서 본 논문에서는 공공기관 클라우드 데이터센터에서 활용 가능한 공개키 기반의 안전한 데이터 관리 기법에 대해서 제안한다. 이를 통해 공공기관에 클라우드 컴퓨팅을 도입할 때 인증 받은 사용자만 데이터센터를 사용할 수 있고, 공공 데이터의 중요도와 난이도를 공용데이터, 개인데이터, 기밀데이터로 설정해주어 체계적이고 안전하며 효율적으로 데이터 관리를 가능하게 한다. 따라서 공공기관에서의 클라우드 서비스에 대해 전반적인 보안성과 편의성을 향상시킬 수 있을 것으로 기대된다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권12호
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• pp.4759-4775
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• 2015

The reduction of power consumption in large-scale datacenters is highly-dependent on the use of virtualization to consolidate multiple workloads. However, these consolidation strategies must also take into account additional important parameters such as performance, reliability, and profitability. Resolving these conflicting goals is often the major challenge encountered in the design of optimization strategies for cloud data centers. In this paper, we put forward a data center monitoring strategy which dynamically alters its approach depending on the cloud system's current state. Results show that our proposed scheme outperformed strategies which only focus on a single metric such as SLA-Awareness and Energy Efficiency.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권3호
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• pp.1362-1376
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• 2016

A cloud computing system can be characterized by the provision of resources in the form of services to third parties on a leased, usage-based basis, as well as the private infrastructures maintained and utilized by individual organizations. To attain the desired reliability and energy efficiency in a cloud data center, trade-offs need to be carried out between system performance and power consumption. Resolving these conflicting goals is often the major challenge encountered in the design of optimization strategies for cloud data centers. The work presented in this paper is directed towards the development of an Energy-efficient and Performance-aware Cloud System equipped with strategies for dynamic switching of optimization approach. Moreover, a platform is also provided for the deployment of a Wind Farm CMS (Condition Monitoring System) which allows ubiquitous access. Due to the geographically-dispersed nature of wind farms, the CMS can take advantage of the cloud's highly scalable architecture in order to keep a reliable and efficient operation capable of handling multiple simultaneous users and huge amount of monitoring data. Using the proposed cloud architecture, a Wind Farm CMS is deployed in a virtual platform to monitor and evaluate the aging conditions of the turbine's major components in concurrent, yet isolated working environments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권11호
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• pp.5179-5202
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• 2018

Transmission Control Protocol (TCP) is the most widely used protocol in the cloud data centers today. However, cloud data centers using TCP experience many issues as TCP was designed based on the assumption that it would primarily be used in Wide Area Networks (WANs). One of the major issues with TCP in the cloud data centers is the Incast issue. This issue arises because of the many-to-one communication pattern that commonly exists in the modern cloud data centers. In many-to-one communication pattern, multiple senders simultaneously send data to a single receiver. This causes packet loss at the switch buffer which results in TCP throughput collapse that leads to high Flow Completion Time (FCT). Recently, Software-Defined Networking (SDN) has been used by many researchers to mitigate the Incast issue. In this paper, a detailed survey of various SDN based solutions to the Incast issue is carried out. In this survey, various SDN based solutions are classified into four categories i.e. TCP Receive Window based solutions, Tuning TCP Parameters based solutions, Quick Recovery based solutions and Application Layer based solutions. All the solutions are critically evaluated in terms of their principles, advantages, and shortcomings. Another important feature of this survey is to compare various SDN based solutions with respect to different performance metrics e.g. maximum number of concurrent senders supported, calculation of delay at the controller etc. These performance metrics are important for deployment of any SDN based solution in modern cloud data centers. In addition, future research directions are also discussed in this survey that can be explored to design and develop better SDN based solutions to the Incast issue.

• ETRI Journal
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• 제43권1호
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• pp.53-63
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• 2021

Cloud computing has drastically reduced the price of computing resources through the use of virtualized resources that are shared among users. However, the established large cloud data centers have a large carbon footprint owing to their excessive power consumption. Inefficiency in resource utilization and power consumption results in the low fiscal gain of service providers. Therefore, data centers should adopt an effective resource-management approach. In this paper, we present a novel load-balancing framework with the objective of minimizing the operational cost of data centers through improved resource utilization. The framework utilizes a modified genetic algorithm for realizing the optimal allocation of virtual machines (VMs) over physical machines. The experimental results demonstrate that the proposed framework improves the resource utilization by up to 45.21%, 84.49%, 119.93%, and 113.96% over a recent and three other standard heuristics-based VM placement approaches.

• 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.

• International journal of advanced smart convergence
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• 제1권2호
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• pp.52-58
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• 2012

Green cloud computing refers to the green ambient benefits that information technology services delivered over the Internet can offer for the society. The green meaning environment friendly and cloud computing is a traditional symbol for the Internet and a type of service provider. Cloud computing has drastically increased the number of datacenters and the energy consumption of data centers and that has become a critical issue which is extremely important in green ambience. These days the cloud data center needs high energy resources that leads to high operational cost and also maximizes CO2 - carbon footprint that pollutes the ambience which is not to be considered as green ambience. So we need to provide a way that leads us to green ambience. Cloud computing for the green ambience should be designed in a way which will utilize less energy resources and to minimize the CO2 -carbon footprint, known as green cloud. In this paper we discuss various elements of Clouds which contributes to minimize the total energy consumption and the carbon emission so as to enable green ambience through green cloud computing.

• Journal of information and communication convergence engineering
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• 제16권4호
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• pp.264-270
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• 2018

In our research study, we aim at optimizing multiple load in cloud, effective resource allocation and lesser response time for the job assigned. Using Hadoop on datacenter is the best and most efficient analytical service for any corporates. To provide effective and reliable performance analytical computing interface to the client, various cloud service providers host Hadoop clusters. The previous works done by many scholars were aimed at execution of workflows on Hadoop platform which also minimizes the cost of virtual machines and other computing resources. Earlier stochastic hill climbing technique was applied for single parameter and now we are working to optimize multiple parameters in the cloud data centers with proposed heuristic hill climbing. As many users try to priorities their job simultaneously in the cluster, resource optimized workflow scheduling technique should be very reliable to complete the task assigned before the deadlines and also to optimize the usage of the resources in cloud.