• Journal of The Korean Astronomical Society
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• v.38 no.2
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• pp.223-226
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• 2005

We present the results of a 21cm radio continuum aperture synthesis mosaic of the Large Magellanic Cloud (LMC), made by combining data from 1344 separate pointing centers using the Australia Telescope Compact Array (ATCA) and the 64-m Parkes single-dish telescope. The resolution of the mosaicked images is 55' ( 10 pc, using a distance to the LMC) and a region $10^{\circ}{\times}12^{\circ}$ is surveyed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.8
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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.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.171-174
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• 2013

Virtualization technology opened a new era in the field of Data intensive, Grid and Cloud Computing. Today's Data centers are smarter than ever leveraging the Virtualization technology. In response to that, Dynamic consolidations of Virtual Machines (VMs) allow efficient resource management by live migration of VMs in the hosts. Moreover, each client typically has a service level agreement (SLA), leads to stipulation in dealing with energy-performance trade-off as aggressive consolidation may lead to performance degradation beyond the negotiation. In this paper we propose a Cloud Based CDN approach for allocation of VM that aims to maximize the client-level SLA. Our experiment result demonstrates significant enhancement of SLA at certain level.

• Journal of Information Processing Systems
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• v.16 no.1
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• pp.132-144
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• 2020

Cloud computing is an emerging technology based on the concept of enabling data access from anywhere, at any time, from any platform. The exponential growth of cloud users has resulted in the emergence of multiple issues, such as the workload imbalance between the virtual machines (VMs) of data centers in a cloud environment greatly impacting its overall performance. Our axis of research is the load balancing of a data center's VMs. It aims at reducing the degree of a load's imbalance between those VMs so that a better resource utilization will be provided, thus ensuring a greater quality of service. Our article focuses on two phases to balance the workload between the VMs. The first step will be the determination of the threshold of each VM before it can be considered overloaded. The second step will be a task allocation to the VMs by relying on an improved and faster version of the meta-heuristic "simulated annealing (SA)". We mainly focused on the acceptance probability of the SA, as, by modifying the content of the acceptance probability, we could ensure that the SA was able to offer a smart task distribution between the VMs in fewer loops than a classical usage of the SA.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.826-845
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• 2017

Outsourcing computation is one of the most important applications in cloud computing, and it has a huge ability to satisfy the demand of data centers. Modular exponentiation computation, broadly used in the cryptographic protocols, has been recognized as one of the most time-consuming calculation operations in cryptosystems. Previously, modular exponentiations can be securely outsourced by using two untrusted cloud servers. In this paper, we present two practical and secure outsourcing modular exponentiations schemes that support only one untrusted cloud server. Explicitly, we make the base and the index blind by putting them into a matrix before send to the cloud server. Our schemes provide better performance in higher efficiency and flexible checkability which support single cloud server. Additionally, there exists another advantage of our schemes that the schemes are proved to be secure and effective without any cryptographic assumptions.

• KNOM Review
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• v.21 no.2
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• pp.46-52
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• 2018

For data-intensive scientific workflow application experiments that leverage the cloud computing environment, large amounts of data can be distributed across multiple data centers in the cloud. The generated intermediate data can also be transmitted through access between different data centers. When the application is executed, the execution result is changed according to the location of the data since the intermediate data generated is used. However, existing data placement strategies do not consider the characteristics of scientific applications. In this paper, we define a data-intensive tasks and propose runtime data placement in that interval. Through the proposed data placement scheme, we analyze the scenarios considering the number of times in the data intensive tasks defined in this study and derive the results. In addition, performance was compared by analyzing runtime data placement times and runtime data placement overhead.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.1
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• pp.1-17
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• 2017

Mobile Cloud Computing has become a promising computing platform. It moves users' data to the centralized large data centers for users' mobile devices to conveniently access. Since the data storage service may not be fully trusted, many public verification algorithms are proposed to check the data integrity. However, these algorithms hardly consider the huge computational burden for the verifiers with resource-constrained mobile devices to execute the verification tasks. We propose an energy-efficient algorithm for assigning verification tasks (EEAVT) to optimize the energy consumption and assign the verification tasks by elastic and customizable ways. The algorithm prioritizes verification tasks according to the expected finish time of the verification, and assigns the number of checked blocks referring to devices' residual energy and available operation time. Theoretical analysis and experiment evaluation show that our algorithm not only shortens the verification finish time, but also decreases energy consumption, thus improving the efficiency and reliability of the verification.

• International Journal of Computer Science & Network Security
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• v.21 no.2
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• pp.158-170
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• 2021

Virtualization technologies are being adopted and broadly utilized in many fields and at different levels. In cloud computing, achieving load balancing across large distributed virtual machines is considered a complex optimization problem with an essential importance in cloud computing systems and data centers as the overloading or underloading of tasks on VMs may cause multiple issues in the cloud system like longer execution time, machine failure, high power consumption, etc. Therefore, load balancing mechanism is an important aspect in cloud computing that assist in overcoming different performance issues. In this research, we propose a new approach that combines the advantages of different task allocation algorithms like Round robin algorithm, and Random allocation with different threshold techniques like the VM utilization and the number of allocation counts using least connection mechanism. We performed extensive simulations and experiments that augment different scheduling policies to overcome the resource utilization problem without compromising other performance measures like makespan and execution time of the tasks. The proposed system provided better results compared to the original round robin as it takes into consideration the dynamic state of the system.

• Journal of Information Processing Systems
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• v.15 no.2
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• pp.440-448
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• 2019

The Internet of Things (IoT) is one of the main enablers for situation awareness needed in accomplishing smart cities. IoT devices, especially for monitoring purposes, have stringent timing requirements which may not be met by cloud computing. This deficiency of cloud computing can be overcome by fog computing for which fog nodes are placed close to IoT devices. Because of low capabilities of fog nodes compared to cloud data centers, fog nodes may not be deployed with all the services required by IoT devices. Thus, in this article, we focus on the issue of fog service placement and present the recent research trends in this issue. Most of the literature on fog service placement deals with determining an appropriate fog node satisfying the various requirements like delay from the perspective of one or more service requests. In this article, we aim to effectively place fog services in accordance with the pre-obtained service demands, which may have been collected during the prior time interval, instead of on-demand service placement for one or more service requests. The concept of the logical fog network is newly presented for the sake of the scalability of fog service placement in a large-scale smart city. The logical fog network is formed in a tree topology rooted at the cloud data center. Based on the logical fog network, a service placement approach is proposed so that services can be placed on fog nodes in a resource-effective way.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.563-564
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• 2017

The core of the cloud computing technology is the data center in that the networking technology is important. Cloud data centers are comprised of tens or even hundreds of thousands of physical servers, so networking technology is required for high-speed data transfer. These networking technologies also require scalability, fault tolerance, and agility. For these requirements, many multi-path based schemes have been proposed. However, it was mainly used for load balancing of traffic and select a path randomly. In this paper, a scheme that can construct a multipath using software defined networking technology and transmit the traffic in parallel by using the multipath to achieve a fast transmission speed, solve the scalability problem and fault tolerance is proposed.