• Journal of Environmental Science International
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• v.33 no.1
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• pp.43-57
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• 2024

The possible experimental time for cloud seeding was analyzed in South Korea. Rain gauge and radar precipitation data collected from September 2017 to August 2022 in from the three main target stations of cloud seeding experimentation (Daegwallyeong, Seoul, and Boryeong) were analyzed. In this study, the assumption that rainfall and cloud enhancement originating from the atmospheric updraft is a necessary condition for the cloud seeding experiment was applied. First, monthly and seasonal means of the precipitation duration and frequency were analyzed and cloud seeding experiments performed in the past were also reanalyzed. Results of analysis indicated that the experiments were possible during a monthly average of 7,025 minutes (117 times) in Daegwallyeong, 4,849 minutes (81 times) in Seoul, and 5,558 minutes (93 times) in Boryeong, if experimental limitations such as the insufficient availability of aircraft is not considered. The seasonal average results showed that the possible experimental time is the highest in summer at all three stations, which seems to be owing to the highest precipitable water in this period. Using the radar-converted precipitation data, the cloud seeding experiments were shown to be possible for 970-1,406 hours (11-16%) per year in these three regions in South Korea. This long possible experimental time suggests that longer duration, more than the previous period of 1 hour, cloud seeding experiments are available, and can contribute to achieving a large accumulated amount of enhanced rainfall.

• Electronics and Telecommunications Trends
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• v.37 no.5
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• pp.62-69
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• 2022

In a situation where applications determine business competitiveness, they cannot respond to varying customer requirements without the cloud's flexibility and scalability. Companies have begun seeking ways to enjoy the advantages of the cloud fully, and the concept of "Cloud Native" is emerging as a solution to the problem. Cloud Native is now a target of interest in the market. Microservice and serverless functions can play a vital role in cloud-native architecture. Microservice arranges applications into various independent services, each offering certain functionality through mutual networking. eBPF is attracting attention as a cloud-native networking solution that quickly supports microservice features that repeat creation/deletion. This study identifies the characteristics of eBPF-based networking and evaluates cloud-native networking and secure networking using eBPF.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.2
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• pp.341-347
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• 2012

In cloud computing, a enterprise or a client can use resources of computers that they are not own them. In case of Web 2.0 applications, such as Facebook, it is difficult to predict the maximum popularity of the service. But, the cloud computing may give a solution about this problem without high cost, thus becomes wildly popular. One of the advantage of cloud computing is providing a high availability. To provide the availability when the cloud computing that has shared-nothing architecture, strict consistency is not well with cloud computing. So, some consistency was proposed including the eventual consistency that was weaken the traditional consistency and has been adopted to many cloud applications. In this paper, we observe various consistency criteria that can adjust to cloud computing and discuss about some consistency that can be adapted to many applications of cloud computing.

• International Journal of Contents
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• v.13 no.2
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• pp.29-34
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• 2017

Cloud computing is becoming an effective and efficient way of computing resources and computing service integration. Through centralized management of resources and services, cloud computing delivers hosted services over the internet, such that access to shared hardware, software, applications, information, and all resources is elastically provided to the consumer on-demand. The main enabling technology for cloud computing is virtualization. Virtualization software creates a temporarily simulated or extended version of computing and network resources. The objectives of virtualization are as follows: first, to fully utilize the shared resources by applying partitioning and time-sharing; second, to centralize resource management; third, to enhance cloud data center agility and provide the required scalability and elasticity for on-demand capabilities; fourth, to improve testing and running software diagnostics on different operating platforms; and fifth, to improve the portability of applications and workload migration capabilities. One of the key features of cloud computing is elasticity. It enables users to create and remove virtual computing resources dynamically according to the changing demand, but it is not easy to make a decision regarding the right amount of resources. Indeed, proper provisioning of the resources to applications is an important issue in IaaS cloud computing. Most web applications encounter large and fluctuating task requests. In predictable situations, the resources can be provisioned in advance through capacity planning techniques. But in case of unplanned and spike requests, it would be desirable to automatically scale the resources, called auto-scaling, which adjusts the resources allocated to applications based on its need at any given time. This would free the user from the burden of deciding how many resources are necessary each time. In this work, we propose an analytical and efficient VM-level scaling scheme by modeling each VM in a data center as an M/M/1 processor sharing queue. Our proposed VM-level scaling scheme is validated via a numerical experiment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.732-735
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• 2011

Cloud computing is a new paradigm that adopts a pay-as-you-go business model. So, clients can ues the various resources, although they have not own the resources. Already, three big players of IT industry, namely Amazon, Google and Microsoft, develop the many applications for cloud computing. In this paper, we describe the data consistency requirements for cloud computing. Data characteristics of cloud computing is replicated, distributed and large-scaled. And consistency and availability of data cannot be satisfied simultaneously. In this paper, we categorized the applications of cloud computing, and describe requirements of consistency criteria for applications. With this result, we can make the base of consistency criteria that can be adapted for cloud computing, in the near future.

• Korean Journal of Remote Sensing
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• v.31 no.5
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• pp.371-384
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• 2015

Although GOCI has potential for land surface monitoring, there have been only a few cases for land applications. It might be due to the lack of reliable land products derived from GOCI data for end-users. To use for land applications, it is often essential to provide cloud-free composite over land surfaces. In this study, we proposed a cloud detection method that was very important to make cloud-free composite of GOCI reflectance and vegetation index. Since GOCI does not have SWIR and TIR spectral bands, which are very effective to separate clouds from other land cover types, we developed a multi-temporal approach to detect cloud. The proposed cloud detection method consists of three sequential steps of spectral tests. Firstly, band 1 reflectance threshold was applied to separate confident clear pixels. In second step, thick cloud was detected by the ratio (b1/b8) of band 1 and band 8 reflectance. In third step, average of b1/b8 ratio values during three consecutive days was used to detect thin cloud having mixed spectral characteristics of both cloud and land surfaces. The proposed method provides four classes of cloudiness (thick cloud, thin cloud, probably clear, confident clear). The cloud detection method was validated by the MODIS cloud mask products obtained during the same time as the GOCI data acquisition. The percentages of cloudy and cloud-free pixels between GOCI and MODIS are about the same with less than 10% RMSE. The spatial distributions of clouds detected from the GOCI images were also similar to the MODIS cloud mask products.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.204-226
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• 2018

Big data processing applications have been migrated into cloud gradually, due to the advantages of cloud computing. Hadoop Distributed File System (HDFS) is one of the fundamental support systems for big data processing on MapReduce-like frameworks, such as Hadoop and Spark. Since HDFS is not aware of the co-location of virtual machines in the cloud, the default scheme of block allocation in HDFS does not fit well in the cloud environments behaving in two aspects: data reliability loss and performance degradation. In this paper, we present a novel location-aware data block allocation strategy (LDBAS). LDBAS jointly optimizes data reliability and performance for upper-layer applications by allocating data blocks according to the locations and different processing capacities of virtual nodes in the cloud. We apply LDBAS to two stages of data allocation of HDFS in the cloud (the initial data allocation and data recovery), and design the corresponding algorithms. Finally, we implement LDBAS into an actual Hadoop cluster and evaluate the performance with the benchmark suite BigDataBench. The experimental results show that LDBAS can guarantee the designed data reliability while reducing the job execution time of the I/O-intensive applications in Hadoop by 8.9% on average and up to 11.2% compared with the original Hadoop in the cloud.

• International Journal of Advanced Culture Technology
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• v.9 no.3
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• pp.315-320
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• 2021

Currently, cloud computing is being used as a technology that greatly changes the IT field. For many businesses, many cloud services are available in the form of custom, reliable, and cost-effective web applications. Most cloud service providers provide functions such as IoT, machine learning, AI services, blockchain, AR & VR, mobile services, and containers in addition to basic cloud services that support the scalability of processors, memory, and storage. In this paper, we will look at the most used cloud service providers and compare the services provided by the cloud service providers.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.9
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• pp.4280-4300
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• 2017

The fact that cloud computing services have been proposed in recent years, organizations and individuals face with various challenges and problems such as how to migrate applications and software platforms into cloud or how to ensure security of migrated applications. This study reviews the current challenges and open issues in cloud computing, with the focus on autonomic resource management especially in federated clouds. In addition, this study provides recommendations and research roadmaps for scientific activities, as well as potential improvements in federated cloud computing. This survey study covers results achieved through 190 literatures including books, journal and conference papers, industrial reports, forums, and project reports. A solution is proposed for autonomic resource management in the federated clouds, using machine learning and statistical analysis in order to provide better and efficient resource management.

• Journal of Information Technology Applications and Management
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• v.27 no.6
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• pp.89-99
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• 2020

Cloud computing is rapidly increasing for achieving comfortable computing. Cloud computing has essentially security vulnerability of software and hardware. For achieving secure cloud computing, the vulnerabilities of cloud computing could be analyzed in a various and systematic approach from perspective of the service designer, service operator, the designer of cloud security and certifiers of cloud systems. The paper investigates the vulnerabilities and security controls from the perspective of administration, and systems. For achieving the secure operation of cloud computing, this paper analyzes technological security vulnerability, operational weakness and the security issues in an enterprise. Based on analysis, the paper suggests secure establishments for cloud computing.