• Atmosphere
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• 제24권1호
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• pp.111-122
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• 2014

In the Korea Meteorological Administration earth system model (HadGEM2-AO), cloud drop number concentration is determined from aerosol number concentration according to the observed relationship between aerosol and cloud drop number concentrations. However, the observational dataset used for establishing the relationship was obtained from limited regions of the earth and therefore may not be representative of the entire earth. Here we reestablished the relationship between aerosol and cloud drop number concentrations based on a composite of observational dataset obtained from many different regions around the world that includes the original dataset. The new relationship tends to provide lower cloud drop number concentration for aerosol number concentration < 600 $cm^{-3}$ and the opposite for > 600 $cm^{-3}$. This new empirical relationship was applied to the KMA earth system model and the historical run (1861~2005) is made again. Here only the 30 year (1861~1890) averages from the runs with the new and the original relationships between aerosol and cloud drop number concentrations (newHIST and HIST, respectively) were compared. For this early period aerosol number concentrations were generally lower than 600 $cm^{-3}$ and therefore cloud drop number concentrations were generally lower but cloud drop effective radii were larger for newHIST than for HIST. The results from the complete historical run with the new relationship are expected to show more significant differences from the original historical run.

• International Journal of Computer Science & Network Security
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• 제21권12호
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• pp.235-247
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• 2021

Today, the cloud computing has become a major demand of many organizations. The major reason behind this expansion is due to its cloud's sharing infrastructure with higher computing efficiency, lower cost and higher fle3xibility. But, still the security is being a hurdle that blocks the success of the cloud computing platform. Therefore, a novel Multi-tenant Decentralized Information Flow Control (MT-DIFC) model is introduced in this research work. The proposed system will encapsulate four types of entities: (1) The central authority (CA), (2) The encryption proxy (EP), (3) Cloud server CS and (4) Multi-tenant Cloud virtual machines. Our contribution resides within the encryption proxy (EP). Initially, the trust level of all the users within each of the cloud is computed using the proposed two-stage trust computational model, wherein the user is categorized bas primary and secondary users. The primary and secondary users vary based on the application and data owner's preference. Based on the computed trust level, the access privilege is provided to the cloud users. In EP, the cipher text information flow security strategy is implemented using the blowfish encryption model. For the data encryption as well as decryption, the key generation is the crucial as well as the challenging part. In this research work, a new optimal key generation is carried out within the blowfish encryption Algorithm. In the blowfish encryption Algorithm, both the data encryption as well as decryption is accomplishment using the newly proposed optimal key. The proposed optimal key has been selected using a new Self Improved Cat and Mouse Based Optimizer (SI-CMBO), which has been an advanced version of the standard Cat and Mouse Based Optimizer. The proposed model is validated in terms of encryption time, decryption time, KPA attacks as well.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권4호
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• pp.1501-1518
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• 2016

This paper presents an effective management of VM (Virtual Machine) for heterogeneous cloud using Common Deployment Model (CDM) brokering mechanism. The effective utilization of VM is achieved by means of task scheduling with VM placement technique. The placements of VM for the physical machine are analyzed with respect to execution time of the task. The idle time of the VMis utilized productively in order to improve the performance. The VMs are also scheduled to maintain the state of the current VM after the task completion. CDM based algorithm maintains two directories namely Active Directory (AD) and Passive Directory (PD). These directories maintain VM with proper configuration mapping of the physical machines to perform two operations namely VM migration and VM roll back. VM migration operation is performed from AD to PD whereas VM roll back operation is performed from PD to AD. The main objectives of the proposed algorithm is to manage the VM's idle time effectively and to maximize the utilization of resources at the data center. The VM placement and VM scheduling algorithms are analyzed in various dimensions of the cloud and the results are compared with iCanCloud model.

• Water for future
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• 제28권6호
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• pp.229-236
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• 1995

The physically based heavy rainfall model developed by Ceon(1994) for storm events is modified in this study. The main parts of this paper are composed of modeling saturation vapor pressure, cloud thickness, cloud top pressure. In a different way from the previous model, cloud top temperature and albedo measured by satellite are used as input data to the model. In this paper, the defect of saturation vapor pressure equation in the previous model was improved. Furthermore, the parameters for temperature and pressure on cloud top are eliminated as well as the time of calculation in the model is decreased. Also, the results show that there are very small gab between the hourly calculated.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권10호
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• pp.1712-1732
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• 2011

Cloud provides dynamically scalable virtualized computing resources as a service over the Internet. To achieve higher resource utilization over virtualization technology, an optimized strategy that deploys virtual machines on physical machines is needed. That is, the total number of active physical host nodes should be dynamically changed to correspond to their resource usage rate, thereby maintaining optimum utilization of physical machines. In this paper, we propose a pattern-based prediction model for resource provisioning which facilitates best possible resource preparation by analyzing the resource utilization and deriving resource usage patterns. The focus of our work is on predicting future resource requests by optimized dynamic resource management strategy that is applied to a virtualized data center in a Cloud computing environment. To this end, we build a prediction model that is based on user request patterns and make a prediction of system behavior for the near future. As a result, this model can save time for predicting the needed resource amount and reduce the possibility of resource overuse. In addition, we studied the performance of our proposed model comparing with conventional resource provisioning models under various Cloud execution conditions. The experimental results showed that our pattern-based prediction model gives significant benefits over conventional models.

• KIISE Transactions on Computing Practices
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• 제20권12호
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• pp.664-669
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• 2014

As the prevalence of cloud computing increases, various cloud service types have emerged, such as IaaS, PaaS, and SaaS. The growth and diversification of these cloud services has also resulted in the development of technology for cloud service brokers (CSBs), which serve as intermediate cloud services that can assist cloud tenants (users) in deploying services that fit their requirements. In order to broker cloud services, CSBs require the specification of structural models in order to facilitate the analysis and search for cloud services. In this study, we propose a variability-based service analysis model (SAM) that can be used to describe various cloud services. This model is based on the concept of variability in the software product line and represents the commonality and variability of cloud services by binding variants to each variation point that exists in the specification, quality, and pricing of the services. We also propose a virtual cloud bank architecture as a CSB that serves as an intermediate to provides tenants with appropriate cloud services based on the SAM.

• Information Systems Review
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• 제17권1호
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• pp.1-18
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• 2015

Recently, the number of available cloud services are increasing dramatically because many IT companies have entered into cloud service market. Due to the reason, cloud service brokers are emerging as agents to solve cloud service selection problems and to support cloud service initialization and maintenance of unskilled cloud service users. In this study, NCloud24 case in South Korea and Right Scale case in the USA are analyzed as representative examples of the collaboration between original cloud service providers and cloud service brokers. The business models of two companies are analyzed using Business Model Canvas. The emergence of cloud service brokers are interpreted as unbundling process of IaaS (Infrastructure-as-a-service) cloud service companies. Based on the comparison with the two companies, we prospect future directions of cloud service brokerage.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권7호
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• pp.3375-3400
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• 2018

With the advent of database-as-a-service (DAAS) and cloud computing, more and more data owners are motivated to outsource their data to cloud database in consideration of convenience and cost. However, it has become a challenging work to provide security to database as service model in cloud computing, because adversaries may try to gain access to sensitive data, and curious or malicious administrators may capture and leak data. In order to realize privacy preservation, sensitive data should be encrypted before outsourcing. In this paper, we present a secure and practical system over encrypted cloud data, called QSDB (queryable and secure database), which simultaneously supports SQL query operations. The proposed system can store and process the floating point numbers without compromising the security of data. To balance tradeoff between data privacy protection and query processing efficiency, QSDB utilizes three different encryption models to encrypt data. Our strategy is to process as much queries as possible at the cloud server. Encryption of queries and decryption of encrypted queries results are performed at client. Experiments on the real-world data sets were conducted to demonstrate the efficiency and practicality of the proposed system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권11호
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• pp.5269-5286
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• 2018

Task scheduling is one of the key issues in improving system performance and optimizing resource management in cloud computing environment. In order to provide appropriate services for heterogeneous users, we propose a novel task scheduling strategy with service differentiation, in which the delay sensitive tasks are assigned to the rapid cloud with high-speed processing, whereas the fault sensitive tasks are assigned to the reliable cloud with service restoration. Considering that a user can receive service from either local SaaS (Software as a Service) servers or public IaaS (Infrastructure as a Service) cloud, we establish a hybrid queueing network based system model. With the assumption of Poisson arriving process, we analyze the system model in steady state. Moreover, we derive the performance measures in terms of average response time of the delay sensitive tasks and utilization of VMs (Virtual Machines) in reliable cloud. We provide experimental results to validate the proposed strategy and the system model. Furthermore, we investigate the Nash equilibrium behavior and the social optimization behavior of the delay sensitive tasks. Finally, we carry out an improved intelligent searching algorithm to obtain the optimal arrival rate of total tasks and present a pricing policy for the delay sensitive tasks.

• Transactions of the Korean Society of Mechanical Engineers A
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• 제30권8호
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• pp.906-915
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• 2006

This study concerns an advanced 3D surface reconstruction method that the vertices of surface model can be completely matched to the unstructured point cloud measured from arbitrary complex shapes. The concept of bounding voxel model is introduced to generate the mesh model well-representing the geometrical and topological characteristics of point cloud. In the reconstruction processes, the application of various methodologies such as shrink-wrapping, mesh simplification, local subdivision surface fitting, insertion of is isolated points, mesh optimization and so on, are required. Especially, the effectiveness, rapidity and reliability of the proposed surface reconstruction method are demonstrated by the simulation results for the geometrically and topologically complex shapes like dragon and human mouth.