• The Transactions of the Korea Information Processing Society
• /
• v.13 no.7
• /
• pp.291-298
• /
• 2024

Despite its wide application, cloud computing raises privacy leakage concerns because users should send their private data to the cloud. Homomorphic encryption (HE) can resolve the concerns by allowing cloud servers to compute on encrypted data without decryption. However, due to the huge computation overhead of HE, simply executing an entire cloud program with HE causes significant computation. Manually partitioning the program and applying HE only to the partitioned program for the cloud can reduce the computation overhead. However, the manual code partitioning and HE-transformation are time-consuming and error-prone. This work proposes a new homomorphic encryption enabled annotation-guided code partitioning compiler, called Heapa, for privacy preserving cloud computing. Heapa allows programmers to annotate a program about the code region for cloud computing. Then, Heapa analyzes the annotated program, makes a partition plan with a variable list that requires communication and encryption, and generates a homomorphic encryptionenabled partitioned programs. Moreover, Heapa provides not only two region-level partitioning annotations, but also two instruction-level annotations, thus enabling a fine-grained partitioning and achieving better performance. For six machine learning and deep learning applications, Heapa achieves a 3.61 times geomean performance speedup compared to the non-partitioned cloud computing scheme.

• International Journal of Computer Science & Network Security
• /
• v.21 no.6
• /
• pp.107-118
• /
• 2021

The deployment of 5G is in full swing, with a significant yearly growth in the data traffic expected to reach 26% by the year and data consumption to reach 122 EB per month by 2022 [10]. In parallel, the idea of smart cities has been implemented by various governments and private organizations. One of the main objectives of 5G deployment is to help develop and realize smart cities. 5G can support the enhanced data delivery requirements and the mass connection requirements of a smart city environment. However, for specific high-demanding applications like tactile Internet, transportation, and augmented reality, the cloud-based 5G infrastructure cannot deliver the required quality of services. We suggest using multi-access edge computing (MEC) technology for smart cities' environments to provide the necessary support. In cloud computing, the dependency on a central server for computation and storage adds extra cost in terms of higher latency. We present a few scenarios to demonstrate how the MEC, with its distributed architecture and closer proximity to the end nodes can significantly improve the quality of services by reducing the latency. This paper has surveyed the existing work in MEC for 5G and highlights various challenges and opportunities. Moreover, we propose a unique framework based on the use of MEC for 5G in a smart city environment. This framework works at multiple levels, where each level has its own defined functionalities. The proposed framework uses the MEC and introduces edge-sub levels to keep the computing infrastructure much closer to the end nodes.

• International Journal of Computer Science & Network Security
• /
• v.23 no.6
• /
• pp.17-26
• /
• 2023

Blockchain technology has emerged as one of the most crucial solutions in numerous industries, including healthcare. The combination of blockchain technology and cloud computing results in improving access to high-quality telemedicine and healthcare services. In addition to developments in healthcare, the operational strategy outlined in Vision 2030 is extremely essential to the improvement of the standard of healthcare in Saudi Arabia. The purpose of this survey is to give a thorough analysis of the current state of healthcare technologies that are based on blockchain and cloud computing. We highlight some of the unanswered research questions in this rapidly expanding area and provide some context for them. Furthermore, we demonstrate how blockchain technology can completely alter the medical field and keep health records private; how medical jobs can detect the most critical, dangerous errors with blockchain industries. As it contributes to develop concerns about data manipulation and allows for a new kind of secure data storage pattern to be implemented in healthcare especially in telemedicine fields is discussed diagrammatically.

• Journal of Digital Convergence
• /
• v.11 no.3
• /
• pp.115-126
• /
• 2013

The purpose of this study was to confirm the extent of the reduction in the total cost of ownership of the open source software in comparison to the commercial software installed for information system, PC and cloud computing. Accordingly, the actual reduction rates in the total cost of ownership, when open source software is installed in the information system, PC and cloud computing, were computed and analyzed for 51 companies in the area of information system, 18 companies in the area of PC and 6 companies in the area of cloud computing, which included government institution, educational institution and private enterprises. The results of expert survey illustrated that the reduction rates are (1)63.3% on the average for the 4areas of information system, namely, DBMS, WAS, Web and OS, (2) 59.4% on the average for the 6 areas of PC, namely, OS, Documentation Program, Back-up and Restoration, Screen Capture, Vaccine and Others and (3) 61.2% on the average for the 6 areas of cloud computing, namely, Virtualization, OS, WEM/WAS, DBMS, DFS and Cloud Management.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2015.04a
• /
• pp.164-166
• /
• 2015

Recently, the implementations of private and public cloud service (IaaS: Infrastructure as a Service) have been growing rapidly. As a result, the need to provide High-Availability and Load-Balancing for the users has also increased. Openstack which is one of cloud computing solutions currently offers a feature to meet the need through an extension called Load Balancing as a Service (LBaaS). This paper will provide a detailed explanation about Openstack's LBaaS and its operation principle will be analyzed through the actual implementation.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
• /
• v.27 no.3
• /
• pp.127-143
• /
• 2022

Recently, many attempts to run numerical ocean models in cloud computing environments have been tried actively. A cloud computing environment can be an effective means to implement numerical ocean models requiring a large-scale resource or quickly preparing modeling environment for global or large-scale grids. Many commercial and private cloud computing systems provide technologies such as virtualization, high-performance CPUs and instances, ether-net based high-performance-networking, and remote direct memory access for High Performance Computing (HPC). These new features facilitate ocean modeling experimentation on commercial cloud computing systems. Many scientists and engineers expect cloud computing to become mainstream in the near future. Analysis of the performance and features of commercial cloud services for numerical modeling is essential in order to select appropriate systems as this can help to minimize execution time and the amount of resources utilized. The effect of cache memory is large in the processing structure of the ocean numerical model, which processes input/output of data in a multidimensional array structure, and the speed of the network is important due to the communication characteristics through which a large amount of data moves. In this study, the performance of the Regional Ocean Modeling System (ROMS), the High Performance Linpack (HPL) benchmarking software package, and STREAM, the memory benchmark were evaluated and compared on commercial cloud systems to provide information for the transition of other ocean models into cloud computing. Through analysis of actual performance data and configuration settings obtained from virtualization-based commercial clouds, we evaluated the efficiency of the computer resources for the various model grid sizes in the virtualization-based cloud systems. We found that cache hierarchy and capacity are crucial in the performance of ROMS using huge memory. The memory latency time is also important in the performance. Increasing the number of cores to reduce the running time for numerical modeling is more effective with large grid sizes than with small grid sizes. Our analysis results will be helpful as a reference for constructing the best computing system in the cloud to minimize time and cost for numerical ocean modeling.

• Journal of Platform Technology
• /
• v.8 no.4
• /
• pp.59-69
• /
• 2020

Recently, the seriousness of ultrafine dust and fine dust has emerged as a national disaster, but small and medium-sized cities in provincial areas lack fine dust monitoring stations compared to their area, making it difficult to manage fine dust. Although the computing resources for collecting and processing fine dust data are not large, it is necessary to utilize cloud and private and public data to share data. In this paper, we proposed a small edge computing system that can measure fine dust, ultrafine dust and temperature and humidity and process it to provide real-time control of fine dust and service to the public. Collecting fine dust data and using public and private data to service fine dust ratings is efficient to handle with edge computing using raspberry pie because the amount of data is not large and the processing load is not large. For the experiment, the experiment system was constructed using three sensors, raspberry pie and Thinkspeak, and the fine dust measurement was conducted in northern part of kyongbuk region. The results of the experiment confirmed the measured fine dust measurement results over time based on the GIS data of the private sector.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.37 no.3
• /
• pp.57-68
• /
• 2012

The recent proliferation of various smart devices like the smartphone, tablet PC, and smart TV enables consumers to download various applications from the network and to access private files stored in their desktop server at any time and at any place. The trend of ubiquitous access seems to have become stronger and more diversified toward a ubiquitous network computing environment with the aggressive deployment of commercial cloud services. Recently, many Korean network service providers launched commercial B2C public cloud services, which were widely adopted by smart device users. They include Daum cloud, N drive, ucloud, and uplus box, mostly provided by major Korean telecom companies and portals. This paper aims to explore consumers' adoption behaviors toward the B2C public cloud services that were recently deployed in the Korean market. In order to achieve the goal, we identified key influencing factors that affect the consumers' adoption behaviors, based on an extension of the technology acceptance model (TAM). Several hundred smart device users were surveyed to test the generic regression model with the extended set of TAM variables.

• Journal of Internet Computing and Services
• /
• v.13 no.5
• /
• pp.55-64
• /
• 2012

Nowadays, as Cloud computing becomes popular, a need for a DFS(distributed file system) is increased. But, in the current Cloud computing environments, there is no DFS framework that is sufficient to protect sensitive private information from attackers. Therefore, we designed and proposed a secure scheme for distributed file systems. The scheme provides confidentiality and availability for a distributed file system using a secret sharing method. In this paper, we measured the speed of encryption and decryption for our proposed method, and compared them with that of SEED algorithm which is the most popular algorithm in this field. This comparison showed the computational efficiency of our method. Moreover, the proposed secure read/write model is independent of Hadoop DFS structure so that our modified algorithm can be easily adapted for use in the HDFS. Finally, the proposed model is evaluated theoretically using performance measurement method for distributed secret sharing model.

• Journal of the Korea Society of Computer and Information
• /
• v.18 no.7
• /
• pp.11-21
• /
• 2013

Recently operating a large scale computing resource like a data center becomes easier because of the virtualization technology that virtualize servers and enable flexible resource provision. The most of public cloud services provides automatic scaling in the form of scale-in or scale-out and these scaling approaches works well to satisfy the service level agreement (SLA) of users. However, a novel scaling approach is required to operate private clouds that has smaller amount of computing resources than vast resources of public clouds. In this paper, we propose a hybrid server scaling architecture and related algorithms using both scale-in and scale-out to achieve higher resource utilization rate for private clouds. We uses dynamic resource allocation and live migration to run our proposed algorithm. Our propose system aims to provide a fine-grain resource scaling by steps. Thus private cloud systems are able to keep stable service and to reduce server management cost by optimizing server utilization. The experiment results show that our proposed approach performs better in resource utilization than the scale-out approach based on the number of users.