• Journal of Korea Society of Digital Industry and Information Management
• /
• v.16 no.2
• /
• pp.35-43
• /
• 2020

Cloud computing integrates computing resources such as servers, storage, and networks with virtualization technology to provide suitable services according to user needs. Due to the structural characteristics of sharing physical resources based on virtualization technology, threats to availability can occur, so it is essential to respond to availability threats in cloud computing. Existing over-provisioning method is not suitable because it can generate idle resources and cause under-provisioning to degrade or disconnect service. System resources must be allocated in real-time according to the system load to guarantee the cloud system's availability. Through appropriate management measures, it is necessary to reduce the system load and increase the performance of the system. This paper analyzes the work response time according to the allocation or migration of virtual machines and discusses an efficient resource management method considering the system load.

• Journal of the Korean Data and Information Science Society
• /
• v.22 no.5
• /
• pp.989-998
• /
• 2011

Cloud computing provides computation, software, data access, and storage services that do not require end-user knowledge of the physical location and configuration of the system that delivers the services. Cloud computing providers have setup several data centers at different geographical locations over the Internet in order to optimally serve needs of their customers around the world. One of the fundamental challenges in geographically distributed clouds is to provide efficient algorithms for supporting inter-cloud data management and dissemination. In this paper, we propose a group quorum system (GQS)-based dissemination for improving the interoperability of inter-cloud in time-critical event dissemination service, such as computing policy updating, message sharing, event notification and so forth. The proposed GQS-based method organizes these distributed clouds into a group quorum ring overlay to support a constant event dissemination latency. Our numerical results show that the GQS-based method improves the efficiency as compared with Chord-based and Plume methods.

• Electronics and Telecommunications Trends
• /
• v.35 no.4
• /
• pp.135-148
• /
• 2020

Virtualisation in cloud computing is vital for maintaining maximum resource utilization and easy access to operation and storage management of components. Platform virtualisation technology has the potential to be easily implemented with the support of scalability and security, which are the most important components for cloud-based services. Virtual resources must be allocated to a centralized pool called the cloud, and it is considered as cloud computing only when the virtual resources are orchestrated through management and automation software. Therefore, research and development on the latest technology for such a virtualisation platform provides both academia and industry the scope to deploy the fastest and most reliable technology in limited hardware resource. In this research, we reviewed and compared the popular current technologies for network and service management and automation technology.

• Journal of Broadcast Engineering
• /
• v.19 no.1
• /
• pp.24-30
• /
• 2014

This study investigates computing offloading effect of cloud in real-time video personal broadcast service, whose server is mobile device. Mobile device does not have enough computing resource for encoding video. The computing burden is offloaded to cloud, which has abundant resources in terms of computing, power, and storage compared to mobile device. By reducing computing burden, computation energy can be saved while transmission data amount increases because of decreasing compression efficiency. This study shows that the optimal operation point can be found adaptively to time-varying LTE communication condition result of tradeoff analysis between offloaded computation burden and increase in amount of transmitted data.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.11
• /
• pp.4028-4049
• /
• 2014

Attribute-based encryption (ABE) is a promising cryptographic primitive for implementing fine-grained data sharing in cloud computing. However, before ABE can be widely deployed in practical cloud storage systems, a challenging issue with regard to attributes and user revocation has to be addressed. To our knowledge, most of the existing ABE schemes fail to support flexible and direct revocation owing to the burdensome update of attribute secret keys and all the ciphertexts. Aiming at tackling the challenge above, we formalize the notion of ciphertext-policy ABE supporting flexible and direct revocation (FDR-CP-ABE), and present a concrete construction. The proposed scheme supports direct attribute and user revocation. To achieve this goal, we introduce an auxiliary function to determine the ciphertexts involved in revocation events, and then only update these involved ciphertexts by adopting the technique of broadcast encryption. Furthermore, our construction is proven secure in the standard model. Theoretical analysis and experimental results indicate that FDR-CP-ABE outperforms the previous revocation-related methods.

• ETRI Journal
• /
• v.42 no.5
• /
• pp.658-668
• /
• 2020

In edge computing, most procedures, including data collection, data processing, and service provision, are handled at edge nodes and not in the central cloud. This decreases the processing burden on the central cloud, enabling fast responses to end-device service requests in addition to reducing bandwidth consumption. However, edge nodes have restricted computing, storage, and energy resources to support computation-intensive tasks such as processing deep neural network (DNN) inference. In this study, we analyze the effect of models with single and multiple local exits on DNN inference in an edge-computing environment. Our test results show that a single-exit model performs better with respect to the number of local exited samples, inference accuracy, and inference latency than a multi-exit model at all exit points. These results signify that higher accuracy can be achieved with less computation when a single-exit model is adopted. In edge computing infrastructure, it is therefore more efficient to adopt a DNN model with only one or a few exit points to provide a fast and reliable inference service.

• Convergence Security Journal
• /
• v.14 no.7
• /
• pp.85-90
• /
• 2014

Cloud computing originated simply to request and execute the desired operation from the network of clouds. It means that an IT resource that provides a service using the Internet technology. It is getting the most attention in today's IT trends. In cloud computing networks, devices and data centers which are composed of the server, storage and application are connected over network. That is, data of computers in different physical locations are integrated using the virtualization technology to provide a service. Therefore cloud computing system is a key information resource, standardized methods and assessment system are required. In this paper, we aims to derive the parameters and information for research of technical standards stability evaluation method associated with various cloud computing equipment.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.7
• /
• pp.2815-2839
• /
• 2020

In a cloud computing paradigm, allocation of various virtualized ICT resources is a complex problem due to the presence of heterogeneous application (MapReduce, content delivery and networks web applications) workloads having contentious allocation requirements in terms of ICT resource capacities (resource utilization, execution time, response time, etc.). This task of resource allocation becomes more challenging due to finite available resources and increasing consumer demands. Therefore, many unique models and techniques have been proposed to allocate resources efficiently. However, there is no published research available in this domain that clearly address this research problem and provides research taxonomy for classification of resource allocation techniques including strategic, target resources, optimization, scheduling and power. Hence, the main aim of this paper is to identify open challenges faced by the cloud service provider related to allocation of resource such as servers, storage and networks in cloud computing. More than 70 articles, between year 2007 and 2020, related to resource allocation in cloud computing have been shortlisted through a structured mechanism and are reviewed under clearly defined objectives. Lastly, the evolution of research in resource allocation techniques has also been discussed along with salient future directions in this area.

• Journal of Satellite, Information and Communications
• /
• v.11 no.2
• /
• pp.1-7
• /
• 2016

In this paper, we propose contents authoring, management, and distribution technologies where the contents registered in secure storage through a content acquisition and authoring tool can be used as a common experience in smartphones, smart pads, and PCs. Currently, many people are producing and consuming various types of contents in bulk, and it is expected that real-time contents and old contents coexist as IoT(Internet of Things) technology is commonly deployed in the future. Therefore, we need to develop a differentiated service that can compete with global services in contents authoring and collaboration systems to create new markets. Accordingly, we implemented an authoring service platform to occupy cloud markets with high quality contents produced through collaboration.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.2
• /
• pp.558-579
• /
• 2021

The cloud storage provides flexible data storage services for data owners to remotely outsource their data, and reduces data storage operations and management costs for data owners. These outsourced data bring data security concerns to the data owner due to malicious deletion or corruption by the cloud service provider. Data integrity verification is an important way to check outsourced data integrity. However, the existing data verification schemes only consider the case that a verifier launches multiple data verification challenges, and neglect the verification overhead of multiple data verification challenges launched by multiple verifiers at a similar time. In this case, the duplicate data in multiple challenges are verified repeatedly so that verification resources are consumed in vain. We propose a duplicate data verification algorithm based on multiple verifiers and multiple challenges to reduce the verification overhead. The algorithm dynamically schedules the multiple verifiers' challenges based on verification time and the frequent itemsets of duplicate verification data in challenge sets by applying FP-Growth algorithm, and computes the batch proofs of frequent itemsets. Then the challenges are split into two parts, i.e., duplicate data and unique data according to the results of data extraction. Finally, the proofs of duplicate data and unique data are computed and combined to generate a complete proof of every original challenge. Theoretical analysis and experiment evaluation show that the algorithm reduces the verification cost and ensures the correctness of the data integrity verification by flexible batch data verification.