• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4044-4062
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• 2016

We investigate the optimization of energy consumption in Mobile Cloud environment in this paper. In order to optimize the energy consumed by the CPUs in mobile devices, we put forward using the asymptotic time complexity (ATC) method to distinguish the computational complexities of the applications when they are executed in mobile devices. We propose a multi-scale scheme to quantize the channel gain and provide an improved dynamic transmission scheduling algorithm when offloading the applications to the cloud center, which has been proved to be helpful for reducing the mobile devices energy consumption. We give the energy estimation methods in both mobile execution model and cloud execution model. The numerical results suggest that energy consumed by the mobile devices can be remarkably saved with our proposed multi-scale scheme. Moreover, the results can be used as a guideline for the mobile devices to choose whether executing the application locally or offloading it to the cloud center.

• Journal of Korea Multimedia Society
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• v.19 no.4
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• pp.765-773
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• 2016

As multimedia content technology developed, there are many cases that service contents are being provided in many different ways in the cloud-based media service system. A DRM is a technology that can enhance the copyright of the digital content by providing right information. It is available on a single platform and has a problem that the additional cost when the platform is changing. In this paper, we propose a media service system based on cloud computing. It can be used on multiple platforms at the same time by applying a number of DRM for digital contents, and allows use of a new authentication for another platform without any additional cost.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.3026-3049
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• 2016

Cloud computing promises high performance and cost-efficiency. However, most cloud infrastructures operate at a low utilization, which greatly adheres cost effectiveness. Previous works focus on seeking efficient virtual machine (VM) consolidation strategies to increase the utilization of virtual resources in production environment, but overlook the under-utilization of backup virtual resources. We propose a heuristic time sharing policy of backup VMs derived from the restless multi-armed bandit problem. The proposed policy achieves increasing backup virtual resources utilization and providing high availability. Both the results in simulation and prototype system experiments show that the traditional 1:1 backup provision can be extended to 1:M (M≫1) between the backup VMs and the service VMs, and the utilization of backup VMs can be enhanced significantly.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.5
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• pp.2346-2361
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• 2017

A major challenge in cloud infrastructure is the efficient allocation of virtual network elements on top of substrate network elements. Path algebra is a mathematical framework which allows the validation and convergence analysis of the mono-constraint or multi-constraint routing problems independently of the network topology or size. The present study proposes a new heuristic approach based on mathematical framework "paths algebra" to map virtual nodes and links to substrate nodes and paths in cloud. In this approach, we define a measure criterion to rank the substrate nodes, and map the virtual nodes to substrate nodes according to their ranks by using a greedy algorithm. In addition, considering multi-constraint routing in virtual link mapping stage, the used paths algebra framework allows a more flexible and extendable embedding. Obtained results of simulations show appropriate improvement in acceptance ratio of virtual networks and cost incurred by the infrastructure networks.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.6
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• pp.1277-1286
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• 2013

Cloud computing's unique attributes such as elasticity, rapid provisioning and releasing, resource pooling, multi-tenancy, broad-network accessibility, and ubiquity bring many benefits to cloud adopters(company and organization), but also entails specific security risks associated with the type of adopted cloud and deployment mode. To minimize those types of risk, this paper proposed cloud computing security framework refered to strategic alliance model. The cloud computing security framework has main triangles that are cloud threat, security controls, cloud stakeholders and compose of three sides that are purposefulness, accountability, transparent responsibility. Main triangles define purpose of risk minimization, appointment of stakeholders, security activity for them and three sides of framework are principles of security control in the cloud computing, provide direction of deduction for seven service packages.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.58-73
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• 2021

Cloud Service Providers (CSPs) enable their users to access Cloud computing and storage services from anywhere in quick and flexible manners through the Internet. With the basis of 'pay-as-you-go' model, it makes the interactions between CSPs and the users play a vital role in shaping the Cloud computing market. A pool of virtualized and dynamically scalable Cloud services that delivered on demand to the users is associated with guaranteed performance and cost-provisioning. It needed a costing scheme for determining suitable charges in order to secure lease pricing of the Cloud services. However, it is hard to meet the satisfied prices for both CSPs and users due to their conflicting needs. Furthermore, there is lack of Service Level Agreements (SLAs) that allowing the users to take part into price negotiating process. The users may lose their interest to use Cloud services while reducing CSPs profit. Therefore, this paper proposes a generic costing scheme for Cloud services using General Equilibrium Theory (GET). GET helps to formulate the price function for various services' factors to match with various demands from the users. It is initially determined by identifying the market circumstances that a general equilibrium will be hold and reached. Specifically, there are two procedures of agreement made in response to (i) established equilibrium supply and demand, and (ii) service price formed and constructed in a price range. The SLAs in our costing scheme is integrated to satisfy both CSPs and users' needs while minimizing their conflicts. The price ranging strategy is deliberated to provide prices' options to the users with respect their budget limit. Meanwhile, the CSPs can adaptively charge based on users' preferences without losing their profit. The costing scheme is testable and analyzed in multi-tenant computing environments. The results from our simulation experiments demonstrate that the proposed costing scheme provides better users' satisfaction while fostering fairness pricing in the Cloud market.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.4776-4798
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• 2015

The location selection of virtual machines in distributed cloud is difficult because of the physical resource distribution, allocation of multi-dimensional resources, and resource unit cost. In this study, we propose a multi-object virtual machine location selection algorithm (MOVMLSA) based on group information, doubly linked list structure and genetic algorithm. On the basis of the collaboration of multi-dimensional resources, a fitness function is designed using fuzzy logic control parameters, which can be used to optimize search space solutions. In the location selection process, an orderly information code based on group and resource information can be generated by adopting the memory mechanism of biological immune systems. This approach, along with the dominant elite strategy, enables the updating of the population. The tournament selection method is used to optimize the operator mechanisms of the single-point crossover and X-point mutation during the population selection. Such a method can be used to obtain an optimal solution for the rapid location selection of virtual machines. Experimental results show that the proposed algorithm is effective in reducing the number of used physical machines and in improving the resource utilization of physical machines. The algorithm improves the utilization degree of multi-dimensional resource synergy and reduces the comprehensive unit cost of resources.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.2914-2935
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• 2016

With the increasing popularization of cloud computing, how to reduce physical energy consumption and increase resource utilization while maintaining system performance has become a research hotspot of virtual machine deployment in cloud platform. Although some related researches have been reported to solve this problem, most of them used the traditional heuristic algorithm based on greedy algorithm and only considered effect of single-dimensional resource (CPU or Memory) on energy consumption. With considerations to multi-dimensional resource utilization, this paper analyzed impact of multi-dimensional resources on energy consumption of cloud computation. A multi-dimensional resource constraint that could maintain normal system operation was proposed. Later, a novel virtual machine deployment method (NVMDM) based on improved particle swarm optimization (IPSO) and Euclidean distance was put forward. It deals with problems like how to generate the initial particle swarm through the improved first-fit algorithm based on resource constraint (IFFABRC), how to define measure standard of credibility of individual and global optimal solutions of particles by combining with Bayesian transform, and how to define fitness function of particle swarm according to the multi-dimensional resource constraint relationship. The proposed NVMDM was proved superior to existing heuristic algorithm in developing performances of physical machines. It could improve utilization of CPU, memory, disk and bandwidth effectively and control task execution time of users within the range of resource constraint.

• Journal of Korea Multimedia Society
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• v.17 no.10
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• pp.1182-1188
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• 2014

Recently, the research on database outsourcing has been actively done with the popularity of cloud computing. However, because users' data may contain sensitive personal information, such as health, financial and location information, the data encryption methods have attracted much interest. Existing data encryption schemes process a query without decrypting the encrypted databases in order to support user privacy protection. On the other hand, to efficiently handle the large amount of data in cloud computing, it is necessary to study the distributed index structure. However, existing index structure and query processing algorithms have a limitation that they only consider single-column query processing. In this paper, we propose a grid-based multi column indexing scheme and an encrypted query processing algorithm. In order to support multi-column query processing, the multi-dimensional index keys are generated by using a space decomposition method, i.e. grid index. To support encrypted query processing over encrypted data, we adopt the Hilbert curve when generating a index key. Finally, we prove that the proposed scheme is more efficient than existing scheme for processing the exact and range query.

• KIISE Transactions on Computing Practices
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• v.22 no.11
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• pp.547-558
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• 2016

Construction of multi-site Cloud Infrastructure with OpenStack, the most popular cloud open source project with various ICT infrastructure technologies, has operational inefficiency due to installation complexity and geographical limitation. To address this inefficiency, we gradually developed automated installation/configuration tools to automate installation/configuration of Linux and OpenStack by complying with DevOps methodology over a multi-site OpenStack testbed called OF@KOREN SmartX Playground. However, the pre-developed installation tools can be used only for limited cases. Therefore, we designed and developed a prototype of SmartX Provisioning Framework which could conducts Playground-wide provisioning flexibly by following three steps of resource management in Software-defined Infrastructure. We verified the efficiency of the provisioning functionality of the framework by demonstrating an example of automated multi-site cloud construction.