• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1098-1100
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• 2002

Inter-RNC(radio network controller) and inter-BSC(base station center) hard handovers involve rerouting. Thus additional delay time for the new bearer setup and reroute determination should be considered. For theses kinds of handovers we propose a new scheme and coined it as ICHP(Inter-Cluster Handover Prediction). When a call approaches a boundary cell of a cluster, ICHP prepares for the handover by performing resource reservations and reroute computation in advance. Performance analysis shows that ICHP provides faster handover and that it lowers the blocking probability.

• International journal of advanced smart convergence
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• v.1 no.2
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• pp.12-15
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• 2012

Energy costs for operating and cooling computing resources in Cloud infrastructure have increased significantly up to the point where they would surpass the hardware purchasing costs. Thus, reducing the energy consumption can save a significant amount of management cost. One of major approach is removing hardware over-provisioning. In this paper, we propose a technique that facilitates power saving through reducing resource over provisioning based on virtualization technology. To this end, we use dynamic workload shaping to reschedule and redistribute job requests considering overall power consumption. In this paper, we present our approach to shape workloads dynamically and distribute them on virtual machines and physical machines through virtualization technology. We generated synthetic workload data and evaluated it in simulating and real implementation. Our simulated results demonstrate our approach outperforms to when not using no workload shaping methodology.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.3
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• pp.99-105
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• 2021

The cloud computing evolution has brought us increasing necessity to manage virtual resources. For this reason, Kubernetes has developed to realize autonomous resource management in a large scale. It provides cloud computing infrastructure to handle cluster creations and deletions in a secure virtual computing environment. In the paper, we provide a monitoring scheme in which users can observe securely encrypted protocols while each Kubernetes component exchanges their packets. Eventually, users can utilize the proposed scheme for debugging as well as monitoring.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04a
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• pp.4-6
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• 2003

시스템의 구조는 확장 또는 부하 균형을 위해 재구성 및 재구조화가 필요하다. 이러한 상황에서, 다수의 새로운 시스템이 기존의 시스템에 추가되며 이전의 시스템이 담당하고 있던 역할의 일부분이 새로 추가된 시스템으로 분산된다. 이러한 자원 관리는 몇 가지 문제를 야기시키는데, 가장 큰 문제점은 일부 시스템 또는 전체 시스템의 재구조화를 위해 일정기간 동안 서비스 제공이 중단된다는 점이다. 이 논문에서는 동적인 자원관리가 요구되는 변화하는 환경에서 자동적으로 새로운 시스템을 추가하고 적응적으로 시스템의 부하를 재조정할 수 있는 이동 컴퓨팅 모델을 제안한다.

• The KIPS Transactions:PartC
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• v.11C no.1
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• pp.47-54
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• 2004

The growth of computer resource and network speed has increased requests for the use of remotely located computer systems by connecting through computer networks. This phenomenon has hoisted research activities for application service provision that uses server-based remote computing paradigm. The server-based remote computing paradigm has been developed as the ASP (Application Service Provision) model, which provides remote users through application sharing protocol to application programs. Security requirement such as confidentiality, availability, integrity should be satisfied to provide ASP service using centralized computing system. Existing Telnet or FTP service for a remote computing systems have satisfied security requirement by a simple access control to files and/or data. But windows-based centralized computing system is vulnerable to confidentiality, availability, integrity where many users use the same application program installed in the same computer. In other words, the computing system needs detailed security level for each user different from others, such that only authorized user or group of users can run some specific functional commands for the program. In this paper, we propose windows based centralized computing system that sets security policies for each user for the use of instructions of the application programs, and performs access control to the instructions based on the security policies. The system monitors all user messages which are executed through graphical user interface by the users connecting to the system. Ail Instructions, i.e. messages, for the application program are now passed to authorization process that decides if an Instruction is delivered to the application program based on the pre-defined security polices. This system can be used as security clearance for each user for the shared computing resource as well as shared application programs.

• The Journal of the Korea Contents Association
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• v.11 no.3
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• pp.26-35
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• 2011

In these days, internet environment are very quickly development as well on-line service have been using a online for the mission critical business around the world. As the amount of information to be processed by computers has recently been increased there has been cluster computing systems developed by connecting workstations server using high speed networks for high availability. but cluster computing technology are limited for a lot of IT resources. So, grid computing is an expanded technology of distributed computing technology to use low-cost and high-performance computing power in various fields. Although the purpose of Grid computing focuses on large-scale resource sharing, innovative applications, and in some case, high-performance orientation, it has been used as conventional distributed computing environment like clustered computer until now because grid middleware does not have common sharable information system. In order to use grid computing environment efficiently which consists of various grid middleware, it is necessary to have application-independent information system which can share information description and services, and expand them easily. This paper proposed new database architecture and load balancing for high availability through Grid technology.

• Journal of the military operations research society of Korea
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• v.6 no.2
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• pp.47-67
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• 1980

Interactions of major activities participating in fleet operations are investigated in the framework of a closed queueing network system with finite aircrafts assigned to it. An implementable algorithm is developed, which is useful for computing the distributions needed to evaluate the effects of the interactions on the fleet operations. The availability management program is focused on seeking an optimal resource allocation to multiple repair-shops to maximize the fleet availability subject to the budget constraint.

• Journal of Information Processing Systems
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• v.17 no.3
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• pp.489-504
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• 2021

By distributing computing tasks among devices at the edge of networks, edge computing uses virtualization, distributed computing and parallel computing technologies to enable users dynamically obtain computing power, storage space and other services as needed. Applying edge computing architectures to Internet of Vehicles can effectively alleviate the contradiction among the large amount of computing, low delayed vehicle applications, and the limited and uneven resource distribution of vehicles. In this paper, a predictive offloading strategy based on the MEC load state is proposed, which not only considers reducing the delay of calculation results by the RSU multi-hop backhaul, but also reduces the queuing time of tasks at MEC servers. Firstly, the delay factor and the energy consumption factor are introduced according to the characteristics of tasks, and the cost of local execution and offloading to MEC servers for execution are defined. Then, from the perspective of vehicles, the delay preference factor and the energy consumption preference factor are introduced to define the cost of executing a computing task for another computing task. Furthermore, a mathematical optimization model for minimizing the power overhead is constructed with the constraints of time delay and power consumption. Additionally, the simulated annealing algorithm is utilized to solve the optimization model. The simulation results show that this strategy can effectively reduce the system power consumption by shortening the task execution delay. Finally, we can choose whether to offload computing tasks to MEC server for execution according to the size of two costs. This strategy not only meets the requirements of time delay and energy consumption, but also ensures the lowest cost.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.3
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• pp.794-815
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• 2023

The rapid development of mobile communication not only has made the industry gradually diversified, but also has enhanced the service quality requirements of users. In this regard, it is imperative to consider jointly network slicing and mobile edge computing. The former mainly ensures the requirements of varied vertical services preferably, and the latter solves the conflict between the user's own energy and harsh latency. At present, the integration of the two faces many challenges and need to carry out at different levels. The main target of the paper is to minimize the energy consumption of the system, and introduce a multi-slice joint task offloading and resource allocation scheme for massive multiple input multiple output enabled heterogeneous networks. The problem is formulated by collaborative optimizing offloading ratios, user association, transmission power and resource slicing, while being limited by the dissimilar latency and rate of multi-slice. To solve it, assign the optimal problem to two sub-problems of offloading decision and resource allocation, then solve them separately by exploiting the alternative optimization technique and Karush-Kuhn-Tucker conditions. Finally, a novel slices task offloading and resource allocation algorithm is proposed to get the offloading and resource allocation strategies. Numerous simulation results manifest that the proposed scheme has certain feasibility and effectiveness, and its performance is better than the other baseline scheme.