• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권11호
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• pp.3584-3602
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• 2022

NFV realizes flexible and rapid software deployment and management of network functions in the cloud network, and provides network services in the form of chained virtual network functions (VNFs). However, using VNFs to provide quality guaranteed services is still a challenge because of the inherent difficulty in intelligently scaling VNFs to handle traffic fluctuations. Most existing works scale VNFs with fixed-capacity instances, that is they take instances of the same size and determine a suitable deployment location without considering the cloud network resource distribution. This paper proposes a traffic forecasted assisted proactive VNF scaling approach, and it adopts the instance capacity adaptive to the node resource. We first model the VNF scaling as integer quadratic programming and then propose a proactive adaptive VNF scaling (PAVS) approach. The approach employs an efficient traffic forecasting method based on LSTM to predict the upcoming traffic demands. With the obtained traffic demands, we design a resource-aware new VNF instance deployment algorithm to scale out under-provisioning VNFs and a redundant VNF instance management mechanism to scale in over-provisioning VNFs. Trace-driven simulation demonstrates that our proposed approach can respond to traffic fluctuation in advance and reduce the total cost significantly.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 하계학술대회 논문집 B
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• pp.546-549
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• 1995

Recently, electric utility is facing substantially new stream of business environment, such as pressure of business restructuring, competition with private IPPs, diversification of supply-side and demand-side resource options, environmental externalities and uncertainties. Integrated resource planning(IRP) is very useful and powerful approach for solving complex and diversified electricity supply and demand problems. This paper presents a standardized IRP procedure using multi-attribute decision analysis approach. The selection of the most desirable plan is based on multi-attribute trade-off/risk analysis method and score ranking method. As a case study, 50 plans with 12 scenarios are analyzed.

• Journal of electromagnetic engineering and science
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• 제15권1호
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• pp.14-19
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• 2015

In multicellular wireless networks, intercell interference limits system performance, especially cell edge user performance. One promising approach to solve this problem is the intercell interference coordination (ICIC) scheme. In this paper, we propose a new ICIC scheme based on a resource partitioning approach to enhance cell edge user performance in a wireless multicellular system. The most important feature of the proposed scheme is that the algorithm is performed at each base station in a distributed manner and therefore minimizes the required information exchange between neighboring base stations. The proposed scheme has benefits in a practical environment where the traffic load distribution is not uniform among base stations and the backhaul capacity between the base stations is limited.

• Journal of Communications and Networks
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• 제15권5호
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• pp.469-475
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• 2013

In this paper, we propose an efficient interference management technique which controls the number of resource blocks (or subcarriers) shared with other cells based on statistical interference levels among cells. The proposed technique tries to maximize average throughput of a femto cell user under a constraint on non-real time control of a femto cell network while guaranteeing a target throughput value of a macro cell user. In our proposed scheme, femto cells opportunistically use resource blocks allocated to other cells if the required average user throughput is not attained with the primarily allocated resource blocks. The proposed method is similar to the underlay approach in cognitive radio systems, but resource block sharing among cells is statistically controlled. For the statistical control, a femto cell sever constructs a table storing average mutual interference among cells and periodically updates the table. This statistical approach fully satisfies the constraint of non-real time control for femto cell networks. Our simulation results show that the proposed scheme achieves higher average femto user throughput than conventional frequency reuse schemes for time varying number of users.

• 한국산학기술학회논문지
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• 제15권10호
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• pp.6004-6013
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• 2014

다각화 분야 내에서 자원공유의 사안을 다루는 연구들은 경영자원의 '공유'에 주목하였고, '경영자원'에 대한 관심은 부족하였다. 이에 따라 본 연구는 자원기반관점의 핵심적인 변수들과 논리들을 토대로 자원공유의 결정요인과 성과함의에 대해 접근하였다. 본 연구는 우리나라 35개 기업집단의 계열사 263개를 대상으로 실시된 설문조사를 토대로 경영자원의 양적 수준, 질적 수준, 활용성이 계열사 간 자원공유에 미치는 영향에 대한 가설을 수립하고 다중회귀분석을 통해 검증하였으며, 성과함의와 관련하여 경영자원의 양적 수준과 자원공유, 경영자원의 질적 수준과 자원공유, 경영자원의 활용성과 자원공유의 상호작용이 계열사의 성과에 미치는 영향에 대한 가설을 수립하고 상호작용항이 포함된 다중회귀분석을 통해 검증하였다. 가설검증 결과, 경영자원의 양적 수준이 낮을수록, 질적 수준이 높을수록, 활용성이 높을수록 자원공유의 정도는 증가하는 것으로 나타났으며, 경영자원의 양적 수준이 낮을수록, 활용성이 높을수록 계열사 간 자원공유가 성과에 미치는 긍정적인 영향이 증가하는 것으로 확인되었다. 하지만 경영자원의 질적 수준은 자원공유와 성과의 관계에 영향을 미치지 않았다. 본 연구는 경영자원의 질적 수준 및 활용성이 가설과는 상반된 방향으로 자원공유에 영향을 미치는 이유, 경영자원의 질적 수준이 자원공유에는 긍정적으로 작용하지만 성과향상으로 이어지지 않은 이유, 경영자원의 유형에 따라 가설검증의 결과가 달라지는지의 여부 등을 충분히 다루지 못했는데, 향후 연구에서는 이에 대한 보다 심화된 논의가 필요할 것으로 생각된다.

• 한국통신학회논문지
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• 제34권11B호
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• pp.1178-1190
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• 2009

무선 랜에서 다양한 QoS를 제공하기 위해 제안된 IEEE 802.11e는 경쟁기반의 EDCA와 비경쟁 기반인 HCCA 모드를 가진다. 802.11e의 중앙제어 방식인 HCCA는 효율적인 자원분배를 하는 스케줄링 알고리즘을 필요로 한다. 그러나 기존의 HCCA 스케줄러 알고리즘들은 VBR 트래픽 제공하는 실시간 서비스에 QoS를 보장하는데 있어 어려움이 있다. 본 논문에서는 VBR 트래픽에 대하여 QoS를 보장하는 효율적인 자원분배를 위해 평균자원 할당과 최대 자원 할당방법을 동시에 사용하는 이중 리키 버킷을 사용하였다. QoS 보장 된 스테이션의 개수를 최대화하기 위하여 statistical 접근법을 사용하여 각 스테이션의 필요한 TXOP의 최소값을 구하였다. 시뮬레이션 결과는 제안한 알고리즘의 성능이 참조 스케줄러와 비교하여 전송률과 전송 지연 측면에서 성능이 좋음을 보여준다.

• 한국정보처리학회논문지
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• 제6권11S호
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• pp.3350-3355
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• 1999

Modeling for the Internet resource is important to use of limited resource efficiently. Also, the modeling could guide how we can approach the Internet problems. The many studies of price mechanism to internalize the externality, to decrease the externality from congestion, and to use the Internet resource efficiently, are widely going on. The represent styles for Internet pricing are usage-based pricing(UBP) and flat-rat pricing(FRP) and the FRP could prefers for the beginning stage of Internet introduce. The purpose of this study is to examine the efficiency of Internet pricing mechanism based on flat-rate pricing, both consumer and producer side.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권8호
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• pp.1825-1842
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• 2013

Rapid growth of the IT industry has led to significant energy consumption in the last decade. Data centers swallow an enormous amount of electrical energy and have high operating costs and carbon dioxide excretions. In response to this, the dynamic consolidation of virtual machines (VMs) allows for efficient resource management and reduces power consumption through the live migration of VMs in the hosts. Moreover, each client typically has a service level agreement (SLA), this leads to stipulations in dealing with energy-performance trade-offs, as aggressive consolidation may lead to performance degradation beyond the negotiation. In this paper we propose a heuristic based resource allocation of VM selection and a VM allocation approach that aims to minimize the total energy consumption and operating costs while meeting the client-level SLA. Our experiment results demonstrate significant enhancements in cloud providers' profit and energy savings while improving the SLA at a certain level.

• ETRI Journal
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• 제43권1호
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• pp.53-63
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• 2021

Cloud computing has drastically reduced the price of computing resources through the use of virtualized resources that are shared among users. However, the established large cloud data centers have a large carbon footprint owing to their excessive power consumption. Inefficiency in resource utilization and power consumption results in the low fiscal gain of service providers. Therefore, data centers should adopt an effective resource-management approach. In this paper, we present a novel load-balancing framework with the objective of minimizing the operational cost of data centers through improved resource utilization. The framework utilizes a modified genetic algorithm for realizing the optimal allocation of virtual machines (VMs) over physical machines. The experimental results demonstrate that the proposed framework improves the resource utilization by up to 45.21%, 84.49%, 119.93%, and 113.96% over a recent and three other standard heuristics-based VM placement approaches.

• Journal of Information Processing Systems
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• 제19권4호
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• pp.439-449
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• 2023

This paper deals with a resource efficient artificial intelligence (AI) service architecture for multi-channel video streams. As an AI service, we consider the object detection model, which is the most representative for video applications. Since most object detection models are basically designed for a single channel video stream, the utilization of the additional resource for multi-channel video stream processing is inevitable. Therefore, we propose a resource efficient AI service framework, which can be associated with various AI service models. Our framework is designed based on the modular architecture, which consists of adaptive frame control (AFC) Manager, multiplexer (MUX), adaptive channel selector (ACS), and YOLO interface units. In order to run only a single YOLO process without regard to the number of channels, we propose a novel approach efficiently dealing with multi-channel input streams. Through the experiment, it is shown that the framework is capable of performing object detection service with minimum resource utilization even in the circumstance of multi-channel streams. In addition, each service can be guaranteed within a deadline.