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

• Proceedings of the Korea Information Processing Society Conference
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• 2000.10b
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• pp.1613-1616
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• 2000

DiffServ 네트웍 모델은 기존의 Best Effort 서비스를 지원하는 IP 네트웍에 차별화된 서비스를 지원 할 수 있는 IP QoS를 무리없이 도입하기 위하여 제안되었다. DiffServ 네트웍은 IntServ에서와 같은 Scalability 문제를 해소할 수 있도록 Edge-to-Edge QoS를 지원하기 용이한 단순화된 구조를 가지고 있다. 이러한 단순화시킨 네트웍 구조에서 여러 가지 QoS 요구 특성을 가지는 트래픽에게 서비스를 제공하고, 네트웍 자원의 이용 효율을 극대화 하고자 하는 사업자의 요구에 따라 효율적인 자원 할당 방안이 필요하게 된다. 자원 활용의 효율을 제고하기 위해서는 정밀하고 동적인 자원할당 방식을 이용하는 것이 필요하며, 이를 실현하기 위하여 Intra-domain의 Edge-to-Edge Path 상에 있는 노드에서의 트래픽 부하 측정을 바탕으로, DSCP 제어 코드를 사용한 탐색 패킷을 통하여 Intra-domain의 부하 및 자원 할당 수준을 탐색하고, 이를 기반으로 Admission Control을 중심으로 한 Resource Provisioning을 동적으로 수행할 수 있는 메커니즘을 제안한다.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07a
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• pp.328-330
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• 2005

현재의 RSVP-TE는 VPN hose provisioning 메커니즘들을 고려하여 자원예약을 수행하지 못한다. 이 논문에서는 Provider Provisioned-Virtual Private Network(PP-VPN)에서 Quality of Service(QoS)를 제공하는 Hose 모델 기반의 provisioning 메커니즘들을 네트워크에 적용하여 자원예약을 수행하도록 하기 위해 Resource Reservation Protocol Traffic Engineering(RSVP-TE)의 확장방안에 대해 설명한다. 동일한 VPN을 서비스하는 LSP들 간 자원을 공유할 수 있게 함으로써 네트워크 상에 요구되는 자원을 최적화하였으며, VPN 고객을 서비스하기 위한 효율적이고 자동적인 자원예약이 가능하도록 하였다. 이 논문에서는 솔루션의 프로토콜 elements와 procedure에 대하여 설명한다.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.40 no.12
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• pp.83-93
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• 2003

Differentiated service networks, based on bandwidth broker, perform the control and management of QoS provisioning for the QoS guaranteed services, However, the centralized bandwidth broker model has a scalability problem since it has centralized resource management for the admission control function of all call attempts, Therefore, in this paper, we proposea novel adaptive admission control mechanism according to the attempted call status for enhancing the scalability under the centralized bandwidth broker model in IP differentiated service networks, The proposed mechanism decouples the function of admission control from the bandwidth broker, So, the ingress edge node performs the admission control and the bandwidth broker performs the resource management and QoS provisioning, We also introduce an edge-to-edge path concepts and the ingress edge node performs the admission control under the allocated bandwidth to eachpath. The allocated bandwidth per path adaptively varies according to the status of the attempted calls, This mechanism can significantly reduce the number of communication message between the bandwidth broker and each edge node in the network and increase the bandwidth utilization via adaptable resource allocation, In this paper we study the adaptive admission control operation and show the efficient and extensive improvement through the performance evaluation.

• Journal of Internet Computing and Services
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• v.14 no.5
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• pp.39-48
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• 2013

A cloud system has to deal with highly variable workloads resulting from dynamic usage patterns in order to keep the QoS within the predefined SLA. Aside from the aspects regarding services, another emerging concern is to keep the energy consumption at a minimum. This requires the cloud providers to consider energy and performance trade-off when allocating virtualized resources in cloud data centers. In this paper, we propose a resource provisioning approach based on dynamic thresholds to detect the workload level of the host machines. The VM selection policy uses utilization data to choose a VM for migration, while the VM allocation policy designates VMs to a host based on its service reputation. We evaluated our work through simulations and results show that our work outperforms non-power aware methods that don't support migration as well as those based on static thresholds and random selection policy.

• Journal of Korea Multimedia Society
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• v.15 no.12
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• pp.1464-1474
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• 2012

In this paper, we propose a QoS (Quality of Service)-aware and cooperative resource reservation scheme using cross-layer link adaptation for wireless high definition video transmission through UWB (Ultra Wide Band) network with D-MAC (Distributed Medium Access Control). A wireless high definition video transmission system usually requires stable high throughput even without line-of-sight, e.g., a destination device in another room separated by a wall. Since the WiMedia D-MAC supporting DRP (Distributed Reservation Protocol) scheme causes lots of DRP resource reservation conflicts due to failure of beacon detection in wireless channel environment, overall performances of the WiMedia D-MAC can be deteriorated. And the current WiMedia MAC standard has not considered QoS provisioning even though QoS parameters such as a range of service rates are provided to each traffic stream. Therefore, we propose Relay DRP protocol with QoS-based relay node selection criterion, which makes a relay path to avoid DRP resource reservation conflicts and guarantee QoS more stably through cross-layer link adaptation of cooperative relay transmission scheme and is compliant with the current WiMedia D-MAC protocol. Simulation results demonstrate performance improvements of the proposed method for throughput and QoS provisioning.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.4
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• pp.653-658
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• 2015

Cloud service is one of major challenges in IT industries. In cloud environment, service providers predict dynamic user demands and provision resources to guarantee the QoS to cloud users. The conventional prediction models guarantee the QoS to cloud user, but don't guarantee profit of service providers. In this paper, we propose a new resource allocation mechanism using Q-learning algorithm to provide the QoS to cloud user and guarantee profit of service providers. To evaluate the performance of our mechanism, we compare the total expense and the VM provisioning delay with the conventional techniques with real data.

• The Journal of Korean Association of Computer Education
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• v.12 no.2
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• pp.77-86
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• 2009

Large-scale applications, that needs large-capacity R&D resources and realtime data transmission, have demanded more stable and high-performance network environment than current Internet environments. Recently, global R&D networks have focuses on utilizing Lambda networking technologies and resource reservation systems to be satisfied with various applications' requirements. In this paper, we modify the existing DRS (Dynamic Right-Sizing) model to reflect various advantages in terms of the stability and high-capacity of Lambda network. In addition, we suggest the design methodology of high-performance Lambda network, which can integrate NRPS (Network Resource Provisioning System) into our modified DRS model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.2774-2796
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• 2015

Quality-of-service (QoS) provisioning for a cognitive mesh network (CMN) with heterogeneous services has become a challenging area of research in recent days. Considering both real-time (RT) and non-real-time (NRT) traffic in a multihop CMN, [1] studied cross-layer resource management, including joint access control, route selection, and resource allocation. Due to the complexity of the formulated resource allocation problems, which are mixed-integer non-linear programming, a low-complexity yet efficient algorithm was proposed there to approximately solve the formulated optimization problems. In contrast, in this work, we present an application of genetic algorithm (GA) to re-address the hard resource allocation problems studied in [1]. Novel initialization, selection, crossover, and mutation operations are designed such that solutions with enough randomness can be generated and converge with as less number of attempts as possible, thus improving the efficiency of the algorithm effectively. Simulation results show the effectiveness of the newly proposed GA-based algorithm. Furthermore, by comparing the performance of the newly proposed algorithm with the one proposed in [1], more insights have been obtained in terms of the tradeoff among QoS provisioning for RT traffic, throughput maximization for NRT traffic, and time complexity of an algorithm for resource allocation in a multihop network such as CMN.