• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.978-980
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• 2006

A Next Generation Network (NGN) is a packet-based network able to provide services including Telecommunication Services and able to make use of multiple broadband, QoS-enabled transport technologies and in which service-related functions are independent from underlying transport-related technologies. It offers unrestricted access by users to different service providers. It supports generalized mobility which will allow consistent and ubiquitous provision of services to users In this paper, we explain the trend of standardization activity related with open services in ITU-T SG13(Study Group 13). ITU-T SG13 is responsible for studies .elating to the architecture, evolution and convergence of next generation networks including frameworks and functional architectures, signalling requirements for NGN.

• The KIPS Transactions:PartA
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• v.8A no.4
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• pp.287-292
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• 2001

Multimedia service systems should have efficient capacity to serve the growing clients and new data. In the general streaming services, users can endure the small amount of time delay at the beginning of service. But they want to have good quality of service. A streaming server tries to transfer video files to clients from a repository of files in real time. The server must guarantee concurrent and uninterrupted delivery of each video stream requested from clients. To achieve its purpose, many stream servers adopt multi-processors, sufficient memory, and RAID or SAN in their systems. In this paper, we propose a Linux-based parallel media streaming server. It is superior to the other systems in the storing structure, fault-tolerance, and service capacity. Since this system supports the web interlace, users can operate easily through the www. This system uses unique striping policy to distribute multimedia files into the parallel storage nodes. If a service request occurs, each storage node transmits striped files concurrently to the client. Its performance is better than the single media streaming service because of the parallel architecture.

• The KIPS Transactions:PartC
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• v.9C no.2
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• pp.213-220
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• 2002

Distributed competing system gives a new system architecture to be taken into consideration for solving the problems of interoperability of heterogeneous systems. In the present paper, CORBA based on multi-threaded interoperates with software blocks at physically isolated hardware. We show how archives optimal CORBA system from analysis of required functions, implementations of protocols and benchmarking of system performance in the Open Multi-service Network System Environment. The core features of our CORBA system are restricted Quality of Service based on priority, timeout service and exception status information notify to the related software blocks. And the objectives are design and implementation of high performance multi-threaded middleware and satisfied with extendibility, flexibility and stability of CORBA platform.

• Journal of KIISE:Information Networking
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• v.35 no.3
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• pp.173-182
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• 2008

Promoting quality of streaming service in wireless networks has attracted intensive research over the years. Instable wireless channel condition causes high transmission delay and packet loss, due to fading and interference. Therefore, they lead to degrade quality of video streaming service. The IEEE 802.11 Working Group is currently working on a new standard called IEEE 802.11e to support quality of service in WLANs. And several schemes were proposed in order to guarantee QoS. However, they are not adaptable to network condition. Accordingly, they suffered video quality degradation, due to buffer overflow or packet loss. In this paper, to promote quality of video streaming service in WLANs, we propose a cross-layer architecture based on IEEE 802.11e EDCA model. Our cross-layer architecture provides differentiated transmission mechanism of IEEE 802.11e EDCA based on priority of MPEG-4 video frames and adaptively controls the transmission rate by dropping video frames through the efficient bandwidth estimation based on distinction of each AC. Through the simulation, proposed scheme is shown to be able to improve end-to-end qualify for video streaming service in WLANs.

• Journal of Information Technology and Architecture
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• v.10 no.1
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• pp.101-111
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• 2013

Internet traffic volume has been increasing rapidly due to popularization of various smart devices and Internet development. In particular, HTTP-based traffic volume of smart devices is increasing rapidly in addition to desktop traffic volume. The increased mobile traffic can cause serious problems such as network overload, web security, and QoS. In order to solve these problems of the Internet overload and security, it is necessary to accurately detect applications. Traditionally, well-known port based method is utilized in traffic classification. However, this method shows low accuracy since P2P applications exploit a TCP/80 port, which is used for the HTTP protocol; to avoid firewall or IDS. Signature-based method is proposed to solve the lower accuracy problem. This method shows higher analysis rate but it has overhead of signature generation. Also, previous signature-based study only analyzes applications in HTTP protocol-level not application-level. That is, it is difficult to identify application name. Therefore, previous study only performs protocol-level analysis. In this paper, we propose a signature generation method to classify HTTP-based traffics in application-level using the characteristics of typical semi HTTP header. By applying our proposed method to campus network traffic, we validate feasibility of our method.

• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.345-353
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• 2021

Cloud computing represent a new era of computing that's forms through the combination of service-oriented architecture (SOA), Internet and grid computing with virtualization technology. Virtualization is a concept through which every cloud is enable to provide on-demand services to the users. Most IT service provider adopt cloud based services for their users to meet the high demand of computation, as it is most flexible, reliable and scalable technology. Energy based performance tradeoff become the main challenge in cloud computing, as its acceptance and popularity increases day by day. Cloud data centers required a huge amount of power supply to the virtualization of servers for maintain on- demand high computing. High power demand increase the energy cost of service providers as well as it also harm the environment through the emission of CO₂. An optimization of cloud computing based on energy-performance tradeoff is required to obtain the balance between energy saving and QoS (quality of services) policies of cloud. A study about power usage of resources in cloud data centers based on workload assign to them, says that an idle server consume near about 50% of its peak utilization power [1]. Therefore, more number of underutilized servers in any cloud data center is responsible to reduce the energy performance tradeoff. To handle this issue, a lots of research proposed as energy efficient algorithms for minimize the consumption of energy and also maintain the SLA (service level agreement) at a satisfactory level. VM (virtual machine) consolidation is one such technique that ensured about the balance of energy based SLA. In the scope of this paper, we explore reinforcement with fuzzy logic (RFL) for VM consolidation to achieve energy based SLA. In this proposed RFL based active VM consolidation, the primary objective is to manage physical server (PS) nodes in order to avoid over-utilized and under-utilized, and to optimize the placement of VMs. A dynamic threshold (based on RFL) is proposed for over-utilized PS detection. For over-utilized PS, a VM selection policy based on fuzzy logic is proposed, which selects VM for migration to maintain the balance of SLA. Additionally, it incorporate VM placement policy through categorization of non-overutilized servers as- balanced, under-utilized and critical. CloudSim toolkit is used to simulate the proposed work on real-world work load traces of CoMon Project define by PlanetLab. Simulation results shows that the proposed policies is most energy efficient compared to others in terms of reduction in both electricity usage and SLA violation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4717-4737
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• 2017

Today, smart grids, smart homes, smart water networks, and intelligent transportation, are infrastructure systems that connect our world more than we ever thought possible and are associated with a single concept, the Internet of Things (IoT). The number of devices connected to the IoT and hence the number of traffic flow increases continuously, as well as the emergence of new applications. Although cutting-edge hardware technology can be employed to achieve a fast implementation to handle this huge data streams, there will always be a limit on size of traffic supported by a given architecture. However, recent cloud-based big data technologies fortunately offer an ideal environment to handle this issue. Moreover, the ever-increasing high volume of traffic created on demand presents great challenges for flow management. As a solution, flow aggregation decreases the number of flows needed to be processed by the network. The previous works in the literature prove that most of aggregation strategies designed for smart grids aim at optimizing system operation performance. They consider a common identifier to aggregate traffic on each device, having its independent static aggregation policy. In this paper, we propose a dynamic approach to aggregate flows based on traffic characteristics and device preferences. Our algorithm runs on a big data platform to provide an end-to-end network visibility of flows, which performs high-speed and high-volume computations to identify the clusters of similar flows and aggregate massive number of mice flows into a few meta-flows. Compared with existing solutions, our approach dynamically aggregates large number of such small flows into fewer flows, based on traffic characteristics and access node preferences. Using this approach, we alleviate the problem of processing a large amount of micro flows, and also significantly improve the accuracy of meeting the access node QoS demands. We conducted experiments, using a dataset of up to 100,000 flows, and studied the performance of our algorithm analytically. The experimental results are presented to show the promising effectiveness and scalability of our proposed approach.