• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.107-110
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• 2015

In this paper, we propose a coalitonal game theoritic approach to the power control problem in resource-constrained wireless sensor networks, where the objective is to enhance power efficiency of individual sensors while providing the QoS requirements. We model this problem as two-sided one-to-one matching game and deploly deferred acceptance procedure that produces a single matching in the core. Furthermore, we show that, by applying the procedure repeatedly, a certain stable state is achieved where no sensor can anticipate improvements in their power efficiency as far as all of them are subject to their own QoS constraints. We evaluate our proposal by comparing them with cluster-based and the local optimal solution obtained by maximizing the total system energy efficiency, where the objective function is non-convex.

• Journal of KIISE:Databases
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• v.29 no.2
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• pp.119-127
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• 2002

Video server which stores video streams should serve more users with the requested streams rapidly, satisfying their time constraints. However, the number of users supported and the response times for the requested services in video server are in the oppositional relationship with viewpoint of disk throughput. In this paper, we propose new policy that can provide not only rapid responses for the service requests but also increase the number of users supported in the storage system of video server. The policy admits the random movements of disk heads for urgent service requests but maintains the sequential or restricted movements of disk heads and eliminates rewind time of disk heads for less-urgent service requests in storage system of multiple disks environment so that it can not satisfy only the QoS of users but also support more users.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1147-1161
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• 2023

The Internet of Things (IoT) requires a new processing model that will allow scalability in cloud computing while reducing time delay caused by data transmission within a network. Such a model can be achieved by using resources that are closer to the user, i.e., by relying on edge computing (EC). The amount of IoT data also grows with an increase in the number of IoT devices. However, building such a flexible model within a heterogeneous environment is difficult in terms of resources. Moreover, the increasing demand for IoT services necessitates shortening time delay and response time by achieving effective load balancing. IoT devices are expected to generate huge amounts of data within a short amount of time. They will be dynamically deployed, and IoT services will be provided to EC devices or cloud servers to minimize resource costs while meeting the latency and quality of service (QoS) constraints of IoT applications when IoT devices are at the endpoint. EC is an emerging solution to the data processing problem in IoT. In this study, we improve the load balancing process and distribute resources fairly to tasks, which, in turn, will improve QoS in cloud and reduce processing time, and consequently, response time.

• Journal of Korean Institute of Industrial Engineers
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• v.25 no.4
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• pp.500-509
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• 1999

In this paper, we consider an optimal routing problem when point-to-point and point-to-multipoint connection traffics are offered in an ATM network. We propose a mathematical model for cost-minimizing configuration of a logical network for a given ATM-based BISDN. Our model is essentially identical to the previous one proposed by Kim(Kim, 1996) which finds a virtual-path configuration where the relevant gains obtainable from the ATM technology such as the statistical multiplexing gain and the switching/control cost-saving gain are optimally traded-off. Unlike the Kim's model, however, ours explicitly considers the VP's QoS(Quality of Service) for more efficient utilization of bandwidth. The problem is a large-scale, nonlinear, and mixed-integer problem. The proposed algorithm is based on the local linearization of equivalent-capacity functions and the relaxation of link capacity constraints. As a result, the problem can be decomposed into moderate-sized shortest path problems, Steiner arborescence problems, and LPs. This fact renders our algorithm a lot faster than the previous nonlinear programming algorithm while the solution quality is maintained, hence application to large-scale network problems.

• Journal of Broadcast Engineering
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• v.13 no.1
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• pp.6-16
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• 2008

An instable wireless channel condition causes more packet losses and retransmissions due to interference, fading, station mobility, and so on. Therefore video streaming service over a wireless networks is a challenging task because of the changes in the wireless channel conditions and time-constraints characteristics of the video streaming services. To provide efficient video streaming over a wireless networks, QoS-enhanced MAC protocol, IEEE 802.11e, is standardized recently. Tn this paper, we propose a new network-adaptive H.264 video streaming mechanism in the IEEE 802.11e wireless networks. To improve the quality of video streaming services, video stream has to adapt to the changes in the wireless channel conditions. The wireless channel conditions are estimated by the packet loss probability and informed to the application layer by the cross-layering. According to the wireless channel information, the video streaming application filters out the low-priority data. This adaptation mechanism efficiently uses system resources because it drops the low-priority data in advance. Therefore, our cross-layer design can provide improved video streaming services to the end-user. Through the implementation and performance evaluation, we prove that the proposed mechanism improves the QoS of the video streaming by providing the smoothed playback.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.5712-5728
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• 2017

Recently, there are many studies, that considering green wireless cellular networks, have taken the energy consumption of the base station (BS) into consideration. In this work, we first introduce an energy consumption model of multi-mode sharing BS powered by multiple energy sources including renewable energy, local storage and power grid. Then communication load requests of the BS are transformed to energy demand queues, and battery energy level and worst-case delay constraints are considered into the virtual queue to ensure the network QoS when our objective is to minimize the long term electricity cost of BSs. Lyapunov optimization method is applied to work out the optimization objective without knowing the future information of the communication load, real-time electricity market price and renewable energy availability. Finally, linear programming is used, and the corresponding energy efficient scheduling policy is obtained. The performance analysis of our proposed online algorithm based on real-world traces demonstrates that it can greatly reduce one day's electricity cost of individual BS.

• Journal of KIISE:Computing Practices and Letters
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• v.6 no.4
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• pp.430-440
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• 2000

To support Integrated Services in the Internet, the Internet Engineering Task Force(IETF) has developed new mechanisms. These new mechanisms include Resource Reservation Protocol(RSVP) and Integrated Services model. RSVP and Integrated Services are independent of the underlying link layer technologies and it is necessary to define the mapping of RSVP and Integrated Services specifications onto specific link layer technologies. IETF proposed a Subnet Bandwidth Manager(SBM) providing a method for mapping RSVP onto IEEE802 style networks. However, the SBM has several constraints and problems. For solving these constraints and problems, we design and implement a new Ethernet Bandwidth Manager(EBM). This paper discusses (1) new bandwidth management mechanism independent of RSVP, (2) simulation of Ethernet bandwidth to analyze the characteristics of Ethernet and accomplish Ethernet bandwidth management, (3) design and implemetation of EBM that allows Controlled-Load Service, and (4) results of our experiments on EBM.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.6
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• pp.2595-2618
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• 2018

In this paper, we investigate secure communication with the presence of multiple eavesdroppers (Eves) in a two-tier downlink dense heterogeneous network, wherein there is a macrocell base station (MBS) and multiple femtocell base stations (FBSs). Each base station (BS) has multiple users. And Eves attempt to wiretap a macrocell user (MU). To keep Eves ignorant of the confidential message, we propose a physical-layer security scheme based on cross-layer cooperation to exploit interference in the considered network. Under the constraints on the quality of service (QoS) of other legitimate users and transmit power, the secrecy rate of system can be maximized through jointly optimizing the beamforming vectors of MBS and cooperative FBSs. We explore the problem of maximizing secrecy rate in both non-colluding and colluding Eves scenarios, respectively. Firstly, in non-colluding Eves scenario, we approximate the original non-convex problem into a few semi-definite programs (SDPs) by employing the semi-definite relaxation (SDR) technique and conservative convex approximation under perfect channel state information (CSI) case. Furthermore, we extend the frame to imperfect CSI case and use the Lagrangian dual theory to cope with uncertain constraints on CSI. Secondly, in colluding Eves scenario, we transform the original problem into a two-tier optimization problem equivalently. Among them, the outer layer problem is a single variable optimization problem and can be solved by one-dimensional linear search. While the inner-layer optimization problem is transformed into a convex SDP problem with SDR technique and Charnes-Cooper transformation. In the perfect CSI case of both non-colluding and colluding Eves scenarios, we prove that the relaxation of SDR is tight and analyze the complexity of proposed algorithms. Finally, simulation results validate the effectiveness and robustness of proposed scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.6
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• pp.2680-2696
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• 2018

The collaborative content caching system is an effective solution developed in recent years to reduce transmission delay and network traffic. In order to decrease the service end-to-end transmission delay for future 5G ultra-dense networks (UDN), this paper proposes a novel service migration method that can guarantee the continuity of service and simultaneously reduce the traffic flow in the network. In this paper, we propose a service migration optimization model that minimizes the cumulative transmission delay within the constraints of quality of service (QoS) guarantee and network condition. Subsequently, we propose an improved firefly algorithm to solve this optimization problem. Simulation results show that compared to traditional collaborative content caching schemes, the proposed algorithm can significantly decrease transmission delay and network traffic flow.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.5A
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• pp.355-362
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• 2009

In real-time communication services, delay constraints are among the most important QoS (Quality of Service) factors. In particular, it is difficult to guarantee the delay requirement over wireless channels, since they exhibit dynamic time-varying behavior and even severe burst-errors during periods of deep fading. Channel throughput may be increased, but at the cost of the additional delays when ARQ (Automatic Repeat Request) schemes are used. For real-time communication services, it is very essential to predict data deliverability. This paper derives the delay distribution and the successful delivery probability within a given delay budget using a priori channel model and a posteriori information from the perspective of queueing theory. The Gilbert-Elliot burst-noise channel is employed as an a Priori channel model, where a two-state Markov-modulated Bernoulli process $(MMBP_2)$ is used. for a posteriori information, the channel parameters, the queue-length and the initial channel state are assumed to be given. The numerical derivation is verified and analyzed via Monte Carlo simulations. This numerical derivation is then applied to a rate control scheme for real-time video transmission, where an optimal encoding rate is determined based on the future channel capacity and the distortion of the reconstructed pictures.