• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.17 no.4
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• pp.295-306
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• 2013

In this paper, we consider the adaptive multigrid method for solving the Black-Scholes equation to improve the efficiency of the option pricing. Adaptive meshing is generally regarded as an indispensable tool because of reduction of the computational costs. The Black-Scholes equation is discretized using a Crank-Nicolson scheme on block-structured adaptively refined rectangular meshes. And the resulting discrete equations are solved by a fast solver such as a multigrid method. Numerical simulations are performed to confirm the efficiency of the adaptive multigrid technique. In particular, through the comparison of computational results on adaptively refined mesh and uniform mesh, we show that adaptively refined mesh solver is superior to a standard method.

• Journal of Communications and Networks
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• v.12 no.3
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• pp.253-265
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• 2010

The problem of pricing for a telecommunication network is investigated with respect to the users' sensitivity to the pricing structure. A functional optimization problem is formulated, in order to compute price reallocations as functions of data collected in real time during the network evolution. No a-priori knowledge about the users' utility functions and the traffic demands is required, since adaptive reactions to the network conditions are sought in real time. To this aim, a neural approximation technique is studied to exploit an optimal pricing control law, able to counteract traffic changes with a small on-line computational effort. Owing to the generality of the mathematical framework under investigation, our control methodology can be generalized for other decision variables and cost functionals.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1074-1077
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• 2002

This paper proposes an adaptive pricing system with scheduling to balance the demand for contents and to realize an effective use of resources in contents delivery networks. In the proposed adaptive pricing system, the table of the service levels and prices (tariff) is shown to each user at the start of service and each user chooses one of the service classes. These prices are decided adaptively reflecting the congestion state of the networks. Then, by the proposed scheduling algorithm, these requests are scheduled so as to keep the service level agreements completely.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.7
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• pp.2281-2301
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• 2014

In wireless ad hoc networks the nodes focus on achieving the maximum SINR for efficient data transmission. In order to achieve maximum SINR the nodes culminate in exhausting the battery power for successful transmissions. This in turn affects the successful transmission of the other nodes as the maximum transmission power opted by each node serves as a source of interference for the other nodes in the network. This paper models the choice of power for each node as a non cooperative game where the throughput of the network with respect to the consumption of power is formulated as a utility function. We propose an adaptive pricing scheme that encourages the nodes to use minimum transmission power to achieve target SINR at the Nash equilibrium and improve their net utility in multiuser scenario.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.8B
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• pp.764-768
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• 2006

Over the years, the widespread proliferation of multimedia services has necessitated the development for an efficient network management. In this paper, we investigate the role of adaptive online pricing mechanism in order to manage effectively the network congestion problem. Our on-line approach is dynamic and flexible that responds to current network conditions. With a simulation study, we demonstrate that our proposed scheme enhances network performance and system efficiency simultaneously under widely diverse traffic load intensities.

• ETRI Journal
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• v.42 no.4
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• pp.585-595
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• 2020

Integration of multiple communication technologies in a smart grid (SG) enables employing cognitive radio (CR) technology for improving reliability and security with low latency by adaptively and effectively allocating spectral resources. The versatile features of the CR enable the smart meter to select either the unlicensed or the licensed band for transmitting data to the utility company, thus reducing communication outage. Demand response management is regarded as the control unit of the SG that balances the load by regulating the real-time price that benefits both the utility company and consumers. In this study, joint allocation of the transmission power to the smart meter and consumer's demand is formulated as a two stage multi-armed bandit game in which the players select their optimal strategies noncooperatively without having any prior information about the media. Furthermore, based on historical rewards of the player, a real-time pricing adaptation method is proposed. The latter is validated through numerical results.

• Journal of KIISE:Information Networking
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• v.37 no.2
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• pp.94-98
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• 2010

In this paper, we formalize a new adaptive online price control scheme based on the Stackelberg game model. By using the hierarchical interaction strategy, control decisions in each mechanism act cooperatively and collaborate with each other to satisfy conflicting performance criteria. In addition, our dynamic online approach is practical for real network implementation. With a simulation study, the proposed scheme can adaptively adjust the network price to approximate an optimized solution under widely diverse network situations.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10c
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• pp.117-119
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• 2000

UMTS(Universal Mobile Telecommunication System)의 Core Network에서는 SGSN(Serving GPRS Support Node)과 GGSN(Gateway GPRS Support Node)사이의 전송계층을 IP-Over-ATM network을 기반으로 한다. 이는 비연결형(connectionless) IP 트래픽들을 연결지향형(connectionoriented) ATM 전송계층을 통해 전송함으로 이때 효율적인 자원관리를 위해 적절한 VC(Virtual Circuit)의 접속과 해제를 수행해야 한다. 본 논문에서는 [1]에서 제안되는 GPRS(General Packer Radio Service)의 Web 트래픽 모델에 대하여 기존의 VC의 Holding-time을 결정하는 기법인 Holding Cost Pricing Model(LRU, Mean-Variance, Adaptive policy) [2]을 GGSN과 SGSN사이의 ATM 전송계층에 적용하였다. 각각의 기법들에서 VC의 이용률(utilization)과 설정율(setup rate)을 비교함으로써 Adaptive policy 기법의 성능이 다른 기법에 비해 효율적임을 알 수 있다.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.2
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• pp.11-17
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• 2009

This paper presents a new adaptive relay selection scheme for a regenerative orthogonal frequency division multiplexing access(OFDMA) relay network with fairness constrains. In the Proposed scheme, we select the best M relays out of a set of K potential relays to maximize system capacity. Among these selected relays, subcarriers are reallocated to satisfy fairness constraints as well as to minimize the degradation of the system performance. Afterwards, power allocation is performed for each subcarrier based on the water-filling method to enhance the performance improvement. By using the trade-off relationship between the system capacity and the fairness, the modified version of proposed scheme is also investigated.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.05a
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• pp.648-652
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• 2003

In the GPRS(General Packet Radio Service) network, the transport layer between SGSN(Serving GPRS Support Node) and GGSN (Gateway GPRS Support Node) is based on IP-Over ATM Network. which means that the connectionless IP traffic is transmitted through connection oriented ATM transport layer. Efficient resource management is needed to perform connection and disconnection of the pertinent VC because of the connectionless IP traffic being passed through ATM transport layer In this paper, Internet Web service traffic model in the GPRS network is applied to the various VC holding Cost Pricing Model. each method is compared through analyzing each VC utilization and setup rate.