• Journal of KIISE:Information Networking
• /
• v.33 no.2
• /
• pp.183-192
• /
• 2006

This paper analyzes the price-selection problem under priority-based scheduling for QoS (Quality of Service) network services, i.e., how to determine the price associated with each service level. In particular, we focus on the problems with the pricing mechanism based on equilibrium analysis. We claim that the assumptions needed to produce equilibrium nay not hold in some important environments. Specifically, (a) the individual user's impact on the system is not infinitesimal and (b) users do not always have up-to-date global system-status knowledge crucial for optimal user decisions required for equilibrium. These may make the equilibrium models inaccurate in realistic environments. We examine the accuracy of some existing equilibrium methods by using a dynamic model that we have developed for system behavior analysis. The analysis indicates that equilibrium methods fail to model accurately the system behavior in some realistic environments.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.10
• /
• pp.4748-4765
• /
• 2016

We consider a virtualized cognitive radio (CR) network, where multiple virtual network operators (VNOs) who own different virtual cognitive base stations (VCBSs) share the same physical CBS (PCBS) which is owned by an infrastructure provider (InP), sharing the spectrum with the primary user (PU). The uplink scenario is considered where the secondary users (SUs) transmit to the VCBSs. The PU is protected by constraining the interference power from the SUs. Such constraint is applied by the InP through pricing the interference. A Stackelberg game is formulated to jointly maximize the revenue of the InP and the individual utilities of the VNOs, and then the Stackelberg equilibrium is investigated. Specifically, the optimal interference price and channel allocation for the VNOs to maximize the revenue of the InP and the optimal power allocation for the SUs to maximize the individual utilities of the VNOs are derived. In addition, a low‐complexity ±‐optimal solution is also proposed for obtaining the interference price and channel allocation for the VNOs. Simulations are provided to verify the proposed strategies. It is shown that the proposed strategies are effective in resource allocation and the ±‐optimal strategy achieves practically the same performance as the optimal strategy can achieve. It is also shown that the InP will not benefit from a large interference power limit, and selecting VNOs with higher unit rate utility gain to share the resources of the InP is beneficial to both the InP and the VNOs.

• Journal of the Korea Convergence Society
• /
• v.12 no.8
• /
• pp.47-53
• /
• 2021

With increasing interest in the 4th industrial revolution, data-driven scientific methodologies have developed. However, there are limitations of data collection in the real estate field of research. In addition, as the public becomes more knowledgeable about the real estate market, the qualitative sentiment comes to play a bigger role in the real estate market. Therefore, we propose a method to collect quantitative data that reflects sentiment using text mining and k-means algorithms, rather than the existing source data, and to predict the direction of housing index through artificial neural network learning based on the collected data. Data from 2012 to 2019 is set as the training period and 2020 as the prediction period. It is expected that this study will contribute to the utilization of scientific methods such as artificial neural networks rather than the use of the classical methodology for real estate market participants in their decision making process.

• Journal of Digital Convergence
• /
• v.10 no.1
• /
• pp.49-57
• /
• 2012

The Internet succeeded because of the end-to-end principle which allowed anyone to add functionality to the network. However, as the internet is increasingly becoming the platform for smart IT applications such as VoIP, IPTV, Cloud Computing and Smart Phone, networks are now under increasing strain of traffic congestion and the absence of quality of service insurances. To date, the debate over internet rules has focused on network neutrality rather than network efficiency. This article emphasizes the well-functioning role of market mechanism for the efficient use and further development of the network. To maximize the value of the network, this article proposes a differential treatment to packets based on customer types, and a two-part tariff pricing rule to secure funding to expand and upgrade networks.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.31 no.4
• /
• pp.105-123
• /
• 2006

Previous research on two-sided markets has, for the most part, concentrated on indirect network externalities between buyers alto sellers. This paper considers direct competition effect among sellers and among buyers as well as indirect network externalities. We develop an analytic model of C2C e-marketplaces and examine whether a monopolistic incumbent could successfully deter new entry into its market. We find that the effect of the number of sellers or buyers on the price of goods depends on whether sellers have decided to sell the goods using an auction or fixed pricing rule and on the characteristics of the goods. We argue that when the effect of the number of sellers on the price of goods is significantly larger than that of buyers, there is a high possibility of entry. In particular, we show that entry becomes more difficult to deter as fixed-price format is adopted more frequently or the proportion of collectables is relatively low.

• Journal of Electrical Engineering and Technology
• /
• v.12 no.6
• /
• pp.2196-2207
• /
• 2017

This paper presents a two-stage market auction model in a pool-based electricity market, which explicitly takes into account the system network security. The security network-constrained market auction model considers the use of corrective control to yield economically efficient actions in the post-contingency state, while ensuring a certain security level. Under this framework, the proposed model shows not only for quantifying the correlation between secure system operation and efficient market operation, but also for providing transparent information on the pricing system security for market participants. The two-stage market auction procedure is formulated using Benders decomposition (BD). In the first stage, the market participants bid in the market for maximizing their profit, and the independent system operator (ISO) clears the market based on social welfare maximization. System network constraints incorporating post-contingency control actions are described in the second stage of the market auction procedure. The market solutions, along with the BD, yield nodal spot prices (NSPs) and nodal congestion prices (NCPs) as byproducts of the proposed two-stage market auction model. Two benchmark systems are used to test and demonstrate the effectiveness of the proposed model.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.40 no.1
• /
• pp.105-113
• /
• 2017

Network externality can be defined as the effect that one user of a good or service has on the value of that product to other people. When a network externality is present, the value of a product or service is dependent on the number of others using it. There exist asymmetries in network externalities between the online and traditional offline marketing channels. Technological capabilities such as interactivity and real-time communications enable the creation of virtual communities. These user communities generate significant direct as well as indirect network externalities by creating added value through user ratings, reviews and feedback, which contributes to eliminate consumers' concern for buying products without the experience of 'touch and feel'. The offline channel offers much less scope for such community building, and consequently, almost no possibility for the creation of network externality. In this study, we analyze the effect of network externality on the competition between online and conventional offline marketing channels using game theory. To do this, we first set up a two-period game model to represent the competition between online and offline marketing channels under network externalities. Numerical analysis of the Nash equilibrium solutions of the game showed that the pricing strategies of online and offline channels heavily depend not only on the strength of network externality but on the relative efficiency of online channel. When the relative efficiency of online channel is high, the online channel can greatly benefit by the network externality. On the other hand, if the relative efficiency of online channel is low, the online channel may not benefit at all by the network externality.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.41 no.1
• /
• pp.92-100
• /
• 2016

It is informed that the Voice over LTE(VoLTE) which serves voice and message on IP networks is better in terms of economies of scale than the legacy voice service on 2G/3G circuit-switched networks because of its technological and cost efficiency. In addition, services of voice and data are running on a single LTE network and as a result VoLTE has the more economies of scope. But, there is no study about how much technology-efficiency VoLTE has compared to circuit-based voice service and how much voice charge can be reduced as VoLTE grows up. This paper analyzes empirically cost-efficiency of VoLTE against circuit-based voice service and quantifies the reduction of voice charge as 2G/3G voice traffic shifts to VoLTE. The results describe the first is that the average cost of the total voice traffic rises shortly just after the investment of LTE network for providing VoLTE but it will soon have a capacity available to reduce the charge due to VoLTE's outstanding cost efficiency on the assumption that voice traffic is fixed, and the second is that the charge can be cut to 60% of the current rate in case of all the voice traffic moves to VoLTE. The latter proves partially the validation of data-focusing pricing plan. Our results are expected to become basic data for network operators' establishing pricing strategies and for policy makers' inducing price cutting.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.22 no.4
• /
• pp.228-234
• /
• 2021

Real estate market participants need to have a sense of predicting real estate prices in decision-making. Commonly used methodologies, such as regression analysis, ARIMA, and VAR, have limitations in predicting the value of an asset, which fluctuates due to unknown variables. Therefore, to mitigate the limitations, an artificial neural was is used to predict the price trend of apartments in Seoul, the hottest real estate market in South Korea. For artificial neural network learning, the learning model is designed with 12 variables, which are divided into macro and micro factors. The study was conducted in three ways: (Ed note: What is the difference between case 1 and 2? Is case 1 micro factors?)CASE1 with macro factors, CASE2 with macro factors, and CASE3 with the combination of both factors. As a result, CASE1 and CASE2 show 87.5% predictive accuracy during the two-year experiment, and CASE3 shows 95.8%. This study defines various factors affecting apartment prices in macro and microscopic terms. The study also proposes an artificial network technique in predicting the price trend of apartments and analyzes its effectiveness. Therefore, it is expected that the recently developed learning technique can be applied to the real estate industry, enabling more efficient decision-making by market participants.

• Korean Management Science Review
• /
• v.33 no.3
• /
• pp.19-30
• /
• 2016

This study provides a framework to assess network design under the regime of QoE (Quality of Experience). Our approach is expected to reveal the necessity of developing the QoE measures and applying this notion to network design, particularly in the mobile environment. Furthermore, our model shows the ample potential that both users and network providers are able to attain a win-win case by shifting the focus on network design and service operations from QoS (Quality of Service) to QoE. Since the former considers only relevant technological specifications, it may fail in capturing critical factors surrounding users, such as a context where the corresponding user is working on. For example, according to one study [13], the bit-rate, a widely employed QoS measure, shows inferior performance in provisioning network resources to the MOS (Mean Opinion Score), a representative QoE measure. Our framework develops the idea and construct a prototype to systematically assess network design and operations in terms of QoE. The proposed prototype aims at achieving a higher level of efficiency without severely deteriorating users' satisfaction level. We also provide some simulation results which support our idea. That is, reducing the chance of over-provisioning on the basis of the QoE paradigm results in a great flexibility. It may give price cut for users or postponement of network investment for providers or both. Our simulation results also seem robust irrespective of the forms of the QoS-QoE relationship.