• Journal of Electrical Engineering and Technology
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• v.4 no.1
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• pp.49-54
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• 2009

One of the major challenges confronting a multiservice electric utility is the establishment of the right prices for its services. The key objectives of particular pricing schemes are reasonableness of company earnings, economic efficiency, the responsiveness of supply and of the allocation of sources to the desires of consumers, and maintenance of some degree of competition. This paper proposes a value-based pricing mechanism amenable to the current deregulation situation in electricity market allowing service differentiation. The proposed pricing mechanism can be implemented in a nodal auction model, and can also be applied to direct load control.

• Management Science and Financial Engineering
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• v.2 no.1
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• pp.19-51
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• 1996

We suggest a distributed framework for task assignment in the computer-controlled shop floor where each of the resource agents and part agents acts like an independent profit maker. The job allocation problem is formulated as a linear programming problem. The LP formulation is analyzed to provide a rationale for the distributed task assignment procedure. We suggest an auction based negotiation procedure including a price-based bid construction and a price revising mechanism. The performance of the suggested procedure is compared with those of an LP formulation and conventional dispatching procedures by simulation experiments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.9
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• pp.1802-1807
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• 2015

The cloud computing service provides physical IT resources to VM instances to users using virtual technique and the users pay cost of VM instances to service provider. The auction model based on cloud computing provides available resources of service provider to users through auction mechanism. The users bid spot instances to process their a job until its deadline time. If the bidding price of users is higher than the spot price, the user will be provided the spot instances by service provider. In this paper, we propose a new bidding strategy to minimize the total cost for job completion. Typically, the users propose bidding price as high as possible to get the spot instances and the spot price get high. we lower the spot price using proposed strategy and minimize the total cost for job completion. To evaluate the performance of our strategy, we compare the spot price and the total cost for job completion with real workload data.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.73-77
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• 2001

In this paper, we propose a virtual action system based on information agents, We call the system the MultiHammer, MultiHammer can be used for studying and analyzing online actions. MuiltiHammer provides functions of implement-ing a meta online action site and an experiment environ-ment. We have been using MultiHammer as an experiment as an experiment environment for BiddinBot. BiddingBot aims at assisting users to bid simultaneously in multiple online auctions. In order to bid simultaneously in multiple online auctions. In order to analyze the behavior of BiddngBot, we need to pur-chase a lot of items. It is hard for us to prepare a lot of fund to show usability and advantage of BiddingBot. MultiHam-mer enables us to effectively analyze the behavior of BiddingBot. MultiHammer consists of three types of agents for information collecting data storing and auctioning. Agents for information wrappers. To make agent work as wrarp-pers, we heed to realize software modules for each online action site. Implementing these modules reguires a lot of time and patience. To address this problem, we designed a support mechanism for developing the modules. Agents for data storing record the data gathered by agents for informa-tion collecting. Agents for auctioning provide online services using data recorded by agents for data storing. By recording the activities in auction sites. MultiHammer can recreate any situation and trace auction for experimentation, Users can participate in virtual using the same information in real online auctions. Users also participate in real auc-tions via wrapper agents for information collecting

• Journal of the Korean Society for Railway
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• v.15 no.5
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• pp.524-530
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• 2012

Recently, open access policy to railway operation has been widely discussed. Compared to the case of Korea, European countries have dealt with this topic over a few decades. The competition on railway slots incurs an important technological problem about how to optimally allocate railway slots requested from RUs to them. In other words, the authority should be able to coordinate the timetables requested from RUs in the non-discriminatory manner. Related with the coordination, compared to the other European countries, which have done many studies and experiments especially on auction mechanisms, Korean railway has paid less attention to this topic and there have not been any related studies. Our study analyses the state-of-the-arts about the railway slot allocation especially focusing on the auction mechanisms and the associated optimization problems. And we suggest a new railway slot allocation mechanism and related optimization model reflecting the adjustment within the tolerance and the operational policies between railway undertakings.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3638-3657
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• 2022

In urban vehicular edge computing (VEC) environments, one edge server always serves many task requests in its coverage which results in the resource-constrained problem. To resolve the problem and improve system utilization, we first design a general hierarchical resource management framework based on typical VEC network structures. Following the framework, a specific interacting protocol is also designed for our decision algorithm. Secondly, a greedy bidding-based multi-hop task scheduling decision algorithm is proposed to realize effective task scheduling in resource-constrained VEC environments. In this algorithm, the goal of maximizing system utility is modeled as an optimization problem with the constraints of task deadlines and available computing resources. Then, an auction mechanism named greedy bidding is used to match task requests to edge servers in the case of multiple hops to maximize the system utility. Simulation results show that our proposal can maximize the number of tasks served in resource constrained VEC networks and improve the system utility.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1638-1654
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• 2018

The heterogeneous network (HetNet) has been one of the key technologies in Long Term Evolution-Advanced (LTE-A) with growing capacity and coverage demands. However, the introduction of femtocells has brought serious co-layer interference and cross-layer interference, which has been a major factor affecting system throughput. It is generally acknowledged that the resource allocation has significant impact on suppressing interference and improving the system performance. In this paper, we propose a hybrid-clustering algorithm based on the $Mat{\acute{e}}rn$ hard-core process (MHP) to restrain two kinds of co-channel interference in the HetNet. As the impracticality of the hexagonal grid model and the homogeneous Poisson point process model whose points distribute completely randomly to establish the system model. The HetNet model based on the MHP is adopted to satisfy the negative correlation distribution of base stations in this paper. Base on the system model, the spectrum sharing problem with restricted spectrum resources is further analyzed. On the basis of location information and the interference relation of base stations, a hybrid clustering method, which takes into accounts the fairness of two types of base stations is firstly proposed. Then, auction mechanism is discussed to achieve the spectrum sharing inside each cluster, avoiding the spectrum resource waste. Through combining the clustering theory and auction mechanism, the proposed novel algorithm can be applied to restrain the cross-layer interference and co-layer interference of HetNet, which has a high density of base stations. Simulation results show that spectral efficiency and system throughput increase to a certain degree.

• Journal of Communications and Networks
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• v.12 no.2
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• pp.114-121
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• 2010

In this paper, an auctioning strategy is proposed for cellular networks that ensures net energy savings. The pricing scheme, in conjunction with a two dimensional bid structure, incentivizes cooperation at the terminal nodes for better interference management at receivers and for cooperative relaying. It is shown that, for the proposed auctioning strategy, network operators are guaranteed revenue gains, mobile nodes' dominant strategy is to bid their true valuation of their energy resources, and overall effective energy gains occur under the assumption of a reserve price for bidding. Simulation results show that significant energy savings can be achieved by employing this auctioning mechanism for a 3G cellular set-up.

• Journal of Climate Change Research
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• v.9 no.4
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• pp.325-342
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• 2018

The Korea Emissions Trading Scheme ( K-ETS), which manages roughly 70% of the greenhouse gas emissions in South Korea, was initiated in 2015, after implementation of its 1st basic plan and the 1st allocation plan (2014) for the 1st phase (2015-2017). During the three and a half years since the launch of K-ETS, there have been critical policy change such as adjustment of the institutions involved, development and revision of the 2030 national GHG reduction roadmap, and change in the allocation plans. Moreover, lack of liquidity and fluctuation of carbon prices in the K-ETS market during this period has forced the Korean government to adjust the flexibility mechanism and auction permits of the market stability reserve. To evaluate the policy change in the K-ETS regarding conformance to its objectives, this study defines three objectives (Environmental Effectiveness, Cost Effectiveness and Economic Efficiency) and ten indicators. Evaluation of Environmental Effectiveness of K-ETS suggests that the national GHG reduction roadmap, coverage of GHG emitters and credibility of MRV positively affect GHG mitigation. However, there was a negative policy change implemented in 2017 that weakened the emission cap during the 1st phase. In terms of the Cost Effectiveness, the K-ETS policies related to market management and flexibility mechanism (e.g. banking, borrowing and offsets) were improved to deal with the liquidity shortage and permit price increase, which were caused by policy uncertainty and conservative behavior of firms during 2016-2018. Regarding Economic Efficiency, K-ETS expands benchmark?based allocation and began auction-based allocation; nevertheless, free allocation is being applied to sectors with high carbon leakage risk during the 2nd phase (2018-2020). As a result, it is worth evaluating the K-ETS policies that have been developed with respect to the three main objectives of ETS, considering the trial?and?error approach that has been followed since 2015. This study suggests that K-ETS policy should be modified to strengthen the emission cap, stabilize the market, expand auction-based allocation and build K-ETS specified funds during the 3rd phase (2021-2025).

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.9
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• pp.263-272
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• 2023

Industrial Internet of Things (IIoT) is an important factor in increasing production efficiency in industrial sectors, along with data collection, exchange and analysis through large-scale connectivity. However, as traffic increases explosively due to the recent spread of IIoT, an allocation method that can efficiently process traffic is required. In this thesis, I propose a two-stage task offloading decision method to increase successful task throughput in an IIoT environment. In addition, I consider a hybrid offloading system that can offload compute-intensive tasks to a mobile edge computing server via a cellular link or to a nearby IIoT device via a Device to Device (D2D) link. The first stage is to design an incentive mechanism to prevent devices participating in task offloading from acting selfishly and giving difficulties in improving task throughput. Among the mechanism design, McAfee's mechanism is used to control the selfish behavior of the devices that process the task and to increase the overall system throughput. After that, in stage 2, I propose a multi-armed bandit (MAB)-based task offloading decision method in a non-stationary environment by considering the irregular movement of the IIoT device. Experimental results show that the proposed method can obtain better performance in terms of overall system throughput, communication failure rate and regret compared to other existing methods.