• Information Systems Review
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• v.8 no.2
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• pp.103-117
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• 2006

As the interest in the combinatorial auction has increased, diverse combinatorial auction market types have been proposed. Although there have been several studies on the combinatorial auction design, the studies covered some factors or partial dimensions of combinatorial auction design. Given the potential practical value of combinatorial auctions, it is necessary to approach it with an integrated and systematic design methodology for supporting a comprehensive range of combinatorial auction models. Thus, we present a systematic framework for combinatorial auction design methodology. In particular, we classified the combinatorial auction architecture types, process types, and mechanism types. This framework characterizes the different combinatorial auction models, and lead to a useful taxonomy of the combinatorial auction design factors and taxonomy of the market types by coordination among the design factors. In addition, we illustrate an n-bilateral combinatorial auction market, derived from our design methodology, to show the viability of our study.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.11a
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• pp.379-390
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• 2005

In this paper, we introduce a new combinatorial auction mechanism - N-Bilateral Optimized Combinatorial Auction (N-BOCA). N-BOCA is a flexible iterative combinatorial auction model that offers optimized trading for multi-suppliers and multi-purchasers in the supply chain. We design the N-BOCA system from the perspectives of architecture, protocol, and trading strategy. Under the given N-BOCA architecture and protocol, auctioneers and bidders have diverse decision strategies for winner determination. This needs flexible modeling environments. Hence, we propose an optimization modeling agent for bid and auctioneer selection. The agent has the capability to automatic model formulation for Integer Programming modeling. Finally, we show the viability of N-BOCA through prototype and experiments. The results say both higher allocation efficiency and effectiveness compared with I-to-N general combinatorial auction mechanisms.

• Journal of Intelligence and Information Systems
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• v.12 no.1
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• pp.139-161
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• 2006

In this paper, we introduce a new combinatorial auction mechanism - N-Bilateral Optimized Combinatorial Auction (N-BOCA). N-BOCA is a flexible iterative combinatorial auction model that offers optimized trading for multi-suppliers and multi-purchasers in the supply chain. We design the N-BOCA system from the perspectives of architecture, protocol, and trading strategy. Under the given N-BOCA architecture and protocol, auctioneers and bidders have diverse decision strategies f3r winner determination. This needs flexible modeling environments. Hence, we propose an optimization modeling agent for bid and auctioneer selection. The agent has the capability to automatic model formulation for Integer Programming modeling. Finally, we show the viability of N-BOCA through prototype and experiments. The results say both higher allocation efficiency and effectiveness compared with 1-to-N general combinatorial auction mechanisms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.9
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• pp.4197-4219
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• 2017

Cloud computing is a new service to provide dynamic, scalable virtual resource services via the Internet. Cloud market is available to multiple cloud computing resource providers and users communicate with each other and participate in market transactions. However, since cloud computing is facing with more and more security issues, how to complete the allocation process effectively and securely become a problem urgently to be solved. In this paper, we firstly analyze the cloud resource allocation problem and propose a mathematic model based on combinatorial double auction. Secondly, we introduce a trust evaluation mechanism into our model and combine genetic algorithm with simulated annealing algorithm to increase the efficiency and security of cloud service. Finally, by doing the overall simulation, we prove that our model is highly effective in the allocation of cloud resources.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.6
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• pp.2811-2830
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• 2017

In this paper, we study the problem of mobile data offloading for a network that contains multiple mobile network operators (MNOs), multiple WiFi or femtocell access points (APs) and multiple mobile users (MUs). MNOs offload their subscribed MUs' data traffic by leasing the unused Internet connection bandwidth of third party APs. We propose a combinatorial auction-based two-stage matching mechanism comprised of MU-AP matching and AP-MNO matching. The MU-AP matching is designed to match the MUs to APs in order to maximize the total offloading data traffic and achieve better MU satisfaction. Conversely, for AP-MNO matching, MNOs compete for APs' service using the Nash bargaining solution (NBS) and the Vickrey auction theories and, in turn, APs will receive monetary compensation. We demonstrated that the proposed mechanism converges to a distributed stable matching result. Numerical results demonstrate that the proposed algorithm well capture the tradeoff among the total data traffic, social welfare and the QoS of MUs compared to other schemes. Moreover, the proposed mechanism can considerably offload the total data traffic and improve the network social welfare with less computation complexity and communication overhead.

• ETRI Journal
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• v.32 no.4
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• pp.634-637
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• 2010

This letter presents a model for a dynamic collaboration (DC) platform among cloud providers (CPs) that prevents adverse business impacts, cloud vendor lock-in and violation of service level agreements with consumers, and also offers collaborative cloud services to consumers. We consider two major challenges. The first challenge is to find an appropriate market model in order to enable the DC platform. The second is to select suitable collaborative partners to provide services. We propose a novel combinatorial auction-based cloud market model that enables a DC platform among CPs. We also propose a new promising multi-objective optimization model to quantitatively evaluate the partners. Simulation experiments were conducted to verify both of the proposed models.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10d
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• pp.283-285
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• 2002

조합 경매는 구매자들이 원하는 상품들을 조합해서 입찰할 수 있는 경매다. 그러나 판매자의 이익을 최대로 하는 승자를 결정하는 문제는 NP-complete이다. 분기 한정법(branch and bound)을 사용해서 최적의 승자를 찾을 때, 어떤 비드(bid)를 선택해서 분기할 것인가를 결정해야 한다. 이 때, 비드를 선택하는 휴리스틱이 분기 한정법의 성능을 결정하는 중요한 역할을 한다. 본 논문에서는 조합경매의 승자를 결정하기 위해서 분기 한정법과 Linear Programming을 사용할 때, 분기할 비드와 충돌하는 비드들을 동시에 고려하는 비드 선택 휴리스틱을 제안한다. 실험을 통해서 제시하는 휴리스틱의 성능이 우수함을 보였다.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.9
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• pp.477-486
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• 2003

In combinatorial auctions buyers nay bid for arbitrary combinations of goods. But determining the winners of combinatorial auctions who maximize the profit of a seller is known to be NP-complete. A branch-and-bound method can be one of practical algorithm for winner determination. However, bid selection heuristics play a very important role in the efficiency of a branch-and-bound method. In this paper, we designed and implemented an algorithm which used a branch-and-bound method and Linear Programming for winner determination in combinatorial auctions. We propose new bid selection heuristics which consider a branching bid and conflicting bids simultaneously to select a branching bid in the algorithm. In addition, upper bounds are reused to reduce the running time in specific cases. We evaluated the performance of the algorithm by experiments with five data distributions and compared our method with others. The algorithm using heuristics showed a superior efficiency in two data distributions and a similar efficiency in three distributions.

• 한국IT서비스학회:학술대회논문집
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• 2003.05a
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• pp.577-583
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• 2003

Due to the widespread availability of the internet, large-scale and dynamic distributed projects in industry are becoming popular. We present a distributed, collaborative, and adaptive control approach for decentralized multiple projects, which is one of representative project environments in modern e-enterprises. In this paper we deal with short term scheduling and rescheduling of resources, which are shared by multiple projects. We in specific, address the dynamic nature of the situation. We model this as a dynamic economy, where the multiple local markets are established and cleared over time trading resource time slots(goods). Local markets are modeled using a combinatorial auction mechanism. Due to the dynamic and distributed nature of economy, through our approach we can achieve higher levels of flexibility, scalability and adaptability.

• Journal of Internet Computing and Services
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• v.11 no.5
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• pp.105-117
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• 2010

In recent years, dynamic collaboration (DC) among cloud providers (CPs) is becoming an inevitable approach for the widely use of cloud computing and to realize the greatest value of it. In our previous paper, we proposed a combinatorial auction (CA) based cloud market model called CACM that enables a DC platform among different CPs. The CACM model allows any CP to dynamically collaborate with suitable partner CPs to form a group before joining an auction and thus addresses the issue of conflicts minimization that may occur when negotiating among providers. But how to determine optimal group bidding prices, how to obtain the stability condition of the group and how to distribute the winning prices/profits among the group members in the CACM model have not been studied thoroughly. In this paper, we propose to formulate the above problems of cooperative negotiation in the CACM model as a bankruptcy game which is a special type of N-person cooperative game. The stability of the group is analyzed by using the concept of the core and the amount of allocationsto each member of the group is obtained by using Shapley value. Numerical results are presented to demonstrate the behaviors of the proposed approaches.