Spawn: A Distributed Computational Economy
IEEE Transactions on Software Engineering
Optimal solutions for multi-unit combinatorial auctions: branch and bound heuristics
Proceedings of the 2nd ACM conference on Electronic commerce
An Algorithm for Multi-Unit Combinatorial Auctions
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Mariposa: a wide-area distributed database system
The VLDB Journal — The International Journal on Very Large Data Bases
Matchmaking: Distributed Resource Management for High Throughput Computing
HPDC '98 Proceedings of the 7th IEEE International Symposium on High Performance Distributed Computing
An algorithm for optimal winner determination in combinatorial auctions
IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
A taxonomy of market-based resource management systems for utility-driven cluster computing
Software—Practice & Experience
Reverse combinatorial auction-based protocols for resource selection in grids
International Journal of Grid and Utility Computing
Pricing the resource in computational market based on Bayes-game model
ACOS'06 Proceedings of the 5th WSEAS international conference on Applied computer science
The computon in computing grid
SMO'05 Proceedings of the 5th WSEAS international conference on Simulation, modelling and optimization
Reverse auction-based grid resources allocation
PRIMA'06 Proceedings of the 9th Pacific Rim international conference on Agent Computing and Multi-Agent Systems
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In this paper, we present the overall design for an auctioning based resource trading/acquiring system that can be deployed in wide-area computing systems such as Grid systems. Selecting the winning bids is one of the core issues in any system that utilizes the auctioning paradigm. We identify the unique aspects of our system that impact the winner selection process. More specifically, the necessity to acquire or trade resources as a bundle (i.e., perform co-allocation) presents a challenge to traditional bidding mechanisms. We present a new bidding mechanism called "co-bids" to address this problem. Two heuristics for winner selection with co-bids are proposed. The performance of the heuristics are examined via simulations.