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A multi-dimensional fairness combinatorial double-sided auction model in cloud environment

机译:云环境下的多维公平组合双面拍卖模型

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In cloud investment markets, consumers are looking for the lowest cost and a desirable fairness while providers are looking for strategies to achieve the highest possible profit and return. Most existing models for auction-based resource allocation in cloud environments only consider the overall profit increase and ignore the profit of each participant individually or the difference between the rich and the poor participants. This paper proposes a multi-dimensional fairness combinatorial double auction (MDFCDA) model which strikes a balance between the revenue and the fairness among participants. We solve a winner determination problem (WDP) through integer programming which incorporates the fairness attribute based on the history of participants which is stored in a repository. Our evaluation results show that the proposed model increases the willingness of participants to take part in the next auction rounds. Moreover the average percentage of resources utilization is increased.
机译:在云投资市场中,消费者寻求最低的成本和理想的公平性,而提供商则寻求实现最大可能的利润和回报的策略。在云环境中,大多数现有的基于拍卖的资源分配模型仅考虑总体利润增长,而忽略了每个参与者的利润或富人与穷人之间的差异。本文提出了一种多维公平组合双拍卖(MDFC​​DA)模型,该模型在收益与参与者之间的公平之间取得了平衡。我们通过整数编程解决赢家确定问题(WDP),该编程基于存储在存储库中的参与者的历史记录合并了公平属性。我们的评估结果表明,该模型提高了参与者参加下一轮拍卖的意愿。而且,平均资源利用百分比增加了。

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