Real-time Pricing-based Resource Allocation in Open Market Environments

被引:0
|
作者
Mishra, Pankaj [1 ,2 ]
Moustafa, Ahmed [1 ]
Ito, Takayuki [3 ]
机构
[1] Nagoya Inst Technol, Nagoya, Aichi 4668555, Japan
[2] Univ Wollongong, Wollongong, NSW, Australia
[3] Kyoto Univ, Kyoto 6068501, Japan
关键词
Open market environments; resource allocation; reinforcement learning; real-time pricing; AUCTION MECHANISM;
D O I
10.1145/3465237
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Open market environments consist of a set of participants (vendors and consumers) that dynamically leave or join the market. As a result, the arising dynamism leads to uncertainties in supply and demand of the resources in these open markets. In specific, in such uncertain markets, vendors attempt to maximise their revenue by dynamically changing their selling prices according to the market demand. In this regard, an optimal resource allocation approach becomes immensely needed to optimise the selling prices based on the supply and demand of the resources in the open market. Therefore, optimal selling prices should maximise the revenue of vendors while protecting the utility of buyers. In this context, we propose a real-time pricing approach for resource allocation in open market environments. The proposed approach introduces a priority-based fairness mechanism to allocate the available resources in a reverse-auction paradigm. Finally, we compare the proposed approach with two state-of-the-art resource allocation approaches. The experimental results show that the proposed approach outperforms the other two resource allocation approaches in its ability to maximise the vendors ' revenue.
引用
收藏
页数:22
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