摘要
针对传感资源在云市场中实现交易共享的问题,提出传感资源的动态报价策略DPS-SR(Dynamic Pricing Strategy of Sensing Resource)和基于组合双向拍卖的稳定匹配算法CDA-SMA(Stable Matching Algorithm of Combinatorial Double Auction)。DPS-SR综合考虑了历史成交价格、市场供需情况、供应方资源负荷率和需求方焦急度给出合理的供需报价;CDA-SMA以供需双方偏好为导向实现双向稳定匹配。DPS-SR和CDA-SMA共同实现传感资源的动态定价,仿真实验结果显示在不同的市场供需情况下该定价策略比传统的固定比率定价有更好的适应性。
Aiming at the problem of sensor resources transaction sharing in the cloud market, a dynamic pricing strategy of sensing resource (DPS-SR) and a stable matching algorithm based on combinatorial double auction (CDA-SMA) are proposed. DPS-SR takes into account the historical transaction price, the market supply and demand situation, the supply side resource load ratio and the demand side anxious degree to give a reasonable supply and demand quotation; CDA-SMA achieves two-way stable matching based on both supply and demand preferences. DPS-SR and CDA-SMA are used to realize the dynamic pricing of sensor resources. The simulation results show that this pricing strategy has better adaptability than the traditional fixed-rate pricing in different market supply and demand situations.
出处
《计算机应用与软件》
2017年第4期125-130,134,共7页
Computer Applications and Software
基金
山东省计算机网络重点实验室开放课题基金项目(SDKLCN-2013-07)
关键词
传感数据资源
云资源共享
动态报价策略
组合双向拍卖
资源负荷率
Sensor data resource
Cloud resource sharing
Dynamic pricing strategy
Combinatorial double auction
Resource load ratio