摘要
为有效降低视频服务商成本开销和提高服务质量,研究当前业界流行的资源交易模型,构建一种适用于流媒体资源交易的拍卖模型(SMRTM)。由于模型中资源组合交易问题为NP-hard问题,计算复杂度高,通过把多种资源加权为综合满意度,将资源组合交易问题转化为图论中求解二分图最大权匹配问题,基于二分图设计一种资源组合交易算法(RPTA),RPTA在满足市场需求的情况下实现最大化满意度交易匹配,提高交易的收益。验证了算法的可行性、有效性。
To reduce effectively the service cost of video operators and improve the quality of service,a streaming media resource transactions model(SMRTM)was proposed by studying the current popular resource transaction model in the industry.However,the resource combination transaction problem in the model is an NP-hard problem that cannot be solved in polynomial time.Therefore,by weighting multiple resources into comprehensive satisfaction,the resource combination transaction problem was transformed into the bipartite graph maximum weight matching problem.A resource portfolio trading algorithm(RPTA)was designed based on the bipartite graph.Under the condition of meeting the market demand,the maximum satisfaction transaction matching was realized and the profit of the transaction was improved.The feasibility and effectiveness of the algorithm are verified by numerical experiment.
作者
薛杨上
李泽平
陈仁康
XUE Yang-shang;LI Ze-ping;CHEN Ren-kang(College of Computer Science and Technology,Guizhou University,Guiyang 550025,China)
出处
《计算机工程与设计》
北大核心
2022年第1期57-65,共9页
Computer Engineering and Design
基金
国家自然科学基金项目(61462014)。