基于组合双向拍卖的物联网搜索任务分配机制

Combinatorial double auction-based allocation of retrieval tasks in Internet of Things

如何合理地分配搜索任务,进而激励用户加入到搜索中是物联网搜索亟需解决的关键问题。针对物联网中数据实效性强的特点,结合物联网搜索中用户的高异构性和动态性,提出一种基于组合双向拍卖的搜索任务分配模型,从市场供求关系的角度描述了搜索发起者、搜索参与者和搜索引擎之间的关系。首先引入了竞价价值的概念,提出了一种基于贪心策略的启发式算法确定竞拍成功的用户集合,然后提出一种基于临界价格的定价算法,确保用户的竞价反映了其真实估价。理论分析及实验结果证明所提任务分配机制在保证激励相容性、合理性的基础上,有效提高了物联网搜索引擎的效率。

Task allocation mechanism was greatly important to the success of the search service in Internet of Things（Io T）. On basis of analyzing the real time characteristics of the Io T data, and the dynamic characteristics of the users, a combinatorial double auction-based retrieval tasks allocation model was introduced, which described the relationships between the workers, the requesters and the system from the perspective of supply and demand. Firstly, a novel metric to evaluate the value of the users＇ queries was introduced and a greedy heuristic algorithm to determine the winning requesters and workers was proposed. Then, a critical payment scheme was proposed, which guaranteed that submitted bids of the users reflect their real value. Finally, both the rigid theoretical analysis and simulation result show that the proposed mechanism achieves truthfulness, individual rationality and the efficiency of the service provider is improved.