提出了一种面向工业无线网络的基于数据收集成本优化的聚合点选择算法(Optimal Aggregation Point Selection algorithm,OAPS),该算法把网络的聚合点选择问题归结为图论中的选址问题.问题的解可以使聚合点的选择适应网络结构的动态变化,大大降低了数据收集成本并使传输更可靠.仿真分析表明,与无聚合的数据收集方法相比,OAPS可以使数据收集成本降低50%.
This paper proposes an optimal aggregation point selection (OAPS) algorithm based on cost of data collection for industrial wireless networks, which regards aggregation point selection as a location problem in graph theory. The solution to the problem enables the selection of aggregation points to well adapt to dynamic change of the network structure, and can dramatically reduce the communication cost and enhances the transmission reliability. Preliminary simulation results show that the OAPS algorithm efficiently reduces the data-collection cost by nearly 50% compared with other data collection methods without aggregation.