One of the essential concerns of Internet of Things (IoT) is in industrial systems or data architecture to support the evolutions in transportation and logistics. Considering the Industrial IoT (IIoT) openness, the need for accessibility, availability, and searching of data has rapidly increased. The primary purpose of this research is to propose an Efficient Two-Dimensional Filter (ETDF) to store multimedia data of IIoT applications in a specific format to achieve faster response and dynamic updating. This filter consists of a two-dimensional array and a hash function integrated into a cuckoo filter for efficient use of memory. This study evaluates the scalability of the filter by increasing the number of requests from 10,000 to 100,000. To assess the performance of the proposed filter, we measure the parameters of access time and lookup message latency. The results show that the proposed filter improves the access time by 12%, compared to a Fast Two-Dimensional Filter (FTDF). Moreover, it improves memory usage by 20% compared to FTDF. Experiments indicate a better access time of the proposed filter compared to other filters (i.e., Bloom, quotient, cuckoo, and FTD filters). Insertion and deletion times are essential parameters in comparing filters, so they are also analyzed.

中文翻译：

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一种低内存占用的工业物联网多媒体数据高效过滤器

物联网 (IoT) 的基本问题之一是工业系统或数据架构，以支持运输和物流的发展。考虑到工业物联网 (IIoT) 的开放性，对数据的可访问性、可用性和搜索的需求迅速增加。本研究的主要目的是提出一种高效的二维滤波器 (ETDF)，以特定格式存储 IIoT 应用程序的多媒体数据，以实现更快的响应和动态更新。该过滤器由一个二维数组和一个集成到布谷鸟过滤器中的哈希函数组成，以有效利用内存。本研究通过将请求数从 10,000 增加到 100,000 来评估过滤器的可扩展性。为了评估所提出的过滤器的性能，我们测量访问时间和查找消息延迟的参数。结果表明，与快速二维过滤器 (FTDF) 相比，所提出的过滤器将访问时间提高了 12%。此外，与 FTDF 相比，它的内存使用率提高了 20%。实验表明，与其他过滤器（即布隆、商、布谷鸟和 FTD 过滤器）相比，所提出的过滤器具有更好的访问时间。插入和删除时间是比较过滤器的基本参数，因此也进行了分析。