Statistical data for QoS-enabled IoT network with Poisson and Beta Distribution

This dataset comprises a range of features, including time slots, device IDs, geographic coordinates (x, y), energy consumption, uplink history, emergency status, QoS pool identifiers, data flags, resource IDs, and data sizes. The device locations are modeled using a Poisson distribution with a spread of \(100\) meters within a \(500 \times 500\) meter area. The uplink history, QoS pool assignments, and data flags are derived from the probabilities of data availability and priority values. To construct two distinct datasets, we applied a beta distribution to model the probability of data availability and priority levels, allowing for variations in uplink traffic patterns. The normal traffic dataset exhibits a balanced and mixed access pattern, featuring equal representation of all four device types. Our dataset is statistically reproducible and is available for access via the provided link. Together with our proposed system, these datasets serve as a robust benchmark for future research endeavors.

本数据集包含多类特征，其时隙、设备标识符（device IDs）、地理坐标（x, y）、能耗、上行链路历史、紧急状态、QoS池标识符（QoS pool identifiers）、数据标记（data flags）、资源标识符（resource IDs）与数据量均涵盖其中。设备位置采用泊松分布（Poisson distribution）建模，在500×500米的区域内，空间分布跨度为100米。上行链路历史、QoS池分配与数据标记均基于数据可用性概率与优先级取值生成。为构建两类差异化数据集，我们采用贝塔分布（beta distribution）对数据可用性概率与优先级等级进行建模，以此实现上行流量模式的多样化。正常流量数据集呈现均衡且混合的接入模式，四类设备类型的样本占比均等。本数据集具备统计可复现性，可通过指定链接获取。结合我们提出的系统，此类数据集可作为未来研究工作的可靠基准测试集。