A hybrid IoT traffic generator for mobile network performance assessment

摘要

Internet of Things (IoT) technology is the key enabler of the future with a massive number of connected devices. With the evolution of Machine Type Communications (MTC), the number of MTC devices in mobile networks is increasing rapidly to support IoT services. The massive number of short and bursty sessions introduced by MTC devices may result in congestion and system overload impacting human to human (H2H) communications in mobile networks. To study the overall network performance for the future scenarios to come, a flexible traffic model based on practical data is necessary. Unfortunately, scalable and realistic MTC traffic data is inaccessible in most cases. In this work, we propose a hybrid traffic framework by integrating open big data and MTC traffic models. The generated MTC traffic is based on geo-referenced H2H activities and can be used to help assessing mobile network performance.