網路通訊在近20年來的突飛猛進的發展，從寬頻網路到無線網路的普及，使得Human to Human (H2H) 通訊應用更加廣泛，同時也使得網路資源漸漸地飽和。在此同時另一種新興概念逐步也在慢慢崛起 "Machine to Machine (M2M)通訊"，意指不須透過人為操作，讓機器與機器之間透過網路溝通，因此亦稱為物聯網(Internet of Thing，IoT)。第三代合作夥伴計畫(Third Generation Partnership Project，3GPP)定義Machine Type Communication (MTC)為長期演進技術長期演進技術(Long-Term Evolution，LTE) 中M2M通訊標準。
本文提出一個混合式物聯網流量產生器，藉由大數據資料產生H2H流量與根據3GPP MTC流量模型所產生出的MTC流量，將混合式流量輸入行動網路中，以評估其行動網路效能。;In recent 20 years, Internet has rapidly evolved and Human to Human commucation has been used in wide range. This will result in a saturation of Ineternet resource. And there is another commuction type coming, machine-to-machine (M2M) communications, one of the latest research areas that has recently attracted much attention. It is one of the most promising technology for the future of cellular communications. The third Generati on Partnership Projects (3GPP) organization defines Machine Type Communications (MTC) to enhance support of M2M devices. MTC characteristic is MTC devices can communicate with each other MTC device, or with central severs via mobile network and the internet, thus forming so-called Internet of Things (IoT).
The application of MTC communication is rapidly increasing as it is becoming available for a large number of systems due to its increasing demand among cellular network operators.The MTC devices on LTE mobile networks rapidly increasing will overwhelm the network by the huge traffic load.
In this thesis, we proposes an hybrid IoT traffic generator,which use big data to generate H2H traffic and MTC traffic,and uses these traffic help us assess mobile network.