• Akshay J P
• Aakash Raman G
• Girinath A

The Internet of Things (IoT) connect millions of devices in diverse areas such as smart cities, e-health, transportation and defence to meet a wide range of human needs. To provide these services, a large amount of data needs to be transmitted to the IoT network servers. Currently emergency data packets do not get any special priority while routing through the Internet of Things (IoT) networks. These data packets flow through routers using conventional QoS process which does not guarantee that an emergency data packet traveling in congested IoT network will actually be routed to control room on time. A major challenge in packet scheduling is that the behaviour of each traffic class may not be known in advance, and can vary dynamically. Therefore, innovative packet prioritization techniques, e.g., queue management approach needs to be developed to overcome prioritization problems in IoT networks. This project proposes an Artificial Intelligence Packet Priority Queuing model P2 Queue based emergency data packet classification with a prioritization algorithm to provide a required transmission priority for emergency data. In this project, LSTM is used to classify the emergency data packet. Then, according to the model characteristics, a deep intelligent scheduling algorithm based on a Deep Q Network (DQN) framework is proposed to make scheduling decisions for communication. Effective simulation experiments demonstrate that the proposed P2Queue can effectively create scheduling strategies for emergency data packet flows. Results confirmed the machine learning module achieved 91.5% of accuracy when identifying the emergency data and assigning the expected priority.

"PPQM an Emergency Packet Scheduling in IoT Network Using Reinforcement Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 5, page no.k663-k669, May-2022, Available :http://www.jetir.org/papers/JETIR2205B86.pdf

"PPQM an Emergency Packet Scheduling in IoT Network Using Reinforcement Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 5, page no. ppk663-k669, May-2022, Available at : http://www.jetir.org/papers/JETIR2205B86.pdf