A Lightweight IoT Evaluation Model for Threat Flow Prediction with SDN and IoT Integration
Keywords:
software defined network, network resources, sensors, resource management, latencyAbstract
In the present era, several applications have looked into network edges to reduce communication and administration expenses. They are also connected to the Internet of Things (IoT) to provide a flexible network infrastructure for multimedia applications that offers a range of services. Numerous suggested methods are helping to speed up the response time for crucial networks and establish reliable protocols. However, the majority of them lack the bandwidth and dynamic qualities necessary to handle heavy multimedia traffic forwarding procedures. In an unpredictable context, they also raise the incidence of data loss and jeopardize network performance by lengthening delivery times. To maintain real-time data gathering while utilizing the fewest resources possible, this research provides a lightweight IoT evaluation model (LIoT-EM) framework for sensors employing IoT that has customizable edges. It begins by leveraging the IoT, constructing a multi-hop network, and guaranteeing the necessary operations to support restricted networking with reliable resource management. It surpassed previous solutions, according to test results, in terms of delivery rate (on average), processing delay, network overheads, packet loss ratio, and packet retransmission.
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