Optimizing QoS in Internet of Multimedia Things using Cross-Layer Design and Artificial Bee Colony

Futuristic demands of multimedia applications involve comprehensive sharing of dynamic data attributes within the Multimedia Items (IoMT) Internet sense. Exploring the existing research void in this area reveals need of building an integrated routing strategy for IoMT that can cope with multiple network characteristics, physical artifacts, and with cost-effective networks and distribution modules satisfy connectivity requirements. This paper suggest a layer cross architect-layerure optimization for IoMT applications with a emphasis on connectivity efficiency factors such as rising latency, energy limitations, and optimizing low-cost energy usage. The proposed work models and integrates a swarm intelligence paradigm which involve intelligent computing of Artificial Bee Colony (ABC) maintaining effective link creation and selects the best path from source to target IoT nodes. The proposed research achieve the strongest routing usefulness for multimedia data exchange over IoT. To ensure this, the output of the proposed device is validated with an comprehensive simulation test. Results tested using MATLAB simulation method indicate an improvement of 8% in energy usage, 10% increase in throughput, 8% decrease in end to end delay and 10% increase in packet delivery ratio.