Research on Mobile Internet Performance Crowdsourcing Technology Based on SDN Architecture

This paper presents a software-defined network (SDN) architecture for data-analytic transmission and processing tasks.Each SDN node performs its assigned role with varying levels of precision; network bandwidth and node processing capabilities differ; and task requirements fluctuate based on unrecognized statistical patterns.We formulate a resource allocation issue to improve the overall efficacy of the integrated operations.The proposed method includes a system for the allocation of computation and transmission rates (ATCR).Within the mobile network, task offloading presents an advantageous solution, offering lowlatency computation and enhanced control for mobile users.Nonetheless, constrained computational resources and the evolving demands of mobile customers render the routing of computational requests to the appropriate edge problematic.Initially, we delineate the issue of power allocation for mobile users to optimize energy conservation.We tackle request offloading and resource allocation to expedite system responses to user requests.The simulation findings indicate that the proposed technique demonstrates effective performance regarding reaction rate in a dynamic SDN and may contribute to reducing transmission energy consumption.This paper introduces a novel mobile internet crowdsourcing methodology grounded in SDN architecture.The suggested technique utilizes the SDN controller to aggregate and evaluate crowdsourced data from mobile devices, therefore facilitating real-time paper of mobile internet performance.The suggested technique decreases average response times by thirty percent compared to conventional crowdsourcing methods.The suggested strategy improves crowdsourcing accuracy by 25% compared to established crowdsourcing techniques.The suggested technique decreases mobile device energy usage by 20% compared to established crowdsourcing methods.The suggested approach enhances the throughput of the SDN controller by 40% in comparison to conventional SDN controllers.