Optimizing IoT Performance Through Edge Computing: Reducing Latency, Enhancing Bandwidth Efficiency, and Strengthening Security for 2025 Applications

Abstract

In this article, the authors analyze how edge computing may be used to mitigate IoT pressures associated with latency, bandwidth consumption and enforce security. The delay experienced in traditional cloud-based IoT systems is real-time applications such as healthcare, industrial automation and smart cities make them inefficient usage of bandwidth. The study method outsources the processing tasks to the edge nodes, thus reducing the latency by 82%, consuming bandwidth up to 65% and elevating security as it makes use of lesser network points where data transits. The article also investigate several task offloading ratios, like 80:20, and 90:10 to achieve superior performance over various IoT applications. On the flip side, energy usage in edge computing, particularly at scale, continues to be a major source of consternation. In the future, we will work on developing energy efficient algorithms to reduce the power consumption. Moving forward, this study predicts that by 2025, edge computing will be necessary for real-time processing of data and the management of security, while improvements are still to be made on energy efficiency and decentralized security protocols.

Keywords

• edge computing
• internet of things (iot)
• latency reduction
• bandwidth optimization
• real-time data processing
• cloud computing
• scalability
• network congestion
• iot performance.