Adaptive Network Traffic Reduction for Optimal Performance

In response to the increasing demands of network traffic, this research study presents an Adaptive Network Traffic Reduction system to dynamically manage network resources for optimal performance. Unlike utilizing P4 and IoT devices, this system harnesses the versatility of Java programming language. By leveraging Java, this system facilitates real-time analysis and manipulation of network traffic, ensuring efficient traffic management without the need for specialized hardware. Through intelligent traffic monitoring, analysis, and adaptive traffic shaping techniques, this system optimizes network utilization, alleviates congestion, and enhances overall network performance. This adaptive approach enables this systemto respond dynamically to changing network conditions, mitigating traffic bottlenecks in dynamic environments. Extensive simulations and real-world experiments validate the effectiveness of this approach, demonstrating its ability to adapt to varying network conditions and ensure smooth traffic flow. By utilizing Java-based programming, adaptive traffic management strategies and AES algorithm which encrypts and decrypts data using a block cipher technique to ensure confidentiality and security in digital communications and storage.