Optimizing Point-to-Point Wireless Bridge Networks for Performance and Cost: A Case Study on Improving Network Access in Eulogio \\\\\\\"Amang\\\\\\\" Rodriguez Institute of Science and Technology
Researchers
DR. JESUS S. PAGUIGAN, DR. ROGELIO T. MAMARADLO, LARRY T. RUTAQUIO
Abstract
The Eulogio \"Amang\" Rodriguez Institute of Science and Technology (EARIST) is encountering problems in making their academic and administrative systems\' reliable and high-speed network connectivity operate smoothly whenever they like. The researcher assesses and applies point-to- point wireless bridge networks as they are the most productive and budget-friendly alternative. By specifically employing directional line-of-sight antennas in the processes, the technology contributes to better data transmission. It therefore reduces signal loss and infrastructure costs, which are greater when conventional wired solutions are climinated. The rescarch focused on designing an optimized network infrastructure using a star topology for permeability, reliability, and security. Important factors encompass site selection and line-of-sight optimization for higher single-pairing antennas and traffic power cquipment. In addition to the pertinent issues, Data Center Bridging protocols are united to make the system more reliable, and fewer frames are lost. The budget report is rather detailed about the benefits of a wireless bridge network at EARIST, where the time of its lifetime is concerned. Findings suggest that a point-to-point wireless bridge network for performanco and cost utilization can enhance network reliability, speed, and security, and reduce costs associated with operations. The network layout, which was suggested, guarantees a regular internet connection from building to building on the campus acts as a catalyst for improved digital learning environments. The wireless bridging technologies utilized as the means of network infrastructure optimization in EARIST bring accessibility to an intelligent pedagogical climate with a new operational model.