A significant feature of bandwidth monitoring structure is the excellent delivery of internet facilities with larger data rates and bigger coverage. Existing research on bandwidth monitoring focused on pattern tracking, health monitoring, and the performance of numerous physical communication interfaces, amongst others. However, these researches were not Energysaving and cost-reduction in reducing the overhead energy cost of bandwidth monitoring by which internet users achieve their goals to the background. This research was aimed at developing an Energy-saving and costreduction bandwidth monitoring model. These techniques had two stages which are network traffic observation and Bandwidth consumption analysis stages of bandwidth monitoring. Data collection for this research based on bandwidth monitoring using the Paessler Router Traffic Grapher (PRTG) network monitoring software was done at a network operating centre in South-Western Nigeria. The data collected comprised 8,673 records of bandwidth monitored metrics such as Date/Time of bandwidth monitoring, Network traffic volume (of end-to-end connectivity), Network traffic speed (from source to destination and vice-versa), Network downtime, and coverage. The model was formulated using bandwidth optimization (BO) techniques while the data collected were coupled with three algorithms: FUE-sub-channel matching algorithm (FSMA), Joint sub-channel and power allocations algorithm (JSPA), and integrated structure cabling system algorithm (ISCSA). The proposed algorithm was used to formulate the monitoring model using the PRTG monitoring tool. A new mathematical equation was formulated from the model for the integration of Anti-Meridian (AM) / PrimeMeridian (PM) Timer relays and the Normally-Open (NO)/Normally-closed (NC) switches for Energy-saving and cost-reduction to design the monitoring model. When the existing algorithms were compared to the proposed bandwidth monitoring model, the proposed model generated a higher success rate with a maximum of 50 wireless routers capacity

Keywords : Bandwidth Monitoring, Pattern Tracking, Bandwidth Tracking, Network Traffic, Bandwidth Optimization, Communication Interfaces.