In this dissertation, we address important issues related to forecasting the bandwidth of stored and live video over optical access networks. The nature of the communication network usually governs the video transport standard used; nevertheless, the nature of the transmitted traffic imposes some challenges on the transport standards that should also be considered. As far as video traffic is concerned, two major issues should be taken into consideration. First, compressed video has a variable bit rate which requires a large transmission bandwidth to ensure a certain Quality of Service (QoS). Therefore, video transport standards must be able to utilize the network bandwidth efficiently. Second, the timing requirement for video is stringent and must be met to ensure smooth playback at the receiving end. In this dissertation, we also propose an accurate video bandwidth forecasting approach called Feed-Forward Bandwidth Indication (FFBI). FFBI will assist the dynamic bandwidth allocation to help utilize the multimedia network resources more efficiently and comply with the timing requirements of video transmission. FFBI provides 100% accurate bandwidth forecast that comes for free for pre-recorded video and at the expense of some introduced delay for live video. With video transport over access networks projected to supplant other transport mechanisms in the next few years, we conducted a performance analysis of FFBI within Ethernet Passive Optical Networks (EPONs). We found that the use of FFBI can provide a 50% reduction in queueing delay compared to the use of no forecasting and a 35% reduction in queueing delay compared to other
forecasting methods. In addition, we also found that the use of FFBI can provide a 60% reduction in delay jitter compared to the use of no forecasting and a 88% to 92% reduction in delay jitter compared to other forecasting methods.