Recent advances in video coding technology have led to a dramatic growth in network-based video applications. In these applications, users may access and interact with video content on different types of terminals and networks. One critical need in such a ubiquitous environment is the ability to handle the huge variation of resource constraints such as bandwidth, display capability, CPU speed, power, etc. Scalable video coding intends to encode the signal once at highest resolution, but enables decoding from partial streams depending on the specific rate and resolution required by a certain application. This allows for simple and flexible solutions for transmission over heterogeneous networks, additionally providing adaptability for bandwidth variations and error conditions. It further allows simple adaptation for a variety of storage devices and terminals. In this thesis, we study various fundamental techniques in error control and joint rate allocation for scalable video transmission. The goal of our research is to produce the best visual quality of the reconstructed video with a given resource constraint and achieve better tradeoff between computing complexity and quality.