There is an increasing demand for multimedia services in heterogeneous wireless networks. Considering the highly dynamic wireless channels and the relatively large size of the multimedia data, how to support efficient and reliable multimedia delivery is a pressing issue. In this dissertation, we investigate the multimedia delivery algorithms in heterogeneous wireless networks from three different aspects. First, we study the single-flow rate adaptation of video streaming algorithm over multiple wireless interfaces. In order to maintain high video streaming quality while reducing the wireless service cost, the optimal video streaming process with multiple links is formulated as a Markov Decision Process (MDP). The reward function is designed to consider the quality of service (QoS) requirements for video traffic, such as the startup latency, playback fluency, average playback quality, playback smoothness and wireless service cost. To solve the MDP in real time, we propose an adaptive, best-action search algorithm to obtain a sub-optimal solution. To evaluate the performance of the proposed adaptation algorithm, we implemented a testbed using the Android mobile phone and the Scalable Video Coding (SVC) codec and conducted experiments with real video flow. Then, with the multiple multimedia flows competing for limited wireless resources, we propose a utility-based scheduling algorithm for multimedia transmission in Drive-thru Internet. A utility model is devised to map the throughput to user's satisfaction level in terms of multimedia data quality, such as Peak Signal-to-Noise Ratio (PSNR) of video. The objective of the scheduling problem is to maximize the total utility. Then the optimization problem is formulated as a finite-state decision problem with the assumption that future arrival information is known, and it is solved by a searching algorithm as the benchmark. To obtain a real-time solution, a practical heuristic algorithm based on the concept of utility potential is devised. We further implemented the solution and conducted extensive simulations using NS-3. Finally, the multimedia dissemination problem in large-scale VANETs is investigated. We first utilize a hybrid-network framework to address the mobility and scalability issues in large-scale VANETs content distribution. Then, we formulate a utility-based maximization problem to find the best delivery strategy and select an optimal path for the multimedia data dissemination, where the utility function has taken the delivery delay, the Quality of Services (QoS) and the storage cost into consideration. We obtain the closed-form of the utility function, and then obtain the optimal solution of the problem with the convex optimization theory. Finally, we conducted extensive trace-driven simulations to evaluate the performance of the proposed algorithm with real traces collected by taxis in Shanghai. In summary, the research outcomes of the dissertation can contribute to three different aspects of multimedia delivery in heterogeneous wireless networks. First, we have proposed a real-time rate adaptation algorithm for video streaming with multiple wireless interfaces, to maintain the high quality while reducing the wireless services cost. Second, we have presented an optimal scheduling algorithm which can maximize the total satisfaction for multimedia transmission in Drive-thru Internet. Third, we have derived the theoretical analysis of the utility functions including delivery delay, QoS and the storage cost, and have obtained an optimal solution for multimedia data dissemination in large-scale VANETs to achieve the highest utility. / Graduate / 0984 / 0544