||Over the past few years, tremendous advances have been made in mobile computing and wireless communication technologies, including wireless high-speed networks, portable wireless devices, mobile application standards, and supporting software technologies. As a result, mobile data has been flooding the commercial market recently. However, various constraints of mobile computing environments, such as scarce wireless bandwidth and limited client resources, remain as barriers that need to be overcome before the vision of mobile computing can be fully realized. Thus, sophisticated data management and resource management techniques are needed for the enhancement of the performance of mobile data access. This thesis attempts to address some of the performance issues by applying advanced client-side data caching techniques. Broadcasting is an effective technique to reduce network traffic, and is inherently supported by wireless networks. It thus has been advocated by numerous on-demand data access protocols. In a wireless cellular network, broadcasting can be implemented within a single cell. However, the data owned by different cells could be different. If a client requests a data item available only in a remote cell, an inter-cell data transmission over some wired link is needed, which introduces additional access delay. In this paper, we demonstrate that such delay can be minimized through the use of remote caching. Specifically, we propose a novel cooperative caching scheme, in which each cell dynamically allocates the cache spaces for data from different remote cells. It makes replacement decisions according to several important factors: data item access frequency, cell traffic, and retrieval delay. Simulation results show that the proposed scheme can significantly reduce the response time over the non-cooperative caching scheme under various system configurations. Then, we consider general wireless data dissemination services and propose a novel cache replacement policy, called GBC, concerning a realistic mobile environment. The GBC policy takes into account the cost of ensuring cache consistency before each cached item is used. In addition, GBC considers access probability, update frequency, retrieval delay, and data size in developing the cost function which determines the cached item(s) to be replaced. The analytical study we performed shows that GBC achieves the best access performance in terms of stretch, which is a widely used metric for variable-size data.