A Dissertation Submitted to the Department of Electrical Engineering and the Committee on Graduate Studies of National Taiwan University in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy

With the cutting edge technology advance in wireless and mobile computers, users are able to access various information from anywhere at anytime. Note that several features, including mobility of users, resource limitation and data broadcasting, make the mobile computing system unique and call for the design of a new data management for this ubiquitious environment. In this dissertation, we first study the impact of mobility on the design for the cache retrieval and data allocation problems. Then, we investigate the query processing in a mobile computing environment while considering the resource limitation of mobile computers. Finally, we study the problem of generating data broadcast programs for multiple broadcasr channels. Explicitly, for cache retrieval problem, we explore several cache retrieval schemes to improve the efficiency of cache retrieval. In particular, we analyze the impact of using a coordinator buffer to improve the overall performance of cache retrieval. Moreover, in light of the properties of transactions (i.e, temporal locality of data access among transactions), we devise a Dynamic and Adaptive cache Retrieval scheme (DAR) that can utilize proper cache methods according to some specific criteria to deal with the service handoff situation in a mobile computing environment. It is shown by our results that temporal locality has a significant impact to the performance of cache retrieval methods, and by adaptively adopting the advantages of different cache retrieval methods, DAR significantly outperforms other schemes and is particularly effective for a mobile computing environment. For data allocation in a mobile computing environment, we develop data allocation schemes that can utilize the knowledge of user moving patterns for proper allocation of both personal and shared data. By employing the data allocation schemes, the occurrences of costly remote accesses can be minimized and the performance of a mobile computing system is thus improved. For personal data allocation, two data allocation schemes, which explore different levels of mining results, are devised: one utilizes the set level of moving patterns and the other utilizes the path level of moving patterns. The data allocation algorithms for shared data, which are able to achieve local optimization and global optimization, are developed. Local optimization refers to the optimization that the likelihood of local data access by an individual mobile user is maximized whereas global optimization refers to the optimization that the likelihood of local data access by all mobile users is maximized. Specifically, by exploring the features of local optimization and global optimization, we devise two algorithms SD-local and SD-global to achieve local optimization and global optimization, respectively. For query processing in a mobile computing environment, we explore three asymmetric features of a mobile environment. Then, in light of these features, we devise query processing methods for both join and query processing. A semijoin which is initiated by a mobile computer (respectively, the server) and is beneficial to reduce the cost of a join operation is termed a mobile-initiated, or MI (respectively, serverinitiated, or SI ) profitable semijoin. According to those asymmetric features of a mobile computing system, we examine three different join methods and devise some specific criteria to identify MI/SI profitable semijoins. For query processing which refers to the processing of multi-join queries, we develop three query processing schemes. In particular, we formulate the query processing in a mobile computing system as a two-phase query processing procedure that can determine a join sequence and interleave that join sequence with SI profitable semijoins to reduce both the amounts of data transmission and energy consumption. Performance of these join and query methods is comparatively analyzed and sensitivity analysis on several parameters is conducted. Using data broadcasting, mobile users can obtain the data of interest efficiently and only need to wait for the required data to present on the broadcast channel. The issue of designing proper data allocation in the broadcast disks is to reduce the average expected delay of all data items. We explore the problem of generating broadcast programs with the data access frequencies and the number of broadcast disks in a broadcast disk array given. Specifically, we first transform the problem of generating broadcast programs into the one of constructing a channel allocation tree with variant-fanout. By exploiting the feature of tree generation with variant-fanout, we develop a heuristic algorithm VFK to minimize the expected delay of data items in the broadcast program. In order to evaluate the solution quality obtained by algorithm VFK and compare its resulting broadcast program with the optimal one, we devise an algorithm based on a guided search to obtain the optimal solution. Since the data access frequencies in practice may vary with time, we deal with the problem of adjusting broadcast programs to effectively respond to the changes of data access frequencies, and develop an efficient algorithm LD to address this problem.