An adaptive hybrid server architecture for client-server object database management systems

The use of object database management systems (ODBMSs) has increased over the past decade due to their ability to model complex data. ODBMSs are used in many important application domains such as electronic commerce systems, medical information systems, telecommunication systems, web document authoring systems, and computer-aided design and manufacturing systems. ODBMSs typically employ the data-shipping client server architecture in which the clients cache data and operate on the cached data. This architecture reduces network latency and increases resource utilization at the client. Currently, there is a lack of consensus amongst the proponents of ODBMSs as to which data shipping architectures and algorithms should be used to implement an ODBMS. For instance, there is a lack of agreement regarding the best data transfer, cache consistency and recovery algorithms. The absence of both robust (with respect to performance) algorithms, and a comprehensive performance study comparing the competing algorithms are the key reasons for the lack of agreement about the desirable client-server architecture.; This dissertation addresses both of these problems. It first presents an adaptive hybrid client-server architecture which utilizes adaptive data transfer, cache consistency and recovery algorithms to improve the robustness (with respect to performance) of a client-server system. The adaptive algorithms presented here can be also used by the existing client-server architectures to improve their performance. Second, this dissertation presents a comprehensive performance study which evaluates the competing client-server architectures and algorithms. The study verifies the robustness of the new adaptive hybrid client-server architecture and provides new insights into the performance of the different competing algorithms and architectures.