In a data-shipping database system, data items are retrieved from the server machines, cached and processed at the client machines, and then shipped back to the server. Current cache consistency approaches typically rely on a centralized server or servers to enforce the necessary concurrency control actions. This centralized server imposes a limitation on the scalability and performance of these systems. This paper presents a new consistency protocol, Active Data-aware Cache Consistency (ADCC), that allows clients to be aware of the global state of their cached data via a two-tier directory. Using parallel communication with simultaneous client-server and client-client messages, ADCC reduces the network latency for detecting data conflicts by 50%, while increasing message overhead by about 8% only. In addition, ADCC improves scalability by partially offloading the concurrency control function from the server to the clients. An optimization, Lazy Update, is introduced to reduce the message overhead for maintaining client directory consistency. We implement ADCC in a page server DBMS architecture and compare it with the leading cache consistency algorithm, Callback Locking (CBL), which is the most widely implemented algorithm in commercial DBMSs. Our performance study shows that ADCC has a similar or lower abort rate, higher throughput, and better scalability for important workloads and system configurations. Both the simulation results and the analytic study indicate that the message overhead is low and that ADCC produces better behavior compared to the traditional server-based communication under high contention workloads.
The widespread deployment of the advanced computer technology in business and industries has demanded the high standard on quality of service (QoS). For example, many Internet applications, i.e. online trading, ecommerce, and real-time databases, etc., execute in an unpredictable general-purpose environment but require performance guarantees. Failure to meet performance specifications may result in losing business or liability violations. As systems become distributed and complex, it has become a challenge for QoS design. The ability of on-line identification and auto-tuning of adaptive control systems has made the adaptive control theoretical design an attractive approach for QoS design. However, there is an inherent constraint in adaptive control systems, i.e. a conflict between asymptotically good control and asymptotically good on-line identification. This paper first identifies and analyzes the limitations of adaptive control for network QoS by extensive simulation studies. Secondly, as an approach to mitigate the limitations, we propose an adaptive dual control framework. By incorporating the existing uncertainty of on-line prediction into the control strategy and accelerating the parameter estimation process, the adaptive dual control framework optimizes
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