Fuzzy MIMO Control in Virtualized Server Clusters

It is important but challenging to assure the performance of multi-tier Internet applications with the power consumption cap of virtualized server clusters mainly due to system complexity of shared infrastructure and dynamic and bursty nature of workloads. This paper presents PERFUME, a system that simultaneously guarantees power and performance targets with flexible tradeoffs and service differentiation among co-hosted applications while assuring control accuracy and system stability. Based on the proposed fuzzy MIMO control technique, it effectively controls both the throughput and percentile-based response time of multi-tier applications due to its novel self-adaptive fuzzy modeling that integrates the strengths of fuzzy logic, MIMO control and artificial neural network.

Furthermore, we address an important challenge of pro-actively avoiding violations of power and performance targets in anticipation of future workload changes. We implement PERFUME in a testbed of virtualized blade servers hosting multi-tier RUBiS applications. Performance evaluation based on synthetic and real-world Web workloads demonstrates its control accuracy, flexibility in selecting tradeoffs between conflicting targets, service differentiation capability and robustness against highly dynamic and bursty workloads. It outperforms a representative utility based approach in providing guarantee of the system throughput, percentile-based response time and power budget.