Internet services have a characteristic of traffic burstiness. To protect premium customers from traffic surge without over-compromising the needs of basic clients, a stress-resilient server must be able to control the quality of multi-class requests in a coordinated way for fair and graceful performance degradation in stress conditions. The goal of this project is to develop an autonomic resource management system in the network edge in support of such service quality assurance models.
The resource management system features three key innovations. First is an application-level QoS-aware resource management framework for multi-class quality assurance. Its novelty lies in the ability to providing guarantees of client-perceived end-to-end page-view response time in multi-tier web sites. Second is a 2D service differentiation model that formulates the requirements of session-based workload in both inter-session and intra-session dimensions and relates it with a revenue maximization objective in e-commerce applications. Third novelty is a model-free self-tuning feedback controller that regulates the process of resource allocation dynamically and achieves a high degree of control robustness in both long and short time scales.
Edge servers are a critical building block of the Internet with profound impact on our economy and society. This research will advance discovery and understanding of the service quality assurance problems in servers under a stressed condition. By fusing the autonomic resource management technologies into current servers, this research will ultimately enhance the service availability and survivability to stress and DoS attacks. Research-based materials about Internet services will also be instilled into the undergraduate and graduate distributed computing curriculum.
