Team sardes

Overall Objectives
Scientific Foundations
New Results
Contracts and Grants with Industry

Section: New Results

Control for adaptive systems: Self-tuning for Internet services

Participants : Sara Bouchenak, Jean Arnaud.

This work aims at building SLA (Service Level Agreement) management and self-tuning functions for Web application servers. In particular, we address the issue of providing guarantees on both service performance and service availability, two criteria of service quality that are usually handled separetely, and can be seen as antagonistic (high service availability is usually obtained at the expense of performance, and good performance has usually an impact on availability). We have developed two sets of techniques to achieve self-tuning with guarantees on service level objectives (SLOs) such as maximum response times and maximum abandon rates.

The first set of techniques applies fluid models from control theory to modeling, capacity planning, system control and provisioning of server systems. Our main contributions are:

  1. a novel model that reflects the non-linear behavior of server systems,

  2. a dynamically and automatically evolving model state based on online monitoring in order to reflect service workload variation,

  3. novel control laws that take into account both performance and availability SLOs to dynamically and automatically control the system and provision its resources accordingly.

These techniques were proposed in the form of theoretical model and control laws, implemented in a Java-based prototype called ConSer, and successfully evaluated in a real warehouse online service running on a database system [21] . This work is conducted in the context of a collaboration between SARDES and the NeCS INRIA Project-Team. This work is the subject of the PhD thesis of Luc Malrait, who is co-advised by Nicolas Marchand (NeCS) and Sara Bouchenak (SARDES).

The second set of techniques makes use of queuing theory to model, provision and plan the capacity of Internet services deployed on clusters of computers, as is usually the case of e-commerce services. Our main contributions consist of:

  1. an extended queuing model that takes into account the distribution and parallelism of cluster-based distributed systems, and allows to predict system performance and availability,

  2. a novel approach for dynamically and automatically configuring model state, which reflects workload changes and does not require system administrators to perform offline calibration of the model, a technically tricky phase usually necessary prior to the use of these types models,

  3. a novel control algorithm that takes into account both performance and availability SLOs while minimizing system costs; it applies dynamic and automatic configuration and provisioning of cluster-based systems with necessary and sufficient resources that guarantee target service performance and availability.

These techniques were proposed in the form of a theoretical extension of the well-known MVA queuing model, the specification of a capacity planning and provisioning algorithm, the design of an online distributed monitoring mechanism of cluster-based systems, and the implementation of a Java-based software prototype called MoKa running in realistic distributed Web applications running on Web servers and database servers. This work is the subject of the Ph.D. thesis of Jean Arnaud, defended in September 2010 [13] , and has been presented at the ACM SAC conference [25] and in a book chapter [41] .


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