Team Sardes

Members
Overall Objectives
Scientific Foundations
Application Domains
Software
New Results
Contracts and Grants with Industry
Other Grants and Activities
Dissemination
Bibliography

Section: New Results

Autonomous System Management

Participants : Sara Bouchenak, Fabienne Boyer, Noël De Palma, Olivier Gruber, Jean-Bernard Stefani, Jean Arnaud, Jakub Kornaś, Jérémy Philippe, Sylvain Sicard, Christophe Taton.

We have continued the development of the Jade framework for autonomous distributed system management. We report below new results obtained this year.

Automated deployment and configuration

We have continued the development of facilities for the automated deployment and configuration of distributed software architectures. Two main results have been obtained this year: the development of new deployment and reconfiguration support in Jade, and the development of the DepOz framework for the construction of self-deployable and self-configurable components.

The new deployment and reconfiguration support in Jade introduces a new module and package system for Fractal components in Java, that overcomes limitations of the OSGI framework, previously used in Jade. The new module and package system allows a uniform and system-wide management of component executables, and supports dynamic component code updates. The system is described in detail in Jakub Kornaś' PhD thesis [12] .

The DepOz framework supports the construction of complex distributed software architectures, the programming of complex deployment processes, and the construction of self-configurable components. It complements the previous work with the ability to program highly parameterized deployment workflows and to construct self-deployable and self-configurable distributed components. It is described in detail in Chrstophe Taton's PhD thesis [14] .

Autonomous Management of Performance and QoS

The goal of self-optimization is to maintain optimal (or near-optimal) system performance and quality-of-service (QoS) in spite of wide variations of the load or of the amount of available resources. Performance may be measured by various criteria, such as average response time or average throughput for an Internet service, or bounded jitter for a video server, etc. QoS may reflect several service characteristics such as service availability which may be measured as service abandon rate in an Internet service.

We have proposed simple heuristics-based approaches to self-optimization of cluster-based Internet services through dynamic resource provisioning. These approaches were successfully applied to replicated database systems through dynamic resource (un-)provisioning upon database load variation. Dynamic resource provisioning was applied in conjunction with replication protocols and group communication protocols as part of the GORDA European project  [39] , [40] , [43] . The proposed approaches were also applied to messaging systems in the context of the JORAM open-source Java message-oriented middleware hosted by the OW2 consortium. We have used the Jade framework to build autonomic capabilities on top of the JORAM middleware, and described how to (i) dynamically adapt the load distribution among the servers (load-balancing aspect) and (ii) dynamically adapt the replication level (provisioning aspect)  [30] , [32] , [14] . Finally, cluster-based multi-tier enterprise applications were also used as a testbed of the proposed dynamic resource provisioning policies of self-optimization. Among the reasearch issues tackled in this work, we can cite system oscillation due to potential concurrent reconfigurations on the distributed multi-tier system. We proposed system oscillation prevention techniques that follows a software architecture-based approach  [38] , [14] .

The above-mentioned work mainly proposes heuristics-based techniques that provide a best-effort behavior and aims at keeping the managed system near-optimal. We have also proposed new techniques that guarantee system optimality with strict guarantees on service level objectives (SLOs) such as maximum latency and maximum abandon rate for Internet services. The proposed solutions make use of queuing theory to modeling and capacity planning of cluster-based multi-tier enterprise systems  [33] . We also cooperate with the NeCS INRIA research group to apply control theory to modeling and capacity planning of database and server systems  [36] . In the context of this cooperation, the PhD thesis of L. Malrait is co-advised by Nicolas Marchand (NeCS) and Sara Bouchenak. A patent proposal on this work is ongoing.


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