Energy-QoS Tradeoffs in J2EE Hosting Centers

International audienceNowadays, hosting centres are widely used to host various kinds of applications e.g., web servers or scientific applications. Resource management is a major challenge for most organisations that run these infrastructures. Many studies show that clusters are not used at their full capacity which represents a significant source of waste. Autonomic management systems have been introduced in order to dynamically adapt software infrastructures according to runtime conditions. They provide support to deploy, configure, monitor, and repair applications in such environments. In this paper, we report our experiments in using an autonomic management system to provide resource aware management for a clustered application. We consider a standard replicated server infrastructure in which we dynamically adapt the degree of replication in order to ensure a given QoS while minimising energy consumption

Implementing autonomic administration DSLs in TUNe

Software components are recognized as the most adequate approach to support autonomic administration systems. We implemented and experimented with such a system, but observed that the interfaces of a component model are too low-level and difficult to use. Consequently, we designed higher abstraction level languages for modeling administration policies. These languages are specific to our autonomic administration domain. We metamodeled and implemented these DSLs on the Kermeta framework

A Generic Deployment Framework for Grid Computing and Distributed Applications

Deployment of distributed applications on large systems, and especially on grid infrastructures, becomes a more and more complex task. Grid users spend a lot of time to prepare, install and configure middleware and application binaries on nodes, and eventually start their applications. The problem is that the deployment process is composed of many heterogeneous tasks that have to be orchestrated in a specific correct order. As a consequence, the automatization of the deployment process is currently very difficult to reach. To address this problem, we propose in this paper a generic deployment framework allowing to automatize the execution of heterogeneous tasks composing the whole deployment process. Our approach is based on a reification as software components of all required deployment mechanisms or existing tools. Grid users only have to describe the configuration to deploy in a simple natural language instead of programming or scripting how the deployment process is executed. As a toy example, this framework is used to deploy CORBA component-based applications and OpenCCM middleware on one thousand nodes of the French Grid5000 infrastructure.Comment: The original publication is available at http://www.springerlink.co

Autonomic Management Policy Specification: from UML to DSML

International audienceAutonomic computing is recognized as one of the most promizing solutions to address the increasingly complex task of distributed environments' administration. In this context, many projects relied on software components and architectures to provide autonomic management frameworks. We designed such a component-based autonomic management framework, but observed that the interfaces of a component model are too low-level and difficult to use. Therefore, we introduced UML diagrams for the modeling of deployment and management policies. However, we had to adapt/twist the UML semantics in order to meet our requirements, which led us to define DSMLs. In this paper, we present our experience in designing the Tune system and its support for management policy specification, relying on UML diagrams and on DSMLs. We analyse these two approaches, pinpointing the benefits of DSMLs over UML

Two levels autonomic resource management in virtualized IaaS

International audienceVirtualized cloud infrastructures are very popular as they allow resource mutualization and therefore cost reduction. For cloud providers, minimizing the number of used resources is one of the main services that such environments must ensure. Cloud customers are also concerned with the minimization of used resources in the cloud since they want to reduce their invoice. Thus, resource management in the cloud should be considered by the cloud provider at the virtualization level and by the cloud customers at the application level. Many research works investigate resource management strategies in these two levels. Most of them study virtual machine consolidation (according to the virtualized infrastructure utilization rate) at the virtualized level and dynamic application sizing (according to its workload) at the application level. However, these strategies are studied separately. In this article, we show that virtual machine consolidation and dynamic application sizing are complementary. We show the efficiency of the combination of these two strategies, in reducing resource usage and keeping an application’s Quality of Service. Our demonstration is done by comparing the evaluation of three resource management strategies (implemented at the virtualization level only, at the application level only, or complementary at both levels) in a private cloud infrastructure, hosting typical JEE web applications (evaluated with the RUBiS benchmark)

Towards Model-Driven Validation of Autonomic Software Systems in Open Distributed Environments

New distributed systems are running onto fluctuating environments (e.g. ambient or grid computing). These fluctuations must be taken into account when deploying these systems. Autonomic computing aims at realizing programs that implement self-adaptation behaviour. Unfortunately in practice, these programs are not often statically validated, and their execution can lead to emergent undesirable behaviour. In this paper, we argue that static validation is mandatory for large autonomic distributed systems. We identify two kinds of validation that are relevant and crucial when deploying such systems. These validations affect the deployment procedures of software composing a system, as well as the autonomic policies of this system. Using our Dacar model-based framework for deploying autonomic software distributed architectures, we show how we tackle the problem of static validation of autonomic distributed system

Middleware-based Database Replication: The Gaps between Theory and Practice

The need for high availability and performance in data management systems has been fueling a long running interest in database replication from both academia and industry. However, academic groups often attack replication problems in isolation, overlooking the need for completeness in their solutions, while commercial teams take a holistic approach that often misses opportunities for fundamental innovation. This has created over time a gap between academic research and industrial practice. This paper aims to characterize the gap along three axes: performance, availability, and administration. We build on our own experience developing and deploying replication systems in commercial and academic settings, as well as on a large body of prior related work. We sift through representative examples from the last decade of open-source, academic, and commercial database replication systems and combine this material with case studies from real systems deployed at Fortune 500 customers. We propose two agendas, one for academic research and one for industrial R&D, which we believe can bridge the gap within 5-10 years. This way, we hope to both motivate and help researchers in making the theory and practice of middleware-based database replication more relevant to each other.Comment: 14 pages. Appears in Proc. ACM SIGMOD International Conference on Management of Data, Vancouver, Canada, June 200