Policy-based techniques for self-managing parallel applications

This paper presents an empirical investigation of policy-based self-management techniques for parallel applications executing in loosely-coupled environments. The dynamic and heterogeneous nature of these environments is discussed and the special considerations for parallel applications are identified. An adaptive strategy for the run-time deployment of tasks of parallel applications is presented. The strategy is based on embedding numerous policies which are informed by contextual and environmental inputs. The policies govern various aspects of behaviour, enhancing flexibility so that the goals of efficiency and performance are achieved despite high levels of environmental variability. A prototype self-managing parallel application is used as a vehicle to explore the feasibility and benefits of the strategy. In particular, several aspects of stability are investigated. The implementation and behaviour of three policies are discussed and sample results examined

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

Achieving Adaptation Through Live Virtual Machine Migration in Two-Tier Clouds

This thesis presents a model-driven approach for application deployment and management in two-tier heterogeneous cloud environments. For application deployment, we introduce the architecture, the services and the domain specific language that abstract common features of multi-cloud deployments. By leveraging the architecture and the language, application deployers author a deployment model that captures the high-level structure of the application. The deployment model is then translated into deployment workflows on specific clouds. As a use case, we introduce a live VM migration framework that maintains the application quality of services through VM migrations across two tier-clouds. The proposed framework can monitor the performance of the applications and their underlying infrastructure and plan and executes VM migrations to eliminate hotspots in a datacenter. We evaluate both the application deployment architecture and the live migration on public clouds

On Autonomic HPC Clouds

Proceedings of: Second International Workshop on Sustainable Ultrascale Computing Systems (NESUS 2015). Krakow (Poland), September 10-11, 2015.The long tail of science using HPC facilities is looking nowadays to instant available HPC Clouds as a viable alternative to the long waiting queues of supercomputing centers. While the name of HPC Cloud is suggesting a Cloud service, the current HPC-as-a-Service is mainly an offer of bar metal, better named cluster-on-demand. The elasticity and virtualization benefits of the Clouds are not exploited by HPC-as-a-Service. In this paper we discuss how the HPC Cloud offer can be improved from a particular point of view, of automation. After a reminder of the characteristics of the Autonomic Cloud, we project the requirements and expectations to what we name Autonomic HPC Clouds. Finally, we point towards the expected results of the latest research and development activities related to the topics that were identified.The work related to Autonomic HPC Clouds is supported by the European Commission under grant agreement H2020-6643946 (CloudLightning). The CLoudLightning project proposal was prepared by eight partner institutions, three of them as earlier partners in the COST Action IC1305 NESUS, benefiting from its inputs for the proposal. The section related to Autonomic Clouds is supported by the Romanian UEFISCDI under grant agreement PN-II-ID-PCE-2011- 3-0260 (AMICAS)

An Architectural Approach to Autonomics and Self-management of Automotive Embedded Electronic Systems

International audienceEmbedded electronic systems in vehicles are of rapidly increasing commercial importance for the automotive industry. While current vehicular embedded systems are extremely limited and static, a more dynamic configurable system would greatly simplify the integration work and increase quality of vehicular systems. This brings in features like separation of concerns, customised software configuration for individual vehicles, seamless connectivity, and plug-and-play capability. Furthermore, such a system can also contribute to increased dependability and resource optimization due to its inherent ability to adjust itself dynamically to changes in software, hardware resources, and environment condition. This paper describes the architectural approach to achieving the goals of dynamically self-configuring automotive embedded electronic systems by the EU research project DySCAS. The architecture solution outlined in this paper captures the application and operational contexts, expected features, middleware services, functions and behaviours, as well as the basic mechanisms and technologies. The paper also covers the architecture conceptualization by presenting the rationale, concerning the architecture structuring, control principles, and deployment concept. In this paper, we also present the adopted architecture V&V strategy and discuss some open issues in regards to the industrial acceptance

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

Survey of Autonomic Computing and Experiments on JMX-based Autonomic Features

Autonomic Computing (AC) aims at solving the problem of managing the rapidly-growing complexity of Information Technology systems, by creating self-managing systems. In this thesis, we have surveyed the progress of the AC field, and studied the requirements, models and architectures of AC. The commonly recognized AC requirements are four properties - self-configuring, self-healing, self-optimizing, and self-protecting. The recommended software architecture is the MAPE-K model containing four modules, namely - monitor, analyze, plan and execute, as well as the knowledge repository. In the modern software marketplace, Java Management Extensions (JMX) has facilitated one function of the AC requirements - monitoring. Using JMX, we implemented a package that attempts to assist programming for AC features including socket management, logging, and recovery of distributed computation. In the experiments, we have not only realized the powerful Java capabilities that are unknown to many educators, we also illustrated the feasibility of learning AC in senior computer science courses

A peer-to-peer infrastructure for resilient web services

This work is funded by GR/M78403 “Supporting Internet Computation in Arbitrary Geographical Locations” and GR/R51872 “Reflective Application Framework for Distributed Architectures”, and by Nuffield Grant URB/01597/G “Peer-to-Peer Infrastructure for Autonomic Storage Architectures”This paper describes an infrastructure for the deployment and use of Web Services that are resilient to the failure of the nodes that host those services. The infrastructure presents a single interface that provides mechanisms for users to publish services and to find hosted services. The infrastructure supports the autonomic deployment of services and the brokerage of hosts on which services may be deployed. Once deployed, services are autonomically managed in a number of aspects including load balancing, availability, failure detection and recovery, and lifetime management. Services are published and deployed with associated metadata describing the service type. This same metadata may be used subsequently by interested parties to discover services. The infrastructure uses peer-to-peer (P2P) overlay technologies to abstract over the underlying network to deploy and locate instances of those services. It takes advantage of the P2P network to replicate directory services used to locate service instances (for using a service), Service Hosts (for deployment of services) and Autonomic Managers which manage the deployed services. The P2P overlay network is itself constructed using novel Web Services-based middleware and a variation of the Chord P2P protocol, which is self-managing.Postprin