Self-Healing Distributed Scheduling Platform

International audienceDistributed systems require effective mechanisms to manage the reliable provisioning of computational resources from different and distributed providers. Moreover, the dynamic environment that affects the behaviour of such systems and the complexity of these dynamics demand autonomous capabilities to ensure the behaviour of distributed scheduling platforms and to achieve business and user objectives. In this paper we propose a self-adaptive distributed scheduling platform composed of multiple agents implemented as intelligent feedback control loops to support policy-based scheduling and expose self-healing capabilities. Our platform leverages distributed scheduling processes by (i) allowing each provider to maintain its own internal scheduling process, and (ii) implementing self-healing capabilities based on agent module recovery. Simulated tests are performed to determine the optimal number of agents to be used in the negotiation phase without affecting the scheduling cost function. Test results on a real-life platform are presented to evaluate recovery times and optimize platform parameters

Visibility of Control in Adaptive Systems

Adaptive systems respond to changes in their internal state or external environment with guidance from an underlying control system. ULS systems are particularly likely to re- quire dynamic adaptation because of their decentralized con- trol and the large number of independent stakeholders whose actions are integral to the system's behavior. Adaptation may take various forms, but the system structure will al- most inevitably include one or more closed feedback loops. We argue that adaptability is a characteristic of a solution, not of a problem, and that the feedback loop governing con- trol of adaptability should be explicit in design and analysis and either explicit or clearly traceable in implementation.</p

Manipulating and documenting software structures

An effective approach to program understanding involves browsing, exploring, and creating views that document software structures at multiple levels of abstraction. While exploring the many relationships in a multi-million line legacy software system, one can easily lose context. One approach to alleviate this problem is to visualize these structures using sheye-view techniques. This chapter introduces Simple Hierarchical Multi-Perspective (SHriMP) views. The SHriMP visualization technique has been incorporated into the Rigi reverse engineering system, greatly enhancing its capabilities for documenting software abstractions. The applicability and usefulness of SHriMP views are illustrated with selected software visualization tasks

4th International Workshop on Green and Sustainable Software (GREENS 2015)

Engineering green software-intensive systems is critical in our drive towards a sustainable, smarter planet. The goal of green software engineering is to apply green principles to the design and operation of software-intensive systems. Green and self-greening software systems have tremendous potential to decrease energy consumption. Moreover, enterprise software can and should be re-thought to address sustainability issues using innovative business models, processes, and incentives. Monitoring and measuring the greenness of software is critical towards the notion of sustainable and green software. Demonstrating improvement is paramount for users to achieve and affect change. Thus, the theme of GREENS 2015 is Towards a Green Software Body of Knowledge. The GREENS workshop series brings together researchers and practitioners to discuss both the state-of-the-art and state-of-the-practice in green software, including novel ideas, research challenges, methods, experiences, and tools to support the engineering of sustainable and energy efficient software systems

Autonomic Computing

This report examines selected aspects of autonomic computing and explores some of the strengths and weaknesses of that technology. It also makes connections between autonomic computing and current work in several initiatives at the Software Engineering Institute. Furthermore, it describes the potential and impact of autonomic computing for Department of Defense (DoD) systems and outlines some of the challenges for the DoD as it moves to exploit autonomic computing technology