Automatic performance optimisation of component-based enterprise systems via redundancy

Component technologies, such as J2EE and .NET have been extensively adopted for building complex enterprise applications. These technologies help address complex functionality and flexibility problems and reduce development and maintenance costs. Nonetheless, current component technologies provide little support for predicting and controlling the emerging performance of software systems that are assembled from distinct components. Static component testing and tuning procedures provide insufficient performance guarantees for components deployed and run in diverse assemblies, under unpredictable workloads and on different platforms. Often, there is no single component implementation or deployment configuration that can yield optimal performance in all possible conditions under which a component may run. Manually optimising and adapting complex applications to changes in their running environment is a costly and error-prone management task. The thesis presents a solution for automatically optimising the performance of component-based enterprise systems. The proposed approach is based on the alternate usage of multiple component variants with equivalent functional characteristics, each one optimized for a different execution environment. A management framework automatically administers the available redundant variants and adapts the system to external changes. The framework uses runtime monitoring data to detect performance anomalies and significant variations in the application's execution environment. It automatically adapts the application so as to use the optimal component configuration under the current running conditions. An automatic clustering mechanism analyses monitoring data and infers information on the components' performance characteristics. System administrators use decision policies to state high-level performance goals and configure system management processes. A framework prototype has been implemented and tested for automatically managing a J2EE application. Obtained results prove the framework's capability to successfully manage a software system without human intervention. The management overhead induced during normal system execution and through management operations indicate the framework's feasibility

Decentralised architecture for multi-objective autonomic management

Designing and organising large numbers of autonomic resources into a coherent system is a difficult tendeavour. It necessitates handling complex interactions among dynamic, heterogeneous components, autonomic managers and human policies. Several architectural models have been proposed for organising these interactions. This paper focuses on a decentralised approach, while also considering two other possibilities – centralised and hierarchical. An architectural model is proposed and a prototype implementation with corresponding experimental results are subsequently presented and discussed

A generic holonic control architecture for heterogeneous multi-scale and multi-objective smart microgrids

Designing the control infrastructure of future “smart” power grids is a challenging task. Future grids will integrate a wide variety of heterogeneous producers and consumers that are unpredictable and operate at various scales. Information and Communication Technology (ICT) solutions will have to control these in order to attain global objectives at the macrolevel, while also considering private interests at the microlevel. This article proposes a generic holonic architecture to help the development of ICT control systems that meet these requirements. We show how this architecture can integrate heterogeneous control designs, including state-of-the-art smart grid solutions. To illustrate the applicability and utility of this generic architecture, we exemplify its use via a concrete proof-of-concept implementation for a holonic controller, which integrates two types of control solutions and manages a multiscale, multiobjective grid simulator in several scenarios. We believe that the proposed contribution is essential for helping to understand, to reason about, and to develop the “smart” side of future power grids

Scenarios for an autonomic micro smart grid

Autonomic computing is a bio-inspired vision elaborated to manage the increasing complexity of contemporary heterogeneous, large scale, dynamic computer systems. This paper presents a series of scenarios relative to micro smart grids – district-size “smart” electricity networks. These scenarios involve situations where autonomic management approaches could provide promising solutions. They therefore appear as short stories of a possible autonomic micro smart grid, that illustrate the concepts of autonomic computing as well as the potential behind this vision. At the same time, these scenarios reveal open issues as well as novel perspectives on the future of micro smart grids

AutoHome: an Autonomic Management Framework for Pervasive Home Applications

International audienceThis paper introduces the design of the AutoHome service oriented framework to simplify the development and runtime adaptive support of autonomic pervasive applications. To this end, we describe our novel open infrastructure for building and executing home applications. This includes the amalgamation of the two computing areas of Autonomics and Service Orientation, to produce a Component-based platform providing facilities including monitoring, touchpoints and other common autonomic services. This infrastructure uniquely blends the advantages of distributed autonomic control with global conflict management in a management hierarchy. We discuss this platform in terms of pervasive home systems and show how one would develop such a system for two examples of automated home applications: intruder detection and medical support respectively. Both applications were built within our framework and evaluated showing that the use of the framework introduces minimal overheads but provides many benefits. We then conclude by highlighting the contributions of AutoHome and a discussion about the lessons learned, limitations and future research directions

Exemplifying Conflict Resolution in Multi-Objective Smart Micro-Grids

Distributed autonomic management systems following contradictory objectives raise difficult design challenges. We proposed a generic architecture to address this concern and exemplified it via manager integration solutions for multi-objective micro-grids (low-tension networks of the size of a district). This demo showcases some of these sample implementations via the MisTiGriD simulation platform with the aim of inspiring designers facing similar challenges

Hierarchical Self-awareness and Authority for Scalable Self-integrating Systems

System self-integration from open sets of components provides the basis for open adaptability to unpredictable environments. Hierarchical architectures are essential for enabling such systems to scale, as they allow to compromise between processing detailed knowledge in parallel and coordinating parallel processes from a more abstract viewpoint; recursively. This position paper aims to bring to the fore the following key design aspect of such hierarchical systems: how should the authority of decision and action be assigned across hierarchical levels, with respect to the self-awareness capabilities of these levels, The difficulty lays in that all levels lack knowledge, which may be key to certain decisions, because lower levels have detailed knowledge but within a narrow scope (good for local customisation), and higher levels have a broader scope but no details (good for global coordination). We highlight the most obvious authority schemes available and discuss their advantages and shortcomings: top-down, bottom-up, and iterative (yoyo). We discuss three detailed application examples from our previous work on hierarchical systems, pointing-out the knowledge and authority schemes employed and the possible alternatives. This provides a basis for offering system designers the necessary understanding and tools for taking the appropriate decisions with respect to the distribution of self-awareness capabilities and authority of decision and action across hierarchical system levels