A Framework For Dynamic Updating In Component-based Software Systems

Setiap sistem perisian (software) perlu dikemas kini setiap masa bagi pelbagai alasan seperti penetapan pepijat (fixing bugs) Every software system needs to be updated over time for different reasons such as fixing bugs, upgrading its components, or adapting the system in response to its environment's changes

Combining Mobile Agents and Process-based Coordination to Achieve Software Adaptation

We have developed a model and a platform for end-to-end run-time monitoring, behavior and performance analysis, and consequent dynamic adaptation of distributed applications. This paper concentrates on how we coordinate and actuate the potentially multi-part adaptation, operating externally to the target systems, that is, without requiring any a priori built-in adaptation facilities on the part of said target systems. The actual changes are performed on the fly onto the target by communities of mobile software agents, coordinated by a decentralized process engine. These changes can be coarse-grained, such as replacing entire components or rearranging the connections among components, or fine-grained, such as changing the operational parameters, internal state and functioning logic of individual components. We discuss our successful experience using our approach in dynamic adaptation of a large-scale commercial application, which requires both coarse and fine grained modifications

Using Process Technology to Control and Coordinate Software Adaptation

We have developed an infrastructure for end-to-end run-time monitoring, behavior/performance analysis, and dynamic adaptation of distributed software. This infrastructure is primarily targeted to pre-existing systems and thus operates outside the target application, without making assumptions about the target's implementation, internal communication/computation mechanisms, source code availability, etc. This paper assumes the existence of the monitoring and analysis components, presented elsewhere, and focuses on the mechanisms used to control and coordinate possibly complex repairs/reconfigurations to the target system. These mechanisms require lower level effectors somehow attached to the target system, so we briefly sketch one such facility (elaborated elsewhere). Our main contribution is the model, architecture, and implementation of Workflakes, the decentralized process engine we use to tailor, control, coordinate, etc. a cohort of such effectors. We have validated the Workflakes approach with case studies in several application domains. Due to space restrictions we concentrate primarily on one case study, briefly discuss a second, and only sketch others

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