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

Dynamic Adaptation of Temporal Event Correlation Rules

Temporal event correlation is essential to realizing self-managing distributed systems. Autonomic controllers often require that events be correlated across multiple components using rule patterns with timer-based transitions, e.g., to detect denial of service attacks and to warn of staging problems with business critical applications. This short paper discusses automatic adjustment of timer values for event correlation rules, in particular compensating for the variability of event propagation delays due to factors such as contention for network and server resources. We describe a corresponding Management Station architecture and present experimental studies on a testbed system that suggest that this approach can produce results at least as good as an optimal fixed setting of timer values

Kinesthetics eXtreme: An External Infrastructure for Monitoring Distributed Legacy Systems

Autonomic computing - self-configuring, self-healing, self-optimizing applications, systems and networks - is widely believed to be a promising solution to ever-increasing system complexity and the spiraling costs of human system management as systems scale to global proportions. Most results to date, however, suggest ways to architect new software constructed from the ground up as autonomic systems, whereas in the real world organizations continue to use stovepipe legacy systems and/or build 'systems of systems' that draw from a gamut of new and legacy components involving disparate technologies from numerous vendors. Our goal is to retrofit autonomic computing onto such systems, externally, without any need to understand or modify the code, and in many cases even when it is impossible to recompile. We present a meta-architecture implemented as active middleware infrastructure to explicitly add autonomic services via an attached feedback loop that provides continual monitoring and, as needed, reconfiguration and/or repair. Our lightweight design and separation of concerns enables easy adoption of individual components, as well as the full infrastructure, for use with a large variety of legacy, new systems, and systems of systems. We summarize several experiments spanning multiple domains

Adaptive Synchronization of Semantically Compressed Instructional Videos for Collaborative Distance Learning

The increasing popularity of online courses has highlighted the need for collaborative learning tools for student groups. In addition, the introduction of lecture videos into the online curriculum has drawn attention to the disparity in the network resources available to students. We present an e-Learning architecture and adaptation model called AI2TV (Adaptive Interactive Internet Team Video), which allows groups of students to collaboratively view a video in synchrony. AI2TV upholds the invariant that each student will view semantically equivalent content at all times. A semantic compression model is developed to provide instructional videos at different level-of-details to accommodate dynamic network conditions and usersäó» system requirements. We take advantage of the semantic compression algorithmäó»s ability to provide different layers of semantically equivalent video by adapting the client to play at the appropriate layer that provides the client with the richest possible viewing experience. Video player actions, like play, pause and stop, can be initiated by any group member and and the results of those actions are synchronized with all the other students. These features allow students to review a lecture video in tandem, facilitating the learning process. Experimental trials show that AI2TV successfully synchronizes instructional videos for distributed students while concurrently optimizing the video quality, even under conditions of fluctuating bandwidth, by adaptively adjusting the quality level for each student while still maintaining the invariant

A Uniform Programming Abstraction for Effecting Autonomic Adaptations onto Software Systems

Most general-purpose work towards autonomic or self-managing systems has emphasized the front end of the feedback control loop, with some also concerned with controlling the back end enactment of runtime adaptations but usually employing an effector technology peculiar to one type of target system. While completely generic 'one size fits all' effector technologies seem implausible, we propose a general-purpose programming model and interaction layer that abstracts away from the peculiarities of target-specific effectors, enabling a uniform approach to controlling and coordinating the low-level execution of reconfigurations, repairs, micro-reboots, etc

A Uniform Programming Abstraction for Effecting Autonomic Adaptations onto Software Systems

Most general-purpose work towards autonomic or self-managing systems has emphasized the front end of the feedback control loop, with some also concerned with controlling the back end enactment of runtime adaptations -- but usually employing an effector technology peculiar to one type of target system. While completely generic "one size fits all" effector technologies seem implausible, we propose a general purpose programming model and interaction layer that abstracts away from the peculiarities of target specific effectors,enabling a uniform approach to controlling and coordinating the low-level execution of reconfigurations, repairs,micro-reboots, etc

Towards Pervasive Supervision for Autonomic Systems

Abstract One of the key motivations for the provisioning of autonomic communication features in next generation services is to reduce the need of human inference for management tasks. This however means essentially that system control is delegated to the system itself, i.e., the system operator gives up control to a certain extent. The consequence is that autonomic systems might deviate from intended behavior, may show inconsistent or unwanted states and behavior. We propose an approach to develop control structures complementary to distributed, heterogeneous services. We concentrate on necessary properties of those control structures, and furthermore on issues like selfapplicability and self-evolution

Retrofitting Autonomic Capabilities onto Legacy Systems

Autonomic computing - self-configuring, self-healing, self-optimizing applications, systems and networks - is a promising solution to ever-increasing system complexity and the spiraling costs of human management as systems scale to global proportions. Most results to date, however, suggest ways to architect new software constructed from the ground up as autonomic systems, whereas in the real world organizations continue to use stovepipe legacy systems and/or build 'systems of systems' that draw from a gamut of disparate technologies from numerous vendors. Our goal is to retrofit autonomic computing onto such systems, externally, without any need to understand, modify or even recompile the target system's code. We present an autonomic infrastructure that operates similarly to active middleware, to explicitly add autonomic services to pre-existing systems via continual monitoring and a feedback loop that performs, as needed, reconfiguration and/or repair. Our lightweight design and separation of concerns enables easy adoption of individual components, independent of the rest of the full infrastructure, for use with a large variety of target systems. This work has been validated by several case studies spanning multiple application domains

An Event Monitor and Response Framework Based on the WSLogA Architecture

Web services provide organizations with a powerful infrastructure by which information and products may be distributed, but the task of supporting Web service systems can be difficult due to the complex nature of environment configuration and operation. Tools are needed to monitor and analyze such Enterprise environments so that appropriate engineering, quality control, or business activities can be pursued. This investigation resulted in the development of a software development kit, the WSLogA Framework, which is inspired by the vision of Cruz et al. (2003, 2004). The WSLogA Framework provides distributed Enterprise systems with a platform for comprehensive information capture and environment management. Five component groups are intended for employment to enable integrated workflows addressing monitoring and response activities, but these components may also be used individually to facilitate the phased integration of the WSLogA Framework into existing environments. The WSLogA Framework\u27s design is portable across technology platforms (e.g., Java and .NET) and a variety of technologies may be substituted for the provided implementations to address unique system architectures. The WSLogA Framework supersedes existing logging and monitoring solutions in terms of both capability and intent. Applications based on the WSLogA Framework have an internal, real-time view of their operation and may adjust their environment based on the information provided by events related to their or system activities. The WSLogA Framework is intended as a software development kit around which system functionality may be organized and implemented, which makes the WSLogA Framework an architectural peer or complement to traditional application frameworks such as Spring\u27s Web module. WSLogA Framework based systems should be envisioned as information appliance elements rather than traditionally scoped applications or services