Adaptation of Asynchronously Communicating Software

International audienceSoftware adaptation techniques aim at generating new components called adapters, which make a set of services work correctly together by compensating for existing mismatch. Most approaches assume that services interact synchronously using rendez-vous communication. In this paper, we focus on asynchronous communication, where services interact exchanging messages via buffers. We overview a method for automatically generating adapters in such asynchronous environments

Adaptation of Asynchronously Communicating Software

International audienceSoftware adaptation techniques aim at generating new components called adapters, which make a set of services work correctly together by compensating for existing mismatch. Most approaches assume that services interact synchronously using rendez-vous communication. In this paper, we focus on asynchronous communication, where services interact exchanging messages via buffers. We overview a method for automatically generating adapters in such asynchronous environments

Stability-Based Adaptation of Asynchronously Communicating Software

International audienceSoftware Adaptation aims at composing incompatible black-box components or services (peers) whose individual functionality is as required for the new system. Adaptation techniques aim at automatically generating new components called adapters. An adapter works as an orchestrator and makes the involved peers work correctly together by receiving all messages exchanged in the system and by correcting mis-match between them. A challenging issue in this area is to consider that peers are described with (possibly cyclic) behavioural models and interact asynchronously, that is, exchanging messages via message buffers. The synthesis of adapters in this context is difficult because the composition of peers may result in infinite systems. In this paper, we propose new adaptation techniques, which rely on a property of communicating systems called stability. Stability aims at verifying whether a communicating system exhibits the same observational behaviour from a certain buffer bound on. We also provide adapter generation techniques using process algebra encodings and enumerative analysis techniques

Model-Based Adaptation of Software Communicating via FIFO Buffers

Software Adaptation is a non-intrusive solution for composing black-box components or services (peers) whose individual functionality is as required for the new system, but that present interface mismatch, which leads to deadlock or other undesirable behaviour when combined. Adaptation techniques aim at automatically generating new components called adapters. All the interactions among peers pass through the adapter, which acts as an orchestrator and makes the involved peers work correctly together by compensating for mismatch. Most of the existing solutions in this field assume that peers interact synchronously using rendezvous communication. However, many application areas rely on asynchronous communication models where peers interact exchanging messages via buffers. Generating adapters in this context becomes a difficult problem because peers may exhibit cyclic behaviour, and their composition often results in infinite systems. In this paper, we present a method for automatically generating adapters in asynchronous environments where peers interact using FIFO buffers.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Stability of Asynchronously Communicating Systems

Recent software is mostly constructed by reusing and composing existing components. Software components are usually stateful and therefore described using behavioral models such as finite state machines. Asynchronous communication is a classic interaction mechanism used for such software systems. However, analysing communicating systems interacting asynchronously via reliable FIFO buffers is an undecidable problem. A typical approach is to check whether the system is bounded, and if not, the corresponding state space can be made finite by limiting the presence of communication cycles in behavioral models or by fixing buffer sizes. In this paper, we focus on infinite systems and we do not restrict the system by imposing any arbitrary bounds. We introduce a notion of stability and prove that once the system is stable for a specific buffer bound, it remains stable whatever larger bounds are chosen for buffers. This enables us to check certain properties on the system for that bound and to ensure that the system will preserve them whatever larger bounds are used for buffers. We also prove that computing this bound is undecidable but show how we succeed in computing these bounds for many typical examples using heuristics and equivalence checking

ECOSENSUS: developing collaborative learning systems for stakeholding development in environmental planning

ECOSENSUS *(Electronic/Ecological Collaborative Sensemaking Support System) investigates the socio-technological issues around developing collaboration tools for participatory environmental decision making amongst (a) marginalised natural resource users, (b) professional 'experts' from different countries, and (c) key decision makers associated with managing ecosystems. An integral activity is the production of open content learning resources to support stakeholders in facilitating distributed environmental decision making. This involves the integrated use of three open source software tools: Moodle (online course management), Compendium (dialogue mapping) and uDig (user friendly desktop/internet GIS). In the first ECOSENSUS-1 phase, the pilot collaborative effort has been focused on supporting stakeholders in developing adaptive management plans for the Rupununi Wetlands in southern Guyana, a region rich in flora and fauna but also under intense pressure to expand the exploitation of its natural resources, including timber, gold, and commercially viable fish species. Results of the ECOSENSUS-1 are briefly described along with some preliminary notes on the current ECOSENUS-2 phase of associated research in Guyana supported by an additional grant from DEFRA. The paper prompts questions on how ECOSENSUS can feed into wider open source course development using the LabSpace on the OpenLearn project

The LAB@FUTURE Project - Moving Towards the Future of E-Learning

This paper presents Lab@Future, an advanced e-learning platform that uses novel Information and Communication Technologies to support and expand laboratory teaching practices. For this purpose, Lab@Future uses real and computer-generated objects that are interfaced using mechatronic systems, augmented reality, mobile technologies and 3D multi user environments. The main aim is to develop and demonstrate technological support for practical experiments in the following focused subjects namely: Fluid Dynamics - Science subject in Germany, Geometry - Mathematics subject in Austria, History and Environmental Awareness – Arts and Humanities subjects in Greece and Slovenia. In order to pedagogically enhance the design and functional aspects of this e-learning technology, we are investigating the dialogical operationalisation of learning theories so as to leverage our understanding of teaching and learning practices in the targeted context of deployment

Closed loop interactions between spiking neural network and robotic simulators based on MUSIC and ROS

In order to properly assess the function and computational properties of simulated neural systems, it is necessary to account for the nature of the stimuli that drive the system. However, providing stimuli that are rich and yet both reproducible and amenable to experimental manipulations is technically challenging, and even more so if a closed-loop scenario is required. In this work, we present a novel approach to solve this problem, connecting robotics and neural network simulators. We implement a middleware solution that bridges the Robotic Operating System (ROS) to the Multi-Simulator Coordinator (MUSIC). This enables any robotic and neural simulators that implement the corresponding interfaces to be efficiently coupled, allowing real-time performance for a wide range of configurations. This work extends the toolset available for researchers in both neurorobotics and computational neuroscience, and creates the opportunity to perform closed-loop experiments of arbitrary complexity to address questions in multiple areas, including embodiment, agency, and reinforcement learning

The 3DMA Middleware for Mobile Applications

Mobile devices have received much research interest in re- cent years. Mobility raises new issues such as more dynamic context, limited computing resources, and frequent disconnections. To handle these issues, we propose a middleware, called 3DMA, which introduces three requirements, 1) distribution, 2) decoupling and 3) decomposition. 3DMA uses a space based middleware approach combined with a set of workers which are able to act on the users behalf either to reduce load on the mobile device, or to support disconnected behavior. In order to demonstrate aspects of the middleware architecture we consider the development of a commonly used mobile application