Towards adaptive multi-robot systems: self-organization and self-adaptation

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.The development of complex systems ensembles that operate in uncertain environments is a major challenge. The reason for this is that system designers are not able to fully specify the system during specification and development and before it is being deployed. Natural swarm systems enjoy similar characteristics, yet, being self-adaptive and being able to self-organize, these systems show beneficial emergent behaviour. Similar concepts can be extremely helpful for artificial systems, especially when it comes to multi-robot scenarios, which require such solution in order to be applicable to highly uncertain real world application. In this article, we present a comprehensive overview over state-of-the-art solutions in emergent systems, self-organization, self-adaptation, and robotics. We discuss these approaches in the light of a framework for multi-robot systems and identify similarities, differences missing links and open gaps that have to be addressed in order to make this framework possible

A deliberative model for self-adaptation middleware using architectural dependency

A crucial prerequisite to externalized adaptation is an understanding of how components are interconnected, or more particularly how and why they depend on one another. Such dependencies can be used to provide an architectural model, which provides a reference point for externalized adaptation. In this paper, it is described how dependencies are used as a basis to systems' self-understanding and subsequent architectural reconfigurations. The approach is based on the combination of: instrumentation services, a dependency meta-model and a system controller. In particular, the latter uses self-healing repair rules (or conflict resolution strategies), based on extensible beliefs, desires and intention (EBDI) model, to reflect reconfiguration changes back to a target application under examination

Biologically Inspired Near Extinct System Reconstruction

Recovery software system operations from a state of extensive damage without human intervention is a challenging problem as it may need to be based on a different infrastructure from the one that the system was originally designed for and deployed on (i.e., computational and communication devices) and significant reorganization of system functionalities. In this paper, we introduce a bio-inspired approach for reconstructing nearly extinct complex software systems. Our approach is based on encoding a computational DNA (co-DNA) of a system and computational analogues of biological processes to enable the transmission of co-DNA over computational devices and, through it, the transformation of these devices into system cells that can realise chunks of the system functionality, and spread further its reconstruction process

A nature inspired multi-agent framework for autonomic service management in ubiquitous computing environments

This paper describes the design of a scalable biomimetic framework that addresses several key issues of autonomous agents in the management domain of complex Ubiquitous Service-Oriented Networks. We propose an autonomous network service management platform - SwarmingNet, which is motivated by observations of the swarm intelligence in biological systems (e.g., Termite, Ant/Bees colonies, or Locusts). In this SwarmingNet architecture, the required network service processes are implemented by a group of highly diverse and autonomie objects. These objects are called TeleService Solons (TSSs) as elements of TeleService Holons (TSHs), analogue to individual insects as particles of the whole colony. A single TSS is only able to pursue simple behaviors and interactions with local neighbors, however, a group of TSSs have the capabilities of fulfilling the complex tasks relating to service discovery and service activation. We simulate a service configuration process for Multimedia Messaging Service, and a performance comparison between the bio-agents and normal agents is analyzed. Finally, we conclude that through bio-swarming intelligence behaviors, this infrastructure develops the enhanced self-X capabilities which give IP networks advantages of instinctive compatibility, efficiency and scalability

08031 Abstracts Collection -- Software Engineering for Self-Adaptive Systems

From 13.01. to 18.01.2008, the Dagstuhl Seminar 08031 ``Software Engineering for Self-Adaptive Systems\u27\u27 was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

Biologically Inspired Self-Healing Software System Architecture

Self-healing capabilities have begun to emerge as an interesting and potentially valuable property of software systems. Self-healing characteristic enables software systems to continuously and dynamically monitor, diagnose, and adapt itself after a failures has occur in their components. Adding such characteristic into existing software systems is immensely useful and valuable for allowing them to recover from failures. However, developing such self-healing software systems is a significant challenge. The nature introduces to us unforeseen concepts in terms of presenting biological systems that have the ability to handle its abnormal conditions. Based on this observation, this thesis presents self healing architecture for software system based on one of the biological processes that have the ability to heal by itself (the wound-healing process). The self-healing architecture provides software systems the ability to handle anomalous conditions that appear among its components. The presented architecture is divided into to layers, functional and healing layer. In the functional layer, the components of the system provide its services without any disruptions. The component is considered as faulty component if it fails to provide its services. The healing layer aims to heal the faulty component and return it to the running system without the awareness of the user. The presented self-healing software system is formally described to prove its functionality. Set-theoretic and Finite State Machine (FSM) is introduced. A prototype for the presented architecture has been implemented using Java language. Java objects are considered as the system components. The modules of the healing layer in the selfhealing architecture have been implemented into Java classes. An object from the module class will be created to perform its task for the healing process. The thesis concludes with recommendations for future works in this area and enhancement of the presented architecture

Self-organising agent communities for autonomic resource management

The autonomic computing paradigm addresses the operational challenges presented by increasingly complex software systems by proposing that they be composed of many autonomous components, each responsible for the run-time reconfiguration of its own dedicated hardware and software components. Consequently, regulation of the whole software system becomes an emergent property of local adaptation and learning carried out by these autonomous system elements. Designing appropriate local adaptation policies for the components of such systems remains a major challenge. This is particularly true where the system’s scale and dynamism compromise the efficiency of a central executive and/or prevent components from pooling information to achieve a shared, accurate evidence base for their negotiations and decisions.In this paper, we investigate how a self-regulatory system response may arise spontaneously from local interactions between autonomic system elements tasked with adaptively consuming/providing computational resources or services when the demand for such resources is continually changing. We demonstrate that system performance is not maximised when all system components are able to freely share information with one another. Rather, maximum efficiency is achieved when individual components have only limited knowledge of their peers. Under these conditions, the system self-organises into appropriate community structures. By maintaining information flow at the level of communities, the system is able to remain stable enough to efficiently satisfy service demand in resource-limited environments, and thus minimise any unnecessary reconfiguration whilst remaining sufficiently adaptive to be able to reconfigure when service demand changes