Observation and Control of Organic Systems

Tomforde, Sven; Prothmann, Holger; Branke, Jürgen; Hähner, Jörg; Mnif, Moez; Müller-Schloer, Christian; Richter, Urban; Schmeck, Hartmut

doi:10.1007/978-3-0348-0130-0_21

Cited by 74 publications

(30 citation statements)

References 13 publications

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“…4.7, we present our concept of the Norm Manager (NM), which uses the common Observer-Controller pattern [7]. The complete control loop implemented by the Observer-Controller component helps to mitigate effects of attacks to the TDG and allows a better fulfilment of the system goals.…”

Section: Higher-level Norm Managermentioning

confidence: 99%

“…As a consequence, the benefit for all participants decreases significantly and the system itself becomes dysfunctional to a certain degree. To counteract such events and to further guide the self-organised behaviour, this chapter introduces a concept working at system-level without interfering with the agents' autonomy: A higher-level observation and control loop following the general Observer/Controller pattern [7] of Organic Computing is proposed and applied to the TDG. This loop derives an appropriate situation description in the first place that covers abstract information about work and trust relationships among agents, augmented by figures reflecting detected patterns (e.g.…”

Section: Introductionmentioning

confidence: 99%

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Normative Control: Controlling Open Distributed Systems with Autonomous Entities

Kantert

Edenhofer

Tomforde

et al. 2016

Trustworthy Open Self-Organising Systems

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Open distributed systems consisting of a potentially large set of autonomous entities might not be controllable directly. More precisely, standard control interventions, such as altering parameters and behaviour, are not possible due to the entity's autonomy. However, indirect control using socio-inspired mechanisms can be applied to guide the system's behaviour and influence the distributed entities using sanctions and incentives. The demanded behaviour as well as the corresponding sanctions and incentives are coded as norms and generated in response to perceived environmental and internal conditions. Such a norm is issued by centralised authorities. Norm violation is monitored using a higher-level observer in a distributed manner. After an introduction and motivation for using social mechanisms in technical systems, we present a novel normative control loop establishing the afore-described concept within a Trusted Desktop Grid scenario. The evaluation demonstrates the potential benefit in terms of an increased system robustness and fast recovery from attack states.

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Section: Higher-level Norm Managermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Normative Control: Controlling Open Distributed Systems with Autonomous Entities

Kantert

Edenhofer

Tomforde

et al. 2016

Trustworthy Open Self-Organising Systems

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“…Only if the new model specifications satisfy all safety constraints considered as part of the simulation process, are they eventually fed into level 1. The general design concept as illustrated by Figure 1 is explained in detail in Tomforde et al (2011). Besides robotics, it has been successfully applied to domains such as control of urban traffic lights, see Prothmann et al (2011), adaptation of data communication protocols, see Tomforde et al (2009Tomforde et al ( , 2010, or cloud computing environments, see Sommer et al (2016).…”

Section: Observer/controller Architecturementioning

confidence: 99%

“…Several studies in Organic Computing have emphasized the adequacy of Learning Classifier Systems (LCS) as a comprehensive framework to support the self-adaptation process based on the observer/controller design concept, see, for example, Richter (2009) and Tomforde et al (2011). Holland (1975 presented the first LCS that combined basic rule-based reactive behavior with an evolutionary component to evolve and improve the rule base.…”

Section: Learning Classifier Systemsmentioning

confidence: 99%

An Organic Computing Approach to Self-Organizing Robot Ensembles

2016

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Similar to the Autonomous Computing initiative, which has mainly been advancing techniques for self-optimization focusing on computing systems and infrastructures, Organic Computing (OC) has been driving the development of system design concepts and algorithms for self-adaptive systems at large. Examples of application domains include, for instance, traffic management and control, cloud services, communication protocols, and robotic systems. Such an OC system typically consists of a potentially large set of autonomous and self-managed entities, where each entity acts with a local decision horizon. By means of cooperation of the individual entities, the behavior of the entire ensemble system is derived. In this article, we present our work on how autonomous, adaptive robot ensembles can benefit from OC technology. Our elaborations are aligned with the different layers of an observer/controller framework, which provides the foundation for the individuals' adaptivity at system design-level. Relying on an extended Learning Classifier System (XCS) in combination with adequate simulation techniques, this basic system design empowers robot individuals to improve their individual and collaborative performances, e.g., by means of adapting to changing goals and conditions. Not only for the sake of generalizability but also because of its enormous transformative potential, we stage our research in the domain of robot ensembles that are typically comprised of several quad-rotors and that organize themselves to fulfill spatial tasks such as maintenance of building facades or the collaborative search for mobile targets. Our elaborations detail the architectural concept, provide examples of individual self-optimization as well as of the optimization of collaborative efforts, and we show how the user can control the ensembles at multiple levels of abstraction. We conclude with a summary of our approach and an outlook on possible future steps.

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“…A system-wide observation and control of a TDG based on norms demands for a higher-levelled norm manager (NM) -which we realise as instance of Organic Computing's [2] design pattern: an Observer/Controller structure [3]. The goal of this NM is to improve the system's robustness.…”

Section: Introductionmentioning

confidence: 99%

Robust Self-Monitoring in Trusted Desktop Grids for Self-Configuration at Runtime

Kantert

Edenhofer

Tomforde

et al. 2014

2014 IEEE Eighth International Conference on Self-Adaptive and Self-Organizing Systems Workshops

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A Trusted Desktop Grid System (TDG) is a platform for autonomous agents to share their computing resources based on trust relationships. Thereby, agents that only use the system without a fair participation are considered as malicious. Typically, the effects of active malicious agents and high-load situations of the TDG are similar -calling for appropriate approaches to distinguish them and, thus, allowing for counter measures to attacks. In this paper, we investigate the effect of high load to our measurements and present a concept for filtering our metrics. The evaluation demonstrated that we can normalise our metrics under high load to detect attacks with a high certainty using system-wide metrics.

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Observation and Control of Organic Systems

Cited by 74 publications

References 13 publications

Normative Control: Controlling Open Distributed Systems with Autonomous Entities

Normative Control: Controlling Open Distributed Systems with Autonomous Entities

An Organic Computing Approach to Self-Organizing Robot Ensembles

Robust Self-Monitoring in Trusted Desktop Grids for Self-Configuration at Runtime

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