Organic Computing (OC) and Autonomic Computing (AC) systems are distinct from conventional systems through their ability to self-adapt and to self-organise. However, these properties are just means and not the end. What really makes OC and AC systems useful is their ability to survive in a real world, i.e. to recover from disturbances and attacks from the outside world. This property is called robustness. In this paper, we propose a metric to gauge robustness in order to be able to quantitatively compare the effectiveness of different self-organising and self-adaptive system designs with each other. In the following, we apply this metric to three experimental application scenarios and discuss their usefulness.

In this paper, we present a realtime fluid simulation based on cellular automata (CAs). The main goal is to demonstrate the performance and extensibility of this approach. To show this, we created a fluid simulation and extended it by simulating different kinds of fluids at the same time with effects like oil foating on water and a focus on short computation time. This makes the simulation interesting for games in VR. In our simulation, we had a high framerate of 100 FPS for a CA running on the CPU with 1763 cells due to parallelization and optimization.

Open, distributed systems face the challenge to maintain an appropriate operation performance even in the presence of bad behaving or malicious agents.A promising mechanism to counter the resulting negative impact of such agents is to establish technical trust.In this paper, we investigate strategies to improve the efficiency of trust mechanisms regarding the isolation of undesired participants by means of reputation and accusation techniques.We demonstrate the potential benefit of the developed techniques within simulations of a Trusted Desktop Computing Grid. TRUSTED DESKTOP GRIDWe use an open, distributed Trusted Desktop Grid (TDG) as application scenario to show and prove the effective application of distributed algorithms as well as Organic Computing (Müller-Schloer et al., 2011) methods.In this scenario, we use an open and heterogeneous Multi-Agent System (MAS) and we do not assume benevolence.The agents in the system cooperate to gain an advantage.The mechanism determining this cooperation is Trust.Because of the openness of the system, different agents may try to exploit it.They may be uncooperative, malfunctioning or even malicious.An agent, which acts on behalf of the user, is submitting jobs it wants to have calculated (Klejnowski, 132

Information and communication technology witnesses a raise of open, distributed systems that consist of various heterogeneous elements. Within such an environment, individual elements have to efficiently fulfil their goals, which may require cooperation with others. As a consequence, a variety of threats appears that need to be handled and circumvented in the entity’s behaviour. One major technical approach to provide a working environment for such systems is to introduce technical trust. In this paper, we present a basic threat model that comprises the most important challenges in this context – related to the basic system and the trust management, respectively. In order to illustrate the particular hazardous aspects, we discuss a Desktop Computing Grid application as scenario.

Distributed grid systems offer possible benefits in terms of fast computation of tasks. This is accompanied by potential drawbacks due to their openness, the heterogeneity of participants, and the unpredictability of agent behaviour, since agents have to be considered as black-boxes. The utilisation of technical trust within adaptive collaboration strategies has been shown to counter negative effects caused by these characteristics. A major challenge in this context is the presence of colluding attackers that try to exploit or damage the system in a coordinated fashion. Therefore, this paper presents a novel approach to detect and isolate such colluding attackers. The concept is based on observations of interaction patterns and derives a classification of agent communities. Within the evaluation, we demonstrate the benefit of the approach and highlight the highly reliable classification.

In this paper, we present our efforts towards creating a deliberately sickening virtual reality (VR) game. Based on a considerable number of tests, we can show that games can be enjoyable despite experienced adverse effects that arise from frequent acceleration in VR and additional post-processing distortions of the rendered scene. We briefly explain the rationale that drove us to take these measures, details about their realisation and results from a questionary-based user evaluation.

Self-organized systems typically consist of distributed autonomous entities. An increasing part of such systems is characterized by openness and heterogeneity of participants. For instance, open desktop computing grids provide a framework for unrestrictedly joining in. However, openness and heterogeneity present severe challenges to the overall system’s stability and efficiency since uncooperative and even malicious participants are free to join. A promising solution for this problem is to introduce technical trust as a basis; however, in turn, the utilization of trust opens space for negative emergent behavior. This article introduces a system-wide observation and control loop that influences the self-organized behavior to provide a performant and robust platform for benevolent participants. Thereby, the observation part is responsible for gathering information and deriving a system description. We introduce a graph-based approach to identify groups of suspicious or malicious agents and demonstrate that this clustering process is highly successful for the considered stereotype agent behaviors. In addition, the controller part guides the system behavior by issuing norms that make use of incentives and sanctions. We further present a concept for closing the control loop and show experimental results that highlight the potential benefit of establishing such a control loop.

Desktop Computing Grids provide a framework for joining in and sharing resources with others. The result is a self-organised system that typically consists of numerous distributed autonomous entities. Openness and heterogeneity postulate severe challenges to the overall system’s stability and efficiency since uncooperative and even malicious participants are free to join. In this paper, we present a concept for identifying agents with exploitation strategies that works on a system-wide analysis of trust and work relationships. Afterwards, we introduce a system-wide control loop to isolate these malicious elements using a norm-based approach – due to the agents’ autonomy, we have to build on indirect control actions. Within simulations of a Desktop Computing Grid scenario, we show that the intelligent control loop works highly successful: these malicious elements are identified and isolated with a low error rate. We further demonstrate that the approach results in a significant increa se of utility for all participating benevolent agents.

We present an interactive simulation of Swarm Grammars (SGs). SGs are an extension of L-Systems, where symbols of the production system are considered agents, whereas the given production rules determine their differentiation or re-production. Assigning boid properties to the SG agents yields spatial dynamics apt to building structures in space and to col-laborate stigmergically. In the presented interactive simula-tion, we put an emphasis on accessible interactive visuals for shaping the initial configuration of the simulation, to program the agents ’ perceptual and productive behavioural abilities, to dynamically drive developmental stages and to fine-tune vi-sual structural properties such as colouring and scaling of the utilised developmental building blocks. Our system has been successfully deployed to promote swarm dynamics and de-velopmental processes as important aspects of Artificial Life in a playful way. We present results from deploying the sim-ulation in the context of an event to promote STEM research among high-school girls.

Grid Computing Systems are examples for open systems with heterogeneous and potentially malicious entities. Such systems can be controlled by system-wide intelligent control mechanisms working on trust relationships between these entities. Trust relationships are based on ratings among individual entities and represent system-wide information. In this paper, we propose to utilise a normative approach for the system-level control loop working on basis of these trust values. Thereby, a normative approach does not interfere with the entities’ autonomy and handles each system as black box. Implicit rules already existing in the system are turned into explicit norms – which in turn are becoming mandatory for all entities. This allows the distributed systems to derive the desired behaviour and cooperate in reaction to disturbed situations such as attacks.

Dynamic MANET On-demand (AODVv2) routing, formerly known as DYMO, is a routing protocol especially designed for wireless, multi hop networks. AODVv2 determines routes in a network in an on-demand fashion. In this paper we present a formal model of AODVv2, using the process algebra AWN. The benefit of this is two-fold: (a) the given specification is definitely free of ambiguities; (b) a formal and rigorous analysis of the routing protocol is now feasible. To underpin the latter point we also present a first analysis of the AODVv2 routing protocol. On the one hand we show that some of the problems discovered in the AODV routing protocol, the predecessor of AODVv2, have been addressed and solved. On the other hand we show that other limitations still exist; an example is the establishment of non-optimal routes. Even worse, we locate shortcomings in the AODVv2 routing protocol that do not occur in AODV. This yields the conclusion that AODVv2 is not necessarily better than AODV.