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This report presents three reference architectures that can be used as architectural blueprints for applications of three different system classes. The first system class comprises applications in the field of energy management; the second one contains applications in the domain of desktop grid computing; the third system class contains multi-user multi-display applications. Because applications in the scope of energy management are safety-critical and desktop grid computing applications have to cope with a variety of self-interested participants, applications of these domains have in common that they can increase their robustness and efficiency by considering the trustworthiness of participants. Multi-user multi-display applications have to assess the social relationships between its users and adapt based on trustworthiness facets such as transparency and controllability. Therefore, the reference architectures given here are based on a multi-agent system that provides functionality for the utilization of trust. Experiences with participants can be stored and evaluated so that trust can be derived and incorporated into the applications. Additionally, the platform provides the basis for open systems in which agents enter and leave dynamically.
The Trusted Desktop Grid (TDG) is a self-organised, agent-based organisation, where agents perform computational tasks for others to increase their performance. In order to establish a fair distribution and provide counter-measures against egoistic or malicious elements, technical trust is used. A fully self-organised approach can run into disturbed states such as a trust breakdown of the system that lead to unsatisfying system performance although the majority of participants is still behaving well. We previously introduced an additional system-wide control loop to detect and alleviate disturbed situations. Therefore, we describe an Observer/Controller loop at system level that monitors the system status and intervenes if necessary. This paper focuses on the controller part which instantiates norms as reaction to observed suspicious situations. We demonstrate the benefit of our approach within a Repast-based simulation of the TDG. Therein, the impact of disturbances on the system performance is decreased significantly and the time to recover is shortened.
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.
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.
Improving Reliability and Endurance Using End-to-End Trust in Distributed Low-Power Sensor Networks
(2015)
