Synchronization of pulse-coupled biological oscillators
SIAM Journal on Applied Mathematics
Elements of information theory
Elements of information theory
Causal architecture, complexity and self-organization in time series and cellular automata
Causal architecture, complexity and self-organization in time series and cellular automata
Decentralized synchronization protocols with nearest neighbor communication
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
Blind construction of optimal nonlinear recursive predictors for discrete sequences
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Self-Organizing Networked Systems for Technical Applications: A Discussion on Open Issues
IWSOS '08 Proceedings of the 3rd International Workshop on Self-Organizing Systems
On Autonomy and Emergence in Self-Organizing Systems
IWSOS '08 Proceedings of the 3rd International Workshop on Self-Organizing Systems
A Method to Derive Local Interaction Strategies for Improving Cooperation in Self-Organizing Systems
IWSOS '08 Proceedings of the 3rd International Workshop on Self-Organizing Systems
On modeling of self-organizing systems
Autonomics '08 Proceedings of the 2nd International Conference on Autonomic Computing and Communication Systems
Quantitative Modeling of Self-organizing Properties
IWSOS '09 Proceedings of the 4th IFIP TC 6 International Workshop on Self-Organizing Systems
Quantitative Modeling of Self-organizing Properties
IWSOS '09 Proceedings of the 4th IFIP TC 6 International Workshop on Self-Organizing Systems
Methods for approximations of quantitative measures in self-organizing systems
IWSOS'11 Proceedings of the 5th international conference on Self-organizing systems
A light-weight approach for online state classification of self-organizing parallel systems
ARCS'11 Proceedings of the 24th international conference on Architecture of computing systems
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Since the entities composing self-organizing systems have direct access only to information provided by their vicinity, it is a non-trivial task for them to determine properties of the global system state. However, this ability appears to be mandatory for certain self-organizing systems in order to achieve an intended functionality. Based on Shannon's information entropy, we introduce a formal measure that allows to determine the entities' degree of global-state awareness. Using this measure, self-organizing systems and suitable system settings can be identified that provide the necessary information to the entities for achieving the intended system functionality. Hence, the proposed degree supports the evaluation of functional properties during the design and management of self-organizing systems. We show this by applying the measure exemplarily to a self-organizing sensor network designed for intrusion detection. This allows us to find preferable system parameter settings.