Masking Sensitive Data in Self-Organized Smart Region Orchestration

Abstract

Decentralized coordination is widely seen as a promising approach for coping with ever-growing complexity in large-scale cyber-physical systems. Automated controllability in turn is necessary for installing sustainability in smart regions and cities. Ambient algorithmic support for decentralized process coordination will ease collaboration for a better utilization of available resources. Negotiation among software agents in such algorithms inevitably also demand an exchange of information; containing either plain information on local processes, resources or production states, or allow for deriving at least partial information. We analyze two use cases: virtual power plants for future smart grid coordination and automated network formation for smart regions. Based on the requirements of the algorithmic perspective as well as of the domain specific privacy needs, we derive recommendations for a possible solution that brings together these opposing perspectives.