Gözde Ayşe Tataroğlu Özbulak
ABSTRACT
This PhD project proposes the theoretical and technological foundations of an approach for decentralized processing of streaming knowledge graphs, where autonomous reasoners may combine individual and collective processing of continuous data. These decentralized stream processors shall be capable of sharing not only data stream knowledge, but also processing duties, using collaboration and negotiation protocols. Moreover, commonly agreed semantic vocabularies will be used to address the high dynamicity of reasoners' knowledge and goals. The approach proposed in this project goes beyond previous works on stream reasoning, enabling the self-organization and coordination among distributed stream reasoners, based on techniques and principles inspired by Multi-Agent systems. On the one hand, it adds the ability to explicate processing goals, capabilities and knowledge, while on the other it exploits potential ways of interconnecting them in ways that expand their combined capacity/efficacy for managing highly dynamic flows of streaming knowledge. Through this approach, efficient local stream processors can establish cooperative processing schemes, respecting data privacy restrictions and data locality requirements through the exchange of streaming Knowledge Graphs.
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Index Terms
- Decentralized Stream Reasoning Agents
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