Distributed Artificial Intelligence on the Edge

The future of computation.

Projects

All Machine Learning Edge Computing Other

MEC AI

Predictive & prescriptive analytics on MEC system control.

Bayesian Trusted Edge Analytics

Distributed data analysis for IoT applications.

Recent Posts

3 min read blog

The history of software architectures is a history of the ebb and flow of centralization and distribution. Centralization requires good network connections while promising simplicity, homogeneity, and ease of management. Distribution offers robustness and potentially unbounded scalability, but has high demands on design, especially in terms of security. Currently, the discussion is on sensor devices and the Cloud. Sensors measure the environment, people, movement, temperature, any of a million potential attributes of the world around us.

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Selected Publications

Edge computing in Internet of Things enhances application execution by retrieving cloud resources to the close prox- imity of resource-constrained end devices at the edge and by enabling task offloading from end devices to the edge. In this paper, edge computing platforms are extended into the data producing end devices, including wireless sensor network nodes and smart- phones, with mobile agents. Mobile agents operate as a multi-agent system on the opportunistic network of heterogeneous end devices, where the benefits include autonomous, asynchronous and the adaptive execution and relocation of application-specific tasks, while taking into account local resource availability. …
In Web Intelligence, 2018

Recent Publications

. Energy Efficient Opportunistic Edge Computing for the Internet of Things. In Web Intelligence, 2018.

Contact

  • edgeai@lists.oulu.fi
  • Faculty of Information Technology and Electrical Engineering, University of Oulu, Erkki Koiso-Kanttilan katu 5, 90570 Oulu, Finland