This paper presents an application of multi-agent system in ubiquitous computing scenarios characteristic of next-generation networks. Next-generation networks will create environments populated with a vast number of consumers, which will possess diverse types of context-aware devices. In such environments the consumer should be able to access all the available services anytime, from any place, and by using any of its communication-enabled devices. Consequently, next-generation networks will require efficient mechanisms which can match consumers’ demands (requested services) to network-operators’ supplies (available services). The authors propose an agent approach for enabling autonomous coordination between all the entities across the telecom value chain, thus enabling automated context-aware service provisioning for the consumers. Furthermore, the authors hope that the proposed service discovery model will not only be interesting from a scientific point of view, but also amenable to real-world applications.
Multi-Agent Deep Reinforcement Learning Based Cooperative Edge Caching for Ultra-Dense Next-Generation Networks
