AgPi: Agents on Raspberry Pi
AbstractThe Raspberry Pi and its variants have brought with them an aura of change in the world of embedded systems. With their impressive computation and communication capabilities and low footprint, these devices have thrown open the possibility of realizing a network of things in a very cost-effective manner. While such networks offer good solutions to prominent issues, they are indeed a long way from being smart or intelligent. Most of the currently available implementations of such a network of devices involve a centralized cloud-based server that contributes to making the necessary intelligent decisions, leaving these devices fairly underutilized. Though this paradigm provides for an easy and rapid solution, they have limited scalability, are less robust and at times prove to be expensive. In this paper, we introduce the concept of Agents on Raspberry Pi (AgPi) as a cyber solution to enhance the smartness and flexibility of such embedded networks of physical devices in a decentralized manner. The use of a Multi-Agent System (MAS) running on Raspberry Pis aids agents, both static and mobile, to govern the various activities within the network. Agents can act autonomously or on behalf of a human user and can collaborate, learn, adapt and act, thus contributing to embedded intelligence. This paper describes how Tartarus, a multi-agent platform, embedded on Raspberry Pis that constitute a network, can bring the best out of the system. To reveal the versatility of the concept of AgPi, an application for a Location-Aware and Tracking Service (LATS) is presented. The results obtained from a comparison of data transfer cost between the conventional cloud-based approach with AgPi have also been included. View Full-Text
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Semwal, T.; Nair, S.B. AgPi: Agents on Raspberry Pi. Electronics 2016, 5, 72.
Semwal T, Nair SB. AgPi: Agents on Raspberry Pi. Electronics. 2016; 5(4):72.Chicago/Turabian Style
Semwal, Tushar; Nair, Shivashankar B. 2016. "AgPi: Agents on Raspberry Pi." Electronics 5, no. 4: 72.