Scalable Adaptive Group Communication for Collaboration Framework of Cloud-enabled Robots.

Abstract Recently, researchers have been exploring the idea of robots that rely on cloud-computing infrastructure to take advantage of processing power and access vast amounts of data. This approach allows a robot to delegate compute-intensive tasks like image recognition, graphical mapping systems and etc. However, the efficient information sharing of cloud-enabled robots is not addressed which is necessary in disseminating real time information. In this paper, a collaboration framework is presented which is designed for information sharing of cloud-enabled robots. Based on attributes, cloud-enabled robots form logical groups to perform information sharing through the Internet. To provide a faster way of disseminating messages, a scalable adaptive group communication (SAGC) is proposed. The logical groups are processed using fuzzy system to employ scalable grouping, and then, the logical links are adjusted by a node link weight function based on Brownian agent to direct the queries to robots with relevant information. The performance evaluation showed that the SAGC had the fastest response to queries compared to other group communication methods.