Cloud live streaming System based on Auto-adaptive Overlay for Cyber Physical Infrastructure

According to Mark Zuckerberg's speech, at the Samsung S7 launch in February 2016, the age of massive data streaming, especially massive video streaming, is here. At the beginning of the year 2000, most people used to share and search almost only text. Then, they started to be interested in sharing and searching images and, in the latter years, videos with different formats and resolutions. One of the emerging technologies of this decade is Virtual Reality (VR) through which people can share resources in a more exciting and enjoyable manner. If a decade ago people used to only read about how to do things, now they see it being done in videos. Expectations are that, in the not so distant future, they will be able to visualize and experience it through the power of VR. But, new technologies come with new challenges. Video streaming, especially for VR, generates a great amount of data. Techniques used until now need to evolve or lead the way for better ones. Centralized approaches for big data live streaming are no longer appropriate. Peer-to-Peer networks are more suitable due to their decentralized nature and auto-adaptive property. The aim of this paper is to analyze and evaluate the performances of the SPIDER Peer-to-Peer Overlay in the context of live video streaming for two Cloud use cases. The first scenario entitled CyberWater aims to create an e-platform for sustainable water resources with a high focus on pollution phenomena. The second scenario, called ClueFarm, is a Cloud service-based system for quality business development in the farming sector. The experimental results presented in this paper focus on the amount of bandwidth needed in booth test scenarios and emphasize the advantages of the SPIDER Peer-to-Peer Overlay.