From Cloud-Edge to Edge-Edge Continuum: the Swarm-Based Edge Computing Systems

Modern cloud-edge-device computational platforms does not match the needs of artificial intelligence at the edge of the network. Indeed, the lack of computing power allows that only some AI processes can be performed on edge devices, having also to consider their constrained energy capacity. Moreover, the lack of computing continuum between nodes of the same layer, i.e., edge-to-edge, allows to only operate independently within the layer by sensing the environment where nodes stay. In this paper, we propose a lightweight framework for collaborative nodes with decentralized edge intelligence. Organized like a swarm, the groups of nodes emphasize the edge-to-edge continuum of the device-edge-cloud paradigm. This supports a paradigm shift from programming environments for individual devices to dynamic and cooperating groups of nodes. The nodes' coordination relays on green overlay and offloading mechanisms. Innovative mesh architectures with mixed topologies allow building overlays for having swarm coordination. Tasks offloading exploits the overlays to balance the swarm in near-real-time, according to forecasted energy consumption. Stemming from the proposed reference architecture, we also discuss a series of open challenges, which we believe represent relevant research directions in the nearest future.