HYDRO: Hybrid Orchestration of In-Network Computations for the Internet of Things

For some of the Internet-of-Things (IoT) applications, there is a need for processing huge amounts of data stemming from the network edge in near real-time manner. To this end several in-network computation frameworks have been developed which deploy functions in the computing infrastructure from the edge to the cloud. Some of these frameworks take a centralized approach to the orchestration problem with a central entity making deployment decisions of the functions. Others decentralize such decisions. In this paper, we present HYdrO, which is a hybrid approach to orchestration of functions, i.e., a centralized instance gathers the state of the network and provides hints to the individual computing nodes for an efficient resolution of computation requests. We show with a concrete example of Named Function Networking (NFN), a computing framework based on Information Centric Networking, that HYdrO can improve completion times of requests and distribute the load of the infrastructure.