A large-scale study of the impact of node behavior on loosely coupled data dissemination: The case of the distributed Arctic observatory

A Cyber-Physical System (CPS) deployed in remote and resource-constrained environments faces multiple challenges. It has, no or limited: network coverage, possibility of energy replenishment, physical access by humans. Cyber-physical nodes deployed to observe and interact with the Arctic tundra face these challenges. They are subject to environmental factors such as avalanches, low temperatures, snow, ice, water and wild animals. Without energy supply infrastructures and humans available, nodes must achieve long operational lifetime from a single battery charge. They must be extremely energy-efficient. To reduce energy costs and increase their energy efficiency, cyber-physical nodes sleep most of the time, and avoid to communicate when they are unreachable. But, a CPS needs to disseminate data between the nodes for multiple purposes including data reporting to a back-end service, resilient operations, safe-keeping of observational data, and propagating nodes updates. Loosely-coupled data dissemination policies offer this possibility [1] . Although, investigations should be made on their applicability to large-scale CPS. In this paper, we evaluate and discuss the efficiency in energy, time and number of successful delivery of four data dissemination policies proposed in [1] . This evaluation is based on flow-level simulations. We study small and large-scale CPS, and evaluate the effects of the number of nodes and the size of the disseminated data on the nodes energy consumption and the dissemination's delivery success. To mitigate negative effects raised on large-scale CPS and large disseminated data sizes, different strategies are proposed and evaluated. We show that energy saving strategies do not always imply energy efficiency, and better data dissemination often comes at a cost. This last result highlights the importance of simulation prior to real CPS deployments in constrained environments. • CPS deployed in remote and resource-constrained environments faces challenges. • Energy efficient and scalable approaches for data dissemination in CPS are needed. • Simulation of CPS provides trade-offs in energy and data dissemination performance.