Internet of Things (IoT) networks are mostly comprised of power-constrained devices, therefore the most important consideration in designing IoT applications, based on sensor networks is energy efficiency. Minor improvement in energy conservation methods can lead to a significant increase in the lifetime of IoT devices and overall network. To achieve efficient utilisation of energy, different solutions are proposed such as duty cycling optimization, design changes at the MAC layer, etc. In this paper, we propose a new approach to overcome this challenge in cloud-based IoT sensing applications, based on integration of an abstraction layer with constrained application mechanism. To achieve energy conservation and efficient data management in IoT sensing applications, we incorporate modules of efficient web framework with cloud services, in order to minimize the number of round trips for data delivery and graph-based data representation. Our study is the first attempt in the literature, to the best of our knowledge, which introduces the potential of this integration for achieving the aforementioned objectives in the target applications. We implemented the proposed interfacing of abstraction layer in constrained applications, to develop a testbed using Z1 IoT motes, Contiki OS and GraphQL web framework with Google cloud services. Experimental comparisons against baseline REST architecture approach show that our proposed approach achieved significant reductions in data delivery delay and energy consumption (minimum 51.53% and 52.88%, respectively) in IoT applications involving sensor network.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.