Open AccessGraphene based Web Framework for Energy Efficient IoT Applications
Author(s) -
Joy Iong Zong Chen,
Lu-Tsou Yeh
Publication year - 2021
Publication title -
journal of information technology and digital world
Language(s) - English
Resource type - Journals
ISSN - 2582-418X
DOI - 10.36548/jitdw.2021.1.003
Subject(s) - computer science , cloud computing , testbed , efficient energy use , distributed computing , interfacing , wireless sensor network , application layer , energy consumption , computer network , engineering , operating system , software deployment , computer hardware , electrical engineering
Energy efficiency is a crucial factor to be considered while designing sensor network based Internet of Things (IoT) applications due to the compromise in terms of power constraint in these devices. The overall network and IoT device lifetime may be increased significantly by enhancing the energy conservation schemes. Design changes, duty cycle optimization at the MAC layer and various other solutions are proposed to achieve efficiency in energy utilization. In IoT sensing applications based on cloud computing, these challenges are overcome by means of integrating the constrained application mechanism with abstraction layer as proposed in this paper. The round trips for graph-based data representation and data delivery are reduced by incorporating the cloud services with an efficient web framework in order to achieve efficient data management and energy conservation in the IoT sensing applications. In specific applications, the aforementioned objectives may be achieved by the integration of potential technologies. Google cloud services along with Graphene web framework, RIOT OS and Z1 IoT motes are used for developing a testbed in the constrained applications at the abstraction layer for interfacing the proposed implementation. The sensor networks in IoT applications have achieved significant reduction in energy consumption and delay of data delivery using the proposed method when compared to the existing baseline approaches.