An adaptive data coding scheme for energy consumption reduction in SDN-based Internet of Things

Abstract

In recent decades, most internet-connected devices were personal computers. However, everything is connecting to the Internet over time. Today, the Internet of Things (IoT) is expanding rapidly, including everything from clothing to agricultural equipment. The Internet of Everything (IoE) is very complex and heterogeneous due to the independent development of its various sections. Hence, the coordination and management of its different equipment are challenging, and the energy consumption efficiency is very low, which is the bottleneck of battery-operated IoT equipment. So far, various methods have been proposed to reduce energy consumption in IoT devices. However, these methods are used independently and individually on a single IoT node, and none of them consider all objects in the IoT hierarchy together. Whereas the IoT network arises when various objects interact with each other. Therefore, focusing on energy consumption in a single node should be transformed into energy management at the whole network administrative level. In this paper, considering the IoT network features and the data exchange all over the network, a data manipulation method is proposed to reduce energy consumption and network traffic by decreasing the amount of data exchanged. Furthermore, we take advantage of Software-Defined Networking (SDN) to enhance the efficiency of this method by adapting our energy management decisions to the environmental conditions’ dynamicity. Simulation results using real data workloads demonstrate that the proposed method decreases energy consumption by up to 38.1% without an SDN. This reduction is significantly improved by up to 80.0% when utilizing SDN. We also experimentally evaluate the proposed method by its hardware implementation in the real environment and illustrate that a maximum of only 1.3% difference is observed between the simulation results and the experiments, which indicates the consistency of the results.