DEED: Dynamic Energy-Efficient Data offloading for IoT applications under unstable channel conditions

Abstract

With the widespread use of Internet of things (IoT) applications, the fast response and efficient data storage have been the main concerns of the service users and providers. Thus, data offloading has become a hotspot in both industry and academia, especially for real-time applications. To achieve efficient data offloading, a great number of in-depth studies have been conducted. Nevertheless, when addressing the issue of data offloading, few studies have taken into account the unstable channel conditions, which is however more practical and really needs more attention. In this paper, we consider the unstable channel state in the communication model. Based on this, we propose the task reliability model, the energy consumption model, and the device reliability model. From the perspective of optimizing energy consumption, we propose an optimal task scheduling model. Moreover, an innovative Dynamic Energy-Efficient Data offloading scheduling algorithm-DEED is proposed. The purpose of DEED is to as much as possibly reduce the energy consumption while ensuring the task reliability. To verify the effectiveness of the proposed DEED, extensive experiments are conducted to compare it with three comparison algorithms: DRSD, DEPD, and DRPD. The experimental results under different channel conditions demonstrate the superiority of the DEED in terms of the energy saving, reliability, and robustness.