Research Area:  Fog Computing

Abstract:

The tremendous growth of interconnected things/devices in the whole world advances to the new paradigm, i.e., Internet of Things (IoT). The IoT use sensor-based embedded systems to interact with others, providing a wide range of applications and services to upper-level users. Undoubtedly, the data collected by the underlying IoTs are the basis of the upper-layer decision and the foundation for all the applications, which requires efficient energy protocols. Moreover, if the collected data are erroneous and untrustworthy, the data protection and application becomes an unrealistic goal, which further leads to unnecessary energy cost. However, the traditional methods cannot solve this problem efficiently and trustworthily. To achieve this goal, in this paper we design a novel energy-efficient and trustworthy protocol based on mobile fog computing. By establishing a trust model on fog elements to evaluate the sensor nodes, the mobile data collection path with the largest utility value is generated, which can avoid visiting unnecessary sensors and collecting untrustworthy data. Theoretical analysis and experimental results validate that our proposed architecture and method outperform traditional data collection methods in both energy and delay.

Keywords:  

Author(s) Name:  Tian Wang; Lei Qiu; Arun Kumar Sangaiah; Guangquan Xu; Anfeng Liu

Publisher name:  IEEE

DOI:  10.1109/TII.2019.2920277

Volume Information:  ( Volume: 16, Issue: 5, May 2020) Page(s): 3531 - 3539

Paper Link:   https://ieeexplore.ieee.org/abstract/document/8727478