Towards Edge-assisted Internet of Things: From Security and Efficiency Perspectives
This work addresses security and efficiency issues for IoT systems leveraging mobile edge computing, but it is incremental as it reviews existing challenges and opportunities without introducing new methods.
The paper tackles the problem of security and efficiency in data usage for mobile edge computing in IoT applications, exploring how edge computing can enhance data analysis while addressing these challenges, but does not report concrete numerical results.
As we are moving towards the Internet of Things (IoT) era, the number of connected physical devices is increasing at a rapid pace. Mobile edge computing is emerging to handle the sheer volume of produced data and reach the latency demand of computation-intensive IoT applications. Although the advance of mobile edge computing on service latency is studied solidly, security and efficiency on data usage in mobile edge computing have not been clearly identified. In this article, we examine the architecture of mobile edge computing and explore the potentials of utilizing mobile edge computing to enhance data analysis for IoT applications, while achieving data security and computational efficiency. Specifically, we first introduce the overall architecture and several promising edge-assisted IoT applications. We then study the security, privacy and efficiency challenges in data processing for mobile edge computing, and discuss the opportunities to enhance data security and improve computational efficiency with the assistance of edge computing, including secure data aggregation, secure data deduplication and secure computational offloading. Finally, several interesting directions on edge-empowered data analysis are presented for future research.