Towards Edge-assisted Internet of Things: From Security and Efficiency Perspectives

TL;DR

This paper explores how mobile edge computing can enhance data analysis, security, and efficiency in IoT applications by addressing key challenges and proposing potential solutions for secure data processing and computational offloading.

Contribution

It provides a comprehensive analysis of mobile edge computing architecture and discusses novel methods to improve data security and computational efficiency in IoT.

Findings

Identifies security and efficiency challenges in mobile edge IoT data processing.

Proposes secure data aggregation, deduplication, and offloading techniques.

Outlines future research directions for edge-empowered data analysis.

Abstract

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.