Fog Computing Meets URLLC: Energy Minimization of Task Partial Offloading for URLLC Services

IEEE Access, vol. 12, pp. 100328–100342

Abstract

Ultra-high reliability and ultra-low latency communication (URLLC) are critical challenges for upcoming 6G applications. Cloud computing and mobile edge computing (MEC) offer potential solutions but incur high deployment and maintenance costs due to reliance on central or edge servers. Moreover, the surge in users and data exacerbates latency concerns. Therefore, with more flexible servers deployment, fog computing is more capable of URLLC requirements. In this work, we propose a fog computing model utilizing mobile devices’ computing capabilities to mitigate latency delays. We characterise the problem as an optimisation problem in quadratic variables. And we reduce the problem to a mixed integer convex optimisation problem in two dimensions using decomposition subproblems. Based on this, we introduce a partial offloading algorithm based on the finite blocklength (FBL) mechanism, which improves the energy efficiency. Simulations demonstrate the efficiency of our algorithm in URLLC, with a 49% reduction in energy consumption compared to no retransmission and a 36% reduction in energy consumption compared to infinite blocklength (IBL) coding.

Authors 4

1. Chenhao Shi

   Wuhan University

   Affiliation as printed

   School of Electronic Information, Wuhan University, Wuhan, China

2. Jingrui Wei

   Wuhan University

   Affiliation as printed

   School of Electronic Information, Wuhan University, Wuhan, China

3. Yao Lin Zhu Aachen Chair of Information Theory and Data Analytics

   RWTH Aachen University

   Affiliation as printed

   Chair of Information Theory and Data Analytics, RWTH Aachen University, Aachen, Germany

4. Anke Schmeink Aachen Chair of Information Theory and Data Analytics

   RWTH Aachen University

   Affiliation as printed

   Chair of Information Theory and Data Analytics, RWTH Aachen University, Aachen, Germany