Joint Latency-Energy Minimization for Fog-Assisted Wireless IoT Networks

• Published in: IEEE open journal of the Communications Society Vol. 6; pp. 516 - 530
• Main Authors: Shams, Farshad, Lottici, Vincenzo, Tian, Zhi
• Format: Journal Article
• Language: English
• Published: New York IEEE 2025; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Bi-objective optimization; Computational modeling; Energy consumption; fog-assisted networks; Integrated circuit modeling; Internet of Things; IoT; joint resource allocation; Linear programming; NBS; Network latency; Optimization; Pareto boundary; Power demand; Resource allocation; Resource management; Tchebyshev method; Wireless communication; Wireless networks; Wireless sensor networks
• ISSN: 2644-125X; 2644-125X
• DOI: 10.1109/OJCOMS.2024.3522256

This work aims to present a joint resource allocation method for a fog-assisted network wherein IoT wireless devices simultaneously offload their tasks to a serving fog node. The main contribution is to formulate joint minimization of service latency and energy consumption objectives subject to both radio and computing constraints. Moreover, unlike previous works that set a fixed value to the circuit power dissipated to operate a wireless device, practical models are considered. To derive the Pareto boundary between two conflicting objectives we consider, Tchebyshev theorem is used for each wireless device. The interactions among IoT devices are represented through a cooperative Nash bargaining framework, with the unique Nash equilibrium (NE) being computed via a block coordinate descent method. Numerical results obtained using realistic models are presented to corroborate the effectiveness of the proposed algorithm.