Aug 2026· Journal of Supercomputing· Vol 82· 0 citations· 42 references
TL;DR
A Mixed Integer Nonlinear Programming (MINLP) model with the objective of a weighted sum of long-term average task completion rate, total latency and energy consumption is established, which improves the task completion rate by 4% in high load scenarios and achieves a better balance between latency and energy consumption.
A task scheduling method using the Deep Q-Network to determine the computation node for the computation task and a dynamic congestion-aware mechanism to determine a low-cost routing path is proposed, which gradually obtains an effective task scheduling scheme through multiple rounds of alternating iterations.
Mobile edge computing (MEC) has accelerated the development of artificial intelligence and Internet of Things technologies, leading to the explosive growth of intelligent applications characterized by resource intensity and latency sensitivity, such as image processing and smart home. In practice, an application typica...
Zhixiu Yao, Yun Li, Qilie Liu et al.· IEEE Transactions on Service...· 0 citations
Dynamic edge networks suffer from fluctuating bandwidth, latency, and edge-node load, which weaken conventional task offloading strategies under deadline and energy constraints. This study proposes an adaptive task offloading strategy based on dynamic network states. An online broad learning system predicts short-term...
Jie Yang, Peng Li, Guangfu Ge et al.· 2026 5th International Confe...· 0 citations
A task-driven offloading algorithm based on Balanced Multi-Agent Deep Deterministic Policy Gradient (BMADDPG) that reduces average task processing latency by approximately 22.67% and decreases total system cost by at least 18.32% under high-load scenarios.
This paper addresses the joint task offloading and resource allocation problem in multi-user MEC systems and proposes a decentralized control framework based on Multi-Agent Reinforcement Learning (MARL), which achieves lower total system cost and faster convergence than the full-local, full-offload, and heuristic basel...
Youssef Oukissou, Mohamed Amine Meddaoui, Ayoub Belaidi et al.· International journal of Com...· 0 citations
A new paradigm for satisfying the ever-growing demands of real-time Sixth Generation (6G) applications is Mobile Edge Computing (MEC). Additionally, base stations and Internet of Things devices that incorporate renewable energy harvesting capabilities have the potential to lower grid energy use. To maximize system pote...
Mamoon M. Saeed, Rashid A. Saeed, M. A. Ahmed et al.· 2026 6th International Confe...· 0 citations
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