AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
TL;DR
Simulation results demonstrate that WCOA outperforms popular techniques like LDROA, OONS, and Greedy strategies by reducing CPU and RAM usage by over 70% and cutting costs by 50% to 70%, making it a scalable and cost-effective solution for future MEC systems.
For time-sensitive Industrial Internet of Things (IIoT) applications demanding ultra-reliable and low-latency communication (URLLC), it is critical to integrate the age of information (AoI) into computation offloading designs. This paper proposes a joint optimization of task offloading and resource allocation in the mo...
With the rapid increase in real-time computational demands from in-vehicle applications, traditional cloud computing is often unable to meet the millisecond-level response requirements of the Internet of Vehicles due to transmission delays. Vehicular fog computing, which integrates edge infrastructures and idle resourc...
A Real-time Integrated Adaptive Stable Offloading (RIASO) algorithm is proposed based on Lyapunov optimization (LO), Multi Output Learning (MOL), and DRL that optimizes network data processing capabilities while maintaining long-term data queue stability and average consumed power constraints that makes it adaptable to...
Edge cloud computing in the Industrial Internet of Things (IIoT) enables latency-sensitive tasks from IIoT terminals to be offloaded to distributed edge data centers (EDCs). This paper proposes an agentic artificial intelligence (AI)-assisted Stackelberg game framework to address the task offloading and resource alloca...
The low-altitude economy is accelerating the deployment of unmanned aerial vehicles (UAVs) as flexible sensing, communication, and edge-computing platforms. In UAV-assisted Internet of Things (IoT) mobile edge computing (MEC), conventional greedy offloading can become unreliable because per-task decisions ignore shared...
A comparative analytical framework called EDGE-LAT is presented for systematically evaluating the existing latency-aware task offloading and resource allocation approaches in IoT–Fog–Cloud environments and shows that the EDGE-LAT analytical framework identifies better latency-aware strategies under the evaluated simula...
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