Task Offloading Using Multi-Armed Bandit Optimization in Autonomous Mobile Robots
IEEE INFOCOM 2023 - Conference on Computer Communications Workshops, INFOCOM WKSHPS 2023
Evolution in ubiquitous and wireless services has enabled the massive adoption of autonomous cyber-physical systems for improving the workflows in dynamic environments. Among other applications, it has been witnessed that these modern technologies with the help of machine learning and high-speed communications can enable optimum and safe utilization of resources to complete various repetitive yet hazardous tasks. The industry 5.0 vision requires a multitude of devices to work with such orchestration that compute-intensive tasks may be offloaded to nearby nodes to enable collaboration for such time-critical yet compute-intensive tasks. In this work, we present a multi-armed bandit-based approach for task offloading in unmanned autonomous robots. Through experimental validation, a proof of concept is given. It has been demonstrated that using the proposed technique we have achieved a higher task delivery rate with reduced average delay.
industrial internet of things, multi-arm bandit, Safety, task offloading
A. Ur Rahman, A. W. Malik, H. A. Khattak and M. Aloqaily, "Task Offloading Using Multi-Armed Bandit Optimization in Autonomous Mobile Robots," IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), Hoboken, NJ, USA, 2023, pp. 1-7, doi: 10.1109/INFOCOMWKSHPS57453.2023.10226072.