Entropy-based Reinforcement Learning for computation offloading service in software-defined multi-access edge computing

نویسندگان

چکیده

The rapid growth of Internet Things (IoT) devices and the emergence multiple edge applications have resulted in an explosive data traffic at networks. Computation offloading services Multi-access computing (MEC) enabled networks to offer potentials a better Quality Service (QoS) than traditional They are expected reduce propagation delay enhance computational capability for delay-sensitive tasks especially. Nevertheless, distributed resources urgently need reasonable resource controllers ensure such be effectively scheduled. benefits Software-Defined Networking (SDN) may explored demonstrate their full potential through MEC response time programs. In this paper, new SDN-based computation service architecture is proposed increase coordination capabilities control plane. Besides, deal with dynamic network changes exploration degree, we propose novel Entropy-based Reinforcement Learning algorithm Finally, evaluation findings indicate that our model has improve allocation balanced performance significantly.

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ژورنال

عنوان ژورنال: Future Generation Computer Systems

سال: 2022

ISSN: ['0167-739X', '1872-7115']

DOI: https://doi.org/10.1016/j.future.2022.06.002