access icon free Congestion-aware adaptive decentralised computation offloading and caching for multi-access edge computing networks

Multi-access edge computing (MEC) has attracted much more attention to revolutionising smart communication technologies and Internet of Everything. Nowadays, smart end-user devices are designed to execute sophisticated applications that demand more resources and explosively connected to the global ecosystem. As a result, the backhaul network traffic congestion grows enormously and user quality of experience is compromised as well. To address these challenges, the authors proposed congestion-aware adaptive decentralised computing, caching, and communication framework which can orchestrate the dynamic network environment based on deep reinforcement learning for MEC networks. MEC is a paradigm shift that transforms cloud services and capabilities platform at the edge of ubiquitous radio access networks in close proximity to mobile subscribers. The framework can evolve to perform augmented decision-making capabilities for the upcoming network generation. Hence, the problem is formulated using non-cooperative game theory which is nondeterministic polynomial (NP) hard to solve and the authors show that the game admits a Nash equilibrium. In addition, they have constructed a decentralised adaptive scheduling algorithm to leverage the utility of each smart end-user device. Therefore, their methodical observations using theoretical analysis and simulation results substantiate that the proposed algorithm can achieve ultra-low latency, enhanced storage capability, low energy consumption, and scalable than the baseline scheme.

Inspec keywords: Internet of Things; distributed processing; optimisation; multi-access systems; telecommunication scheduling; adaptive scheduling; computational complexity; radio access networks; game theory; mobile computing; cloud computing; telecommunication traffic; learning (artificial intelligence); quality of experience; decision making

Other keywords: MEC networks; energy consumption; backhaul network traffic congestion; dynamic network environment; NP hard problem; cloud services; global ecosystem; smart communication technologies; multiaccess edge computing networks; congestion-aware adaptive decentralised computation offloading; deep reinforcement learning; ubiquitous radio access networks; quality of experience; communication framework; decentralised adaptive scheduling algorithm; noncooperative game theory; ultra-low latency; augmented decision-making capabilities; Nash equilibrium; network generation; Internet of Everything; smart end-user device; mobile subscribers

Subjects: Optimisation techniques; Radio access systems; Mobile radio systems; Knowledge engineering techniques; Game theory; Computer networks and techniques; Game theory; Computer communications; Optimisation techniques; Mobile, ubiquitous and pervasive computing; Multiple access communication

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