This paper discusses the future direction of optical access networks and proposes a new optical access architecture that will support the evolution of optical access systems from a fiber-to-the-home infrastructure to a common optical access platform that connects various devices and systems to anywhere they want to reach. We describe two technologies for its implementation. One is “modularization,” which is expected to be realized before 2030, and the other is “full softwarization,” which is the longer-term goal of drastically increasing network flexibility. For each technology, we summarize related technical trends and discuss a reasonable system configuration focusing on the access nodes.
This paper reviews access system standardization activities and related technologies from the viewpoints of optical-based PON access, mobile access systems including LPWAN, and access network virtualization. Future study issues for the next access systems are also presented.
Edge computing is more useful for real-time remote motion control of Internet of Things devices than cloud computing because of its superior low latency performance. The access system is attracting attention as a place to perform edge computing. By using the network devices of the access system as an edge computing resource, it becomes possible to realize more precise control. This paper is the first, to our knowledge, to demonstrate real-time motion control by implementing edge computing on a 10-gigabit Ethernet passive optical network based on software-defined network enabled broadband access (SEBA), which is a virtualization platform for access systems. The proposed method analyzes the effectiveness of motion control and sets the optimal network settings automatically by using SEBA to take full advantage of edge computing benefits. The proposed method can provide an optimal network for motion control without making the user aware of the network settings. We construct a general motor-based experimental system and verify the effectiveness of the proposed system. The experiment shows that it properly reflects the optimum network settings to SEBA. Also, we verify that the proposed method changed the network settings to satisfy the reference settling time of 3 s. The optimal dynamic bandwidth allocation (DBA) cycle for motion control is determined after five trials, and the settling time was reduced by 53% compared with the case where the DBA cycle was set to 20 ms and no optimization was performed.
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