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Optica Publishing Group
  • Journal of Lightwave Technology
  • Vol. 39,
  • Issue 10,
  • pp. 3004-3010
  • (2021)

Experimental Assessment of Automatic Optical Metro Edge Computing Network for Beyond 5G Applications and Network Service Composition

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Abstract

The upcoming 5G and beyond 5G heterogeneous applications with different quality of service (QoS) will impose strict latency, bandwidth, and flexibility requirements on optical metro access networks. Conventional cloud computing is gradually unable to fulfill the application requirements, especially on latency due to the distance causing propagation and networking delay. Therefore, the edge computing that distributed in metro access networks is promising to serve the applications with the requirements of ultra-low latency. As the resources of edge computing nodes are restricted and light compared with cloud data centers (DC), it is significant to manage across multiple edge computing nodes to enable joint allocation of the distributed resources. To address this issue, the optical metro network infrastructure should be flexible on the data plane and able to interact with the control and orchestration plane to automatically adapt to the communication requirements of multiple edge computing nodes. Related works have been focused on the simulation and numerical study. In this paper, an experimental testbed of a flexible optical metro access network including hardware and software components is built, and the performance is validated with real server traffic. The presented network system is based on the field-programmable gate array (FPGA), and hardware adapted open source network management and telemetry tools. Different from the commercial electrical switches, FPGA is fully programmable making it able to flexibly forward and monitor the traffic, in the meantime, to dynamically control the optical devices according to the feedback from the control plane. By exploiting dynamic software defined networking (SDN) control and network service orchestration, the proposed network is able to establish capacity adapted network slices for edge computing connections. Successful telemetry-assisted dynamic network service chain (NSC) generation, automatic bandwidth resources assignment, and QoS protection are demonstrated.

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