Energy-Efficient Scheduling for Wireless Network Slicing


In 5G networks, mobile service providers will support vertical slices of mobile applications to meet diverse service quality requirements, such as ultra-low latency, densely distributed users and high reliability. Meanwhile, wireless traffic is explosively growing, driven by widespread mobile communication devices and increasing popularity of mobile applications. The wireless network slicing technique, which is built on network function virtualization and software defined network schemes, will support wireless applications on substrate physical facilities with higher flexibility and lower cost.

A scheduling policy for wireless network slicing should maximize the energy efficiency of the network. (Here, we define energy efficiency as the ratio of long-run average throughput of user requests to the long-run average power consumption.) This is a problem of extremely high computational complexity, which prevents direct application of conventional optimization techniques. We have developed a policy called Most Energy-Efficient Resource First (MEERF), which is scalable and priority-based. MEERF is asymptotically optimal in a local wireless environment with highly dense user population and exponentially distributed service times. Our extensive simulations show the robustness of MEERF to different service time distributions. We also show the effectiveness of MEERF compared to benchmark policies in a more general network with potentially geographically distributed users and infrastructures.

  Date and Time




  • Date: 22 Jul 2020
  • Time: 05:00 PM to 06:30 PM
  • All times are (UTC+10:00) Canberra
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  • Melbourne, Victoria
  • Australia

  • Starts 24 June 2020 03:03 PM
  • Ends 22 July 2020 12:00 PM
  • All times are (UTC+10:00) Canberra
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