BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:Australia/Melbourne BEGIN:DAYLIGHT DTSTART:20201004T030000 TZOFFSETFROM:+1000 TZOFFSETTO:+1100 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=10 TZNAME:AEDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20200405T020000 TZOFFSETFROM:+1100 TZOFFSETTO:+1000 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=4 TZNAME:AEST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20200722T102455Z UID:38A2B3FC-50D8-4C3D-8B9C-5454DE087F6A DTSTART;TZID=Australia/Melbourne:20200722T170000 DTEND;TZID=Australia/Melbourne:20200722T183000 DESCRIPTION:In 5G networks\, mobile service providers will support vertical slices of mobile applications to meet diverse service quality requirement s\, such as ultra-low latency\, densely distributed users and high reliabi lity. Meanwhile\, wireless traffic is explosively growing\, driven by wide spread mobile communication devices and increasing popularity of mobile ap plications. The wireless network slicing technique\, which is built on net work function virtualization and software defined network schemes\, will s upport wireless applications on substrate physical facilities with higher flexibility and lower cost.\n\nA scheduling policy for wireless network sl icing should maximize the energy efficiency of the network. (Here\, we def ine 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 applicatio n of conventional optimization techniques. We have developed a policy call ed Most Energy-Efficient Resource First (MEERF)\, which is scalable and pr iority-based. MEERF is asymptotically optimal in a local wireless environm ent with highly dense user population and exponentially distributed servic e times. Our extensive simulations show the robustness of MEERF to differe nt service time distributions. We also show the effectiveness of MEERF com pared to benchmark policies in a more general network with potentially geo graphically distributed users and infrastructures.\n\nOnline\, https://us0 2web.zoom.us/j/86459825706?pwd=UGg1U2ZRQkk5bWxzdmd4K2czTGtMZz09\, Melbourn e\, Victoria\, Australia LOCATION:Online\, https://us02web.zoom.us/j/86459825706?pwd=UGg1U2ZRQkk5bWx zdmd4K2czTGtMZz09\, Melbourne\, Victoria\, Australia ORGANIZER:golnar.khomami@ieee.org SEQUENCE:4 SUMMARY:Energy-Efficient Scheduling for Wireless Network Slicing URL;VALUE=URI:https://events.vtools.ieee.org/m/233891 X-ALT-DESC:Description: <br /><p>In 5G networks\, mobile service providers will support vertical slices of mobile applications to meet diverse servic e quality requirements\, such as ultra-low latency\, densely distributed u sers and high reliability. Meanwhile\, wireless traffic is explosively gro wing\, driven by widespread mobile communication devices and increasing po pularity of mobile applications. The wireless network slicing technique\, which is built on network function virtualization and software defined net work schemes\, will support wireless applications on substrate physical fa cilities with higher flexibility and lower cost.</p>\n<p>A scheduling poli cy for wireless network slicing should maximize the energy efficiency of t he network. (Here\, we define energy efficiency as the ratio of long-run a verage throughput of user requests to the long-run average power consumpti on.) This is a problem of extremely high computational complexity\, which prevents direct application of conventional optimization techniques. We ha ve 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 expone ntially distributed service times. Our extensive simulations show the robu stness of MEERF to different service time distributions. We also show the effectiveness of MEERF compared to benchmark policies in a more general ne twork with potentially geographically distributed users and infrastructure s.</p> END:VEVENT END:VCALENDAR