Monthly meeting of the IEEE Baltimore Section's executive committee. The meeting is open to all Section members. This meeting will be by videoconference only. Virtual: https://events.vtools.ieee.org/m/456281

Meetings of the Administrative Committee are held virtually. Members are welcome to attend. Reserve your place by registering online or calling the office by the Monday before. Agenda: AdCom Meeting: 7:00 P.M. - 9:00 P.M Virtual: https://events.vtools.ieee.org/m/452200

Dr Rui Li of will take a deep dive into the Multimodal Interaction and Affective Computing Lab (MIAC Lab) at Montclair State with a focus on Multimodal Human-Machine Interaction. This exciting work involves multimodal information processing, immersive interaction, intelligent systems for vehicles and robots. Her passion is for the interdisciplinary study of human emotion, behavior, and cognition to bring about excellent human-machine interaction and intelligent machines. Speaker(s): Dr. Rui Li PhD Virtual: https://events.vtools.ieee.org/m/456316

A presentation on the engineering of and demonstration of the receivers, antennas and software required for radio astronomy. Demonstration of a small scale radio telescope will be available for students. Co-sponsored by: Stark College Astronomy Club/Stark College IEEE Chapter Room: E204, Bldg: Main Campus Building, Stark College, 6200 Frank Ave. NW, North Canton, Ohio, United States, 44720

Abstract: Almost all traffic on the Internet today is sent by Congestion Control Algorithms, which aim to maximize utilization of available bandwidth on an Internet link while simultaneously sharing this bandwidth equally with competing traffic. With the rise of heterogeneous congestion control algorithms and increasingly complex application control loops (e.g. adaptive bitrate algorithms found in video streaming), the Internet community has expressed growing concern that network bandwidth allocations are unfairly skewed, and that some Internet services are ‘winners’ at the expense of ‘losing’ services when competing over shared bottleneck links. In this paper, we provide the first study of fairness between live, end-to-end services with distinct workloads. Put simply, if you and your roommate are watching Netflix and YouTube on a bandwidth-constrained Internet link, would you end up streaming your video at the lowest resolution while your roommate enjoys a high quality 4K stream, or would the outcome be fairer? Among our findings, we observe that services typically achieve less-than-fair outcomes: on average, the ‘losing’ service achieves only 72% of its max-min fair share of link bandwidth. We also find that some services are significantly more contentious than others: for example, one popular file distribution service causes competing applications to obtain as low as 16% of their max-min fair share of bandwidth when competing in a moderately-constrained setting. Speaker(s): , Adithya Room: Room 316, Bldg: 3rd floor theater space , 135 N. Bellefield, Pittsburgh, Pennsylvania, United States