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Distinguished Speaker Series: Drone-assisted Mobile Edge Computing
May 8, 2019 @ 6:30 pm - 8:45 pm PDT
FreeDistinguished Speaker Series: Drone-assisted Mobile Edge Computing
Wednesday, May 8th, 2019 at 6:30 PM
TI Auditorium
PROGRAM6:30 – 7:00 PM Networking & Refreshments 7:00 – 8:00 PM Talk by Dr. Nirwan Ansari8:00 – 8:30 PM Panel Session |
REGISTRATIONhttps://www.eventbrite.com/e/distinguished-speaker-series-drone-assisted-mobile-edge-computing-tickets-60709768552 |
IEEE CIS Chapter is co-organizing this free event with IEEE ComSoc chapter.
IEEE Santa Clara Valley Section CIS Chapter
https://ieee-region6.org/scv-cis/
Chair: Dr. Kiran Gunnam
Vice-Chair: Dr. Mehran Nekuii
Treasurer: Ms. Priscilla Chen
Secretary: Mr. Shreyans Mulkutkar
Finance Committee Chair: Ms. Yllka Masada
Note: This event is FREE, open to every one. You don’t need to be an IEEE member to attend!
FREE refreshments & water… donations welcome!
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Please see this for speaker’s bio and abstract:
Speaker: Dr. Nirwan AnsariBio: Nirwan Ansari is Distinguished Professor of Electrical and Computer Engineering at the New Jersey Institute of Technology (NJIT). He has also been a visiting (chair) professor at several universities.
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Title: Drone-assisted Mobile Edge ComputingAbstract: In mobile access networks, different types of Internet of Things (IoT) devices (e.g., sensor nodes and smartphones) will generate vast traffic demands, thus dramatically increasing the traffic loads of their connected access nodes, especially in the 5G era. Mobile edge computing enables data collected by IoT devices to be stored in and processed by local fog nodes as well as allows IoT users to access IoT applications via these nodes at the same time. In this case, the communications latency critically affects the response time of IoT user requests. Owing to the dynamic distribution of IoT users, drone base station (DBS), which can be flexibly deployed over hotspot areas, can potentially improve the wireless latency of IoT users by mitigating the heavy traffic loads of macro BSs. Drone-based communications poses two major challenges: 1) DBS should be deployed in suitable areas with heavy traffic demands to serve more users; 2) traffic loads in the network should be allocated among macro BSs and DBSs to avoid instigating traffic congestions. Therefore, we propose a TrAffic Load baLancing (TALL) scheme in such drone-assisted fog network to minimize the wireless latency of IoT users. In the scheme, we divide the problem into two sub-problems and design two algorithms to optimize the DBS placement and user association, respectively. Extensive simulations have been set up to validate the performance of TALL. |