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07/13/2022
Scheduling Out-of-Coverage Vehicular Communications Using Reinforcement Learning
Performance of vehicle-to-vehicle (V2V) communications depends highly on...
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10/20/2021
Towards Grassroots Peering at the Edge
Fog Computing allows applications to address their latency and privacy r...
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03/16/2021
Generation of Realistic Cloud Access Times for Mobile Application Testing using Transfer Learning
The network Quality of Service (QoS) metrics such as the access time, th...
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02/09/2021
Distributed Learning for Proportional-Fair Resource Allocation in Coexisting WiFi Networks
In this paper, we revisit the widely known performance anomaly that resu...
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03/31/2020
A Fully Distributed, Privacy Respecting Approach for Back-tracking of Potentially Infectious Contacts
In limiting the rapid spread of highly infectious diseases like Covid-19...
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12/09/2019
OfdmFi: Enabling Cross-Technology Communication Between LTE-U/LAA and WiFi
Despite exhibiting very high theoretical data rates, in practice, the pe...
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07/22/2019
VRLS: A Unified Reinforcement Learning Scheduler for Vehicle-to-Vehicle Communications
Vehicle-to-vehicle (V2V) communications have distinct challenges that ne...
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04/29/2019
Reinforcement Learning Scheduler for Vehicle-to-Vehicle Communications Outside Coverage
Radio resources in vehicle-to-vehicle (V2V) communication can be schedul...
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07/13/2018
Greedy Multi-Channel Neighbor Discovery
The accelerating penetration of physical environments by objects with in...
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10/27/2017
Towards efficient coexistence of IEEE 802.15.4e TSCH and IEEE 802.11
A major challenge in wide deployment of smart wireless devices, using di...
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10/22/2017