activity
20152021
most citedOptimized Age of Information Tail for Ultra-Reliable Low-Latency Communications in Vehicular Networks

144 citations · 544 across the 13 of their papers we have counts for

collaborators
Showing 2020Show all

11 papers · 1 filter

cs.NI2020

Predictive Ultra-Reliable Communication: A Survival Analysis Perspective

Sumudu Samarakoon, Mehdi Bennis, Walid Saad +1

Ultra-reliable communication (URC) is a key enabler for supporting immersive and mission-critical 5G applications. Meeting the strict reliability requirements of these applications…

cs.NI2020

Age-Optimal Power Allocation in Industrial IoT: A Risk-Sensitive Federated Learning Approach

Yung-Lin Hsu, Chen-Feng Liu, Sumudu Samarakoon +2

This work studies a real-time environment monitoring scenario in the industrial Internet of things, where wireless sensors proactively collect environmental data and transmit it to…

cs.LG2020

BayGo: Joint Bayesian Learning and Information-Aware Graph Optimization

Tamara Alshammari, Sumudu Samarakoon, Anis Elgabli +1

This article deals with the problem of distributed machine learning, in which agents update their models based on their local datasets, and aggregate the updated models collaborati…

cs.IT2020

Phase Configuration Learning in Wireless Networks with Multiple Reconfigurable Intelligent Surfaces

George C. Alexandropoulos, Sumudu Samarakoon, Mehdi Bennis +1

Reconfigurable Intelligent Surfaces (RISs) are recently gaining remarkable attention as a low-cost, hardware-efficient, and highly scalable technology capable of offering dynamic c…

cs.LG2020

Communication-Efficient and Distributed Learning Over Wireless Networks: Principles and Applications

Jihong Park, Sumudu Samarakoon, Anis Elgabli +4

Machine learning (ML) is a promising enabler for the fifth generation (5G) communication systems and beyond. By imbuing intelligence into the network edge, edge nodes can proactive…

cs.DC2020126 cited

6G White Paper on Edge Intelligence

Ella Peltonen, Mehdi Bennis, Michele Capobianco +16

In this white paper we provide a vision for 6G Edge Intelligence. Moving towards 5G and beyond the future 6G networks, intelligent solutions utilizing data-driven machine learning…