8 citations · 10 across the 5 of their papers we have counts for
7 papers
State Action Separable Reinforcement Learning
Ziyao Zhang, Liang Ma, Kin K. Leung +2
Reinforcement Learning (RL) based methods have seen their paramount successes in solving serial decision-making and control problems in recent years. For conventional RL formulatio…
MACS: Deep Reinforcement Learning based SDN Controller Synchronization Policy Design
Ziyao Zhang, Liang Ma, Konstantinos Poularakis +3
In distributed software-defined networks (SDN), multiple physical SDN controllers, each managing a network domain, are implemented to balance centralised control, scalability, and…
Joint Service Placement and Request Routing in Multi-cell Mobile Edge Computing Networks
Konstantinos Poularakis, Jaime Llorca, Antonia M. Tulino +2
The proliferation of innovative mobile services such as augmented reality, networked gaming, and autonomous driving has spurred a growing need for low-latency access to computing r…
Learning the Optimal Synchronization Rates in Distributed SDN Control Architectures
Konstantinos Poularakis, Qiaofeng Qin, Liang Ma +3
Since the early development of Software-Defined Network (SDN) technology, researchers have been concerned with the idea of physical distribution of the control plane to address sca…
DQ Scheduler: Deep Reinforcement Learning Based Controller Synchronization in Distributed SDN
Ziyao Zhang, Liang Ma, Konstantinos Poularakis +2
In distributed software-defined networks (SDN), multiple physical SDN controllers, each managing a network domain, are implemented to balance centralized control, scalability and r…
SDN-enabled Tactical Ad Hoc Networks: Extending Programmable Control to the Edge
Konstantinos Poularakis, George Iosifidis, Leandros Tassiulas
Modern tactical operations have complex communication and computing requirements, often involving different coalition teams, that cannot be supported by today's mobile ad hoc netwo…