In recent years, there have been intensive theoretical research works on modeling/analysis of oscillatory phenomena. In this paper, we derive a sufficient condition under which (a...
Reinforcement learning algorithms that employ neural networks as function approximators have proven to be powerful tools for solving optimal control problems. However, their traini...
This work presents a cross-layer modification to the DSR protocol which discovers high throughput paths on multi-hop wireless mesh networks. The modified DSR incorporates a metric...
In geographic (or geometric) routing, messages are expected to route in a greedy manner: the current node always forwards a message to its neighbor node that is closest to the des...
We investigate the performance of longest-queue-first (LQF) scheduling (i.e., greedy maximal scheduling) for wireless networks under the SINR interference model. This interference...
Long Bao Le, Eytan Modiano, Changhee Joo, Ness B. ...