We present Group Round-Robin (GRR) scheduling, a hybrid fair packet scheduling framework based on a grouping strategy that narrows down the traditional trade-off between fairness ...
We use techniques from sample-complexity in machine learning to reduce problems of incentive-compatible mechanism design to standard algorithmic questions, for a broad class of re...
Maria-Florina Balcan, Avrim Blum, Jason D. Hartlin...
This paper deals with specific issues related to the design of distributed embedded systems implemented with mixed, eventtriggered and time-triggered task sets, which communicate ...
In this paper, we deal with the large-scale divisible load problem studied in [12]. We show how to reduce this problem to a classical preemptive scheduling problem on a single mac...
Anne Benoit, Loris Marchal, Jean-Francois Pineau, ...
Evolutionary Algorithms’ (EAs’) application to real world optimization problems often involves expensive fitness function evaluation. Naturally this has a crippling effect on ...