In this paper, we propose an interference aware throughput maximizing scheduler for cognitive radio networks (CRNs) as part of a MAC layer resource allocation framework. In the con...
Motivated by issues of saving energy in data centers we define a collection of new problems referred to as "machine activation" problems. The central framework we introd...
We present a distributed machine learning framework based on support vector machines that allows classification problems to be solved iteratively through parallel update algorithm...
In this paper we develop a recovery conscious framework for multi-core architectures and a suite of techniques for improving the resiliency and recovery efficiency of highly conc...
Sangeetha Seshadri, Lawrence Chiu, Cornel Constant...
Scheduling data processing workflows (dataflows) on the cloud is a very complex and challenging task. It is essentially an optimization problem, very similar to query optimizati...
Herald Kllapi, Eva Sitaridi, Manolis M. Tsangaris,...