Abstract. Clustering is a widely used unsupervised data analysis technique in machine learning. However, a common requirement amongst many existing clustering methods is that all p...
In this paper we present a model for dynamically scheduling HTTP requests across clusters of servers, optimizing the use of client resources as well as the scattered server nodes....
In this paper, we have proposed a framework of systems-on-chips clustering in application to complicated sensor networks. The framework can be applied to address the communication ...
One way to exploit Thread Level Parallelism (TLP) is to use architectures that implement novel multithreaded execution models, like Scheduled DataFlow (SDF). This latter model pro...
We describe some extensions to the grid smoothing scheme described in [1, 2] that deal with the following issues: 1) the clustering effect of changing valence in an unstructured ...