Temporally-asymmetric Hebbian learning is a class of algorithms motivated by data from recent neurophysiology experiments. While traditional Hebbian learning rules use mean firin...
– We examine in this paper the tradeoff between application complexity, network complexity, and network efficiency. We argue that the design of the current Internet reflects a ...
Data ONTAP GX is a clustered Network Attached File server composed of a number of cooperating filers. Each filer manages its own local file system, which consists of a number of d...
Michael Eisler, Peter Corbett, Michael Kazar, Dani...
The growth in complexity of modern systems makes it increasingly difficult to extract high-performance. The software stacks for such systems typically consist of multiple layers a...
Smart dust motes are miniature self-contained systems that may be deployed in very large numbers. In military applications these devices are subject to different threats than conv...