The usual methods of applying Bayesian networks to the modeling of temporal processes, such as Dean and Kanazawa's dynamic Bayesian networks (DBNs), consist in discretizing t...
Software-defined networks (SDNs) are a new implementation architecture in which a controller machine manages a distributed collection of switches, by instructing them to install ...
Christopher Monsanto, Nate Foster, Rob Harrison, D...
This paper offers a local distributed algorithm for expectation maximization in large peer-to-peer environments. The algorithm can be used for a variety of well-known data mining...
Abstract—Detecting the occurrence and location of performance anomalies (e.g., high jitter or loss events) is critical to ensuring the effective operation of network infrastructu...
Paul Barford, Nick G. Duffield, Amos Ron, Joel Som...
This paper presents the design challenges posed by a new class of ultra-low-power devices referred to as Energy-Harvesting Active Networked Tags (EnHANTs). EnHANTs are small, fle...
Maria Gorlatova, Peter R. Kinget, Ioannis Kymissis...