Cognitive radio (CR) is the enabling technology for supporting dynamic spectrum access:
the policy that addresses the spectrum scarcity problem that is encountered in many …

When network is undergoing problems such as congestion, scan attack, DDoS attack, etc.,
measurements are much more important than usual. In this case, traffic characteristics …

Time series prediction problems are becoming increasingly high-dimensional in modern
applications, such as climatology and demand forecasting. For example, in the latter …

In this paper, we propose to leverage the emerging deep learning techniques for
spatiotemporal modeling and prediction in cellular networks, based on big system data …

Different from traditional IP networks, named data networking (NDN) based on the named
content can realize fast content retrieval and delivery. As one of the most important …

Network measurement remains a missing piece in today's software packet processing
platforms. Sketches provide a promising building block for filling this void by monitoring …

Compressive sensing (CS) is a novel sampling paradigm that samples signals in a much
more efficient way than the established Nyquist sampling theorem. CS has recently gained a …

Estimation of end-to-end network traffic plays an important role in traffic engineering and
network planning. The direct measurement of a network's traffic matrix consumes large …

Network measurement is challenged to fulfill stringent resource requirements in the face of
massive network traffic. While approximate measurement can trade accuracy for resource …

The problem of incomplete data–ie, data with missing or unknown values–in multi-way
arrays is ubiquitous in biomedical signal processing, network traffic analysis, bibliometrics …