30,275 research outputs found
Spatial networks with wireless applications
Many networks have nodes located in physical space, with links more common
between closely spaced pairs of nodes. For example, the nodes could be wireless
devices and links communication channels in a wireless mesh network. We
describe recent work involving such networks, considering effects due to the
geometry (convex,non-convex, and fractal), node distribution,
distance-dependent link probability, mobility, directivity and interference.Comment: Review article- an amended version with a new title from the origina
Extremal Properties of Three Dimensional Sensor Networks with Applications
In this paper, we analyze various critical transmitting/sensing ranges for
connectivity and coverage in three-dimensional sensor networks. As in other
large-scale complex systems, many global parameters of sensor networks undergo
phase transitions: For a given property of the network, there is a critical
threshold, corresponding to the minimum amount of the communication effort or
power expenditure by individual nodes, above (resp. below) which the property
exists with high (resp. a low) probability. For sensor networks, properties of
interest include simple and multiple degrees of connectivity/coverage. First,
we investigate the network topology according to the region of deployment, the
number of deployed sensors and their transmitting/sensing ranges. More
specifically, we consider the following problems: Assume that nodes, each
capable of sensing events within a radius of , are randomly and uniformly
distributed in a 3-dimensional region of volume , how large
must the sensing range be to ensure a given degree of coverage of the region to
monitor? For a given transmission range, what is the minimum (resp. maximum)
degree of the network? What is then the typical hop-diameter of the underlying
network? Next, we show how these results affect algorithmic aspects of the
network by designing specific distributed protocols for sensor networks
Statistical Inference in a Directed Network Model with Covariates
Networks are often characterized by node heterogeneity for which nodes
exhibit different degrees of interaction and link homophily for which nodes
sharing common features tend to associate with each other. In this paper, we
propose a new directed network model to capture the former via node-specific
parametrization and the latter by incorporating covariates. In particular, this
model quantifies the extent of heterogeneity in terms of outgoingness and
incomingness of each node by different parameters, thus allowing the number of
heterogeneity parameters to be twice the number of nodes. We study the maximum
likelihood estimation of the model and establish the uniform consistency and
asymptotic normality of the resulting estimators. Numerical studies demonstrate
our theoretical findings and a data analysis confirms the usefulness of our
model.Comment: 29 pages. minor revisio
Research on Wireless Multi-hop Networks: Current State and Challenges
Wireless multi-hop networks, in various forms and under various names, are
being increasingly used in military and civilian applications. Studying
connectivity and capacity of these networks is an important problem. The
scaling behavior of connectivity and capacity when the network becomes
sufficiently large is of particular interest. In this position paper, we
briefly overview recent development and discuss research challenges and
opportunities in the area, with a focus on the network connectivity.Comment: invited position paper to International Conference on Computing,
Networking and Communications, Hawaii, USA, 201
Recommender Systems
The ongoing rapid expansion of the Internet greatly increases the necessity
of effective recommender systems for filtering the abundant information.
Extensive research for recommender systems is conducted by a broad range of
communities including social and computer scientists, physicists, and
interdisciplinary researchers. Despite substantial theoretical and practical
achievements, unification and comparison of different approaches are lacking,
which impedes further advances. In this article, we review recent developments
in recommender systems and discuss the major challenges. We compare and
evaluate available algorithms and examine their roles in the future
developments. In addition to algorithms, physical aspects are described to
illustrate macroscopic behavior of recommender systems. Potential impacts and
future directions are discussed. We emphasize that recommendation has a great
scientific depth and combines diverse research fields which makes it of
interests for physicists as well as interdisciplinary researchers.Comment: 97 pages, 20 figures (To appear in Physics Reports
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