66,307 research outputs found
Convergence Speed of the Consensus Algorithm with Interference and Sparse Long-Range Connectivity
We analyze the effect of interference on the convergence rate of average
consensus algorithms, which iteratively compute the measurement average by
message passing among nodes. It is usually assumed that these algorithms
converge faster with a greater exchange of information (i.e., by increased
network connectivity) in every iteration. However, when interference is taken
into account, it is no longer clear if the rate of convergence increases with
network connectivity. We study this problem for randomly-placed
consensus-seeking nodes connected through an interference-limited network. We
investigate the following questions: (a) How does the rate of convergence vary
with increasing communication range of each node? and (b) How does this result
change when each node is allowed to communicate with a few selected far-off
nodes? When nodes schedule their transmissions to avoid interference, we show
that the convergence speed scales with , where is the
communication range and is the number of dimensions. This scaling is the
result of two competing effects when increasing : Increased schedule length
for interference-free transmission vs. the speed gain due to improved
connectivity. Hence, although one-dimensional networks can converge faster from
a greater communication range despite increased interference, the two effects
exactly offset one another in two-dimensions. In higher dimensions, increasing
the communication range can actually degrade the rate of convergence. Our
results thus underline the importance of factoring in the effect of
interference in the design of distributed estimation algorithms.Comment: 27 pages, 4 figure
Leveraging Physical Layer Capabilites: Distributed Scheduling in Interference Networks with Local Views
In most wireless networks, nodes have only limited local information about
the state of the network, which includes connectivity and channel state
information. With limited local information about the network, each node's
knowledge is mismatched; therefore, they must make distributed decisions. In
this paper, we pose the following question - if every node has network state
information only about a small neighborhood, how and when should nodes choose
to transmit? While link scheduling answers the above question for
point-to-point physical layers which are designed for an interference-avoidance
paradigm, we look for answers in cases when interference can be embraced by
advanced PHY layer design, as suggested by results in network information
theory.
To make progress on this challenging problem, we propose a constructive
distributed algorithm that achieves rates higher than link scheduling based on
interference avoidance, especially if each node knows more than one hop of
network state information. We compare our new aggressive algorithm to a
conservative algorithm we have presented in [1]. Both algorithms schedule
sub-networks such that each sub-network can employ advanced
interference-embracing coding schemes to achieve higher rates. Our innovation
is in the identification, selection and scheduling of sub-networks, especially
when sub-networks are larger than a single link.Comment: 14 pages, Submitted to IEEE/ACM Transactions on Networking, October
201
Applications of Geometric Algorithms to Reduce Interference in Wireless Mesh Network
In wireless mesh networks such as WLAN (IEEE 802.11s) or WMAN (IEEE 802.11),
each node should help to relay packets of neighboring nodes toward gateway
using multi-hop routing mechanisms. Wireless mesh networks usually intensively
deploy mesh nodes to deal with the problem of dead spot communication. However,
the higher density of nodes deployed, the higher radio interference occurred.
This causes significant degradation of system performance. In this paper, we
first convert network problems into geometry problems in graph theory, and then
solve the interference problem by geometric algorithms. We first define line
intersection in a graph to reflect radio interference problem in a wireless
mesh network. We then use plan sweep algorithm to find intersection lines, if
any; employ Voronoi diagram algorithm to delimit the regions among nodes; use
Delaunay Triangulation algorithm to reconstruct the graph in order to minimize
the interference among nodes. Finally, we use standard deviation to prune off
those longer links (higher interference links) to have a further enhancement.
The proposed hybrid solution is proved to be able to significantly reduce
interference in a wireless mesh network in O(n log n) time complexity.Comment: 24 Pages, JGraph-Hoc Journal 201
Gossip Algorithms for Distributed Signal Processing
Gossip algorithms are attractive for in-network processing in sensor networks
because they do not require any specialized routing, there is no bottleneck or
single point of failure, and they are robust to unreliable wireless network
conditions. Recently, there has been a surge of activity in the computer
science, control, signal processing, and information theory communities,
developing faster and more robust gossip algorithms and deriving theoretical
performance guarantees. This article presents an overview of recent work in the
area. We describe convergence rate results, which are related to the number of
transmitted messages and thus the amount of energy consumed in the network for
gossiping. We discuss issues related to gossiping over wireless links,
including the effects of quantization and noise, and we illustrate the use of
gossip algorithms for canonical signal processing tasks including distributed
estimation, source localization, and compression.Comment: Submitted to Proceedings of the IEEE, 29 page
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