4 research outputs found
Deterministic Digital Clustering of Wireless Ad Hoc Networks
We consider deterministic distributed communication in wireless ad hoc
networks of identical weak devices under the SINR model without predefined
infrastructure. Most algorithmic results in this model rely on various
additional features or capabilities, e.g., randomization, access to geographic
coordinates, power control, carrier sensing with various precision of
measurements, and/or interference cancellation. We study a pure scenario, when
no such properties are available. As a general tool, we develop a deterministic
distributed clustering algorithm. Our solution relies on a new type of
combinatorial structures (selectors), which might be of independent interest.
Using the clustering, we develop a deterministic distributed local broadcast
algorithm accomplishing this task in rounds, where
is the density of the network. To the best of our knowledge, this is
the first solution in pure scenario which is only polylog away from the
universal lower bound , valid also for scenarios with
randomization and other features. Therefore, none of these features
substantially helps in performing the local broadcast task. Using clustering,
we also build a deterministic global broadcast algorithm that terminates within
rounds, where is the diameter of the
network. This result is complemented by a lower bound , where is the path-loss parameter of the
environment. This lower bound shows that randomization or knowledge of own
location substantially help (by a factor polynomial in ) in the global
broadcast. Therefore, unlike in the case of local broadcast, some additional
model features may help in global broadcast
Data Dissemination in Unified Dynamic Wireless Networks
We give efficient algorithms for the fundamental problems of Broadcast and
Local Broadcast in dynamic wireless networks. We propose a general model of
communication which captures and includes both fading models (like SINR) and
graph-based models (such as quasi unit disc graphs, bounded-independence
graphs, and protocol model). The only requirement is that the nodes can be
embedded in a bounded growth quasi-metric, which is the weakest condition known
to ensure distributed operability. Both the nodes and the links of the network
are dynamic: nodes can come and go, while the signal strength on links can go
up or down.
The results improve some of the known bounds even in the static setting,
including an optimal algorithm for local broadcasting in the SINR model, which
is additionally uniform (independent of network size). An essential component
is a procedure for balancing contention, which has potentially wide
applicability. The results illustrate the importance of carrier sensing, a
stock feature of wireless nodes today, which we encapsulate in primitives to
better explore its uses and usefulness.Comment: 28 pages, 2 figure
Algorithms for Efficient Communication in Wireless Sensor Networks - Distributed Node Coloring and its Application in the SINR Model
In this thesis we consider algorithms that enable efficient communication in wireless ad-hoc- and sensornetworks using the so-called Signal-to-interference-and-noise-ratio (SINR) model of interference. We propose and experimentally evaluate several distributed node coloring algorithms and show how to use a computed node coloring to establish efficient medium access schedules
A Local Broadcast Layer for the SINR Network Model
We present the first algorithm that implements an abstract MAC (absMAC) layer
in the Signal-to-Interference-plus-Noise-Ratio (SINR) wireless network model.
We first prove that efficient SINR implementations are not possible for the
standard absMAC specification. We modify that specification to an "approximate"
version that better suits the SINR model. We give an efficient algorithm to
implement the modified specification, and use it to derive efficient algorithms
for higher-level problems of global broadcast and consensus.
In particular, we show that the absMAC progress property has no efficient
implementation in terms of the SINR strong connectivity graph ,
which contains edges between nodes of distance at most times the
transmission range, where is a small constant that can be chosen
by the user. This progress property bounds the time until a node is guaranteed
to receive some message when at least one of its neighbors is transmitting.
To overcome this limitation, we introduce the slightly weaker notion of
approximate progress into the absMAC specification. We provide a fast
implementation of the modified specification, based on decomposing a known
algorithm into local and global parts. We analyze our algorithm in terms of
local parameters such as node degrees, rather than global parameters such as
the overall number of nodes. A key contribution is our demonstration that such
a local analysis is possible even in the presence of global interference.
Our absMAC algorithm leads to several new, efficient algorithms for solving
higher-level problems in the SINR model. Namely, by combining our algorithm
with known high-level algorithms, we obtain an improved algorithm for global
single-message broadcast in the SINR model, and the first efficient algorithm
for multi-message broadcast in that model