776 research outputs found
Fundamentals of Large Sensor Networks: Connectivity, Capacity, Clocks and Computation
Sensor networks potentially feature large numbers of nodes that can sense
their environment over time, communicate with each other over a wireless
network, and process information. They differ from data networks in that the
network as a whole may be designed for a specific application. We study the
theoretical foundations of such large scale sensor networks, addressing four
fundamental issues- connectivity, capacity, clocks and function computation.
To begin with, a sensor network must be connected so that information can
indeed be exchanged between nodes. The connectivity graph of an ad-hoc network
is modeled as a random graph and the critical range for asymptotic connectivity
is determined, as well as the critical number of neighbors that a node needs to
connect to. Next, given connectivity, we address the issue of how much data can
be transported over the sensor network. We present fundamental bounds on
capacity under several models, as well as architectural implications for how
wireless communication should be organized.
Temporal information is important both for the applications of sensor
networks as well as their operation.We present fundamental bounds on the
synchronizability of clocks in networks, and also present and analyze
algorithms for clock synchronization. Finally we turn to the issue of gathering
relevant information, that sensor networks are designed to do. One needs to
study optimal strategies for in-network aggregation of data, in order to
reliably compute a composite function of sensor measurements, as well as the
complexity of doing so. We address the issue of how such computation can be
performed efficiently in a sensor network and the algorithms for doing so, for
some classes of functions.Comment: 10 pages, 3 figures, Submitted to the Proceedings of the IEE
Reliable Physical Layer Network Coding
When two or more users in a wireless network transmit simultaneously, their
electromagnetic signals are linearly superimposed on the channel. As a result,
a receiver that is interested in one of these signals sees the others as
unwanted interference. This property of the wireless medium is typically viewed
as a hindrance to reliable communication over a network. However, using a
recently developed coding strategy, interference can in fact be harnessed for
network coding. In a wired network, (linear) network coding refers to each
intermediate node taking its received packets, computing a linear combination
over a finite field, and forwarding the outcome towards the destinations. Then,
given an appropriate set of linear combinations, a destination can solve for
its desired packets. For certain topologies, this strategy can attain
significantly higher throughputs over routing-based strategies. Reliable
physical layer network coding takes this idea one step further: using
judiciously chosen linear error-correcting codes, intermediate nodes in a
wireless network can directly recover linear combinations of the packets from
the observed noisy superpositions of transmitted signals. Starting with some
simple examples, this survey explores the core ideas behind this new technique
and the possibilities it offers for communication over interference-limited
wireless networks.Comment: 19 pages, 14 figures, survey paper to appear in Proceedings of the
IEE
Characterization, Avoidance and Repair of Packet Collisions in Inter-Vehicle Communication Networks
This work proposes a combined and accurate simulation of wireless channel, physical layer and networking aspects in order to bridge the gaps between the corresponding research communities. The resulting high fidelity simulations enable performance optimizations across multiple layers, and are used in the second part of this thesis to evaluate the impact of fast-fading channel characteristics on Carrier-Sense Multiple Access, and to quantify the benefit of successive interference cancellation
Characterization, Avoidance and Repair of Packet Collisions in Inter-Vehicle Communication Networks
This work proposes a combined and accurate simulation of wireless channel, physical layer and networking aspects in order to bridge the gaps between the corresponding research communities. The resulting high fidelity simulations enable performance optimizations across multiple layers, and are used in the second part of this thesis to evaluate the impact of fast-fading channel characteristics on Carrier-Sense Multiple Access, and to quantify the benefit of successive interference cancellation
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
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