297 research outputs found
QoS Constrained Optimal Sink and Relay Placement in Planned Wireless Sensor Networks
We are given a set of sensors at given locations, a set of potential
locations for placing base stations (BSs, or sinks), and another set of
potential locations for placing wireless relay nodes. There is a cost for
placing a BS and a cost for placing a relay. The problem we consider is to
select a set of BS locations, a set of relay locations, and an association of
sensor nodes with the selected BS locations, so that number of hops in the path
from each sensor to its BS is bounded by hmax, and among all such feasible
networks, the cost of the selected network is the minimum. The hop count bound
suffices to ensure a certain probability of the data being delivered to the BS
within a given maximum delay under a light traffic model. We observe that the
problem is NP-Hard, and is hard to even approximate within a constant factor.
For this problem, we propose a polynomial time approximation algorithm
(SmartSelect) based on a relay placement algorithm proposed in our earlier
work, along with a modification of the greedy algorithm for weighted set cover.
We have analyzed the worst case approximation guarantee for this algorithm. We
have also proposed a polynomial time heuristic to improve upon the solution
provided by SmartSelect. Our numerical results demonstrate that the algorithms
provide good quality solutions using very little computation time in various
randomly generated network scenarios
An Approximate Inner Bound to the QoS Aware Throughput Region of a Tree Network under IEEE 802.15.4 CSMA/CA and Application to Wireless Sensor Network Design
We consider a tree network spanning a set of source nodes that generate
measurement packets, a set of additional relay nodes that only forward packets
from the sources, and a data sink. We assume that the paths from the sources to
the sink have bounded hop count. We assume that the nodes use the IEEE 802.15.4
CSMA/CA for medium access control, and that there are no hidden terminals. In
this setting, starting with a set of simple fixed point equations, we derive
sufficient conditions for the tree network to approximately satisfy certain
given QoS targets such as end-to-end delivery probability and delay under a
given rate of generation of measurement packets at the sources (arrival rates
vector). The structures of our sufficient conditions provide insight on the
dependence of the network performance on the arrival rate vector, and the
topological properties of the network. Furthermore, for the special case of
equal arrival rates, default backoff parameters, and for a range of values of
target QoS, we show that among all path-length-bounded trees (spanning a given
set of sources and BS) that meet the sufficient conditions, a shortest path
tree achieves the maximum throughput
Impromptu Deployment of Wireless Relay Networks: Experiences Along a Forest Trail
We are motivated by the problem of impromptu or as- you-go deployment of
wireless sensor networks. As an application example, a person, starting from a
sink node, walks along a forest trail, makes link quality measurements (with
the previously placed nodes) at equally spaced locations, and deploys relays at
some of these locations, so as to connect a sensor placed at some a priori
unknown point on the trail with the sink node. In this paper, we report our
experimental experiences with some as-you-go deployment algorithms. Two
algorithms are based on Markov decision process (MDP) formulations; these
require a radio propagation model. We also study purely measurement based
strategies: one heuristic that is motivated by our MDP formulations, one
asymptotically optimal learning algorithm, and one inspired by a popular
heuristic. We extract a statistical model of the propagation along a forest
trail from raw measurement data, implement the algorithms experimentally in the
forest, and compare them. The results provide useful insights regarding the
choice of the deployment algorithm and its parameters, and also demonstrate the
necessity of a proper theoretical formulation.Comment: 7 pages, accepted in IEEE MASS 201
Network coding for reliable wireless sensor networks
Wireless sensor networks are used in many applications and are now a key element
in the increasingly growing Internet of Things. These networks are composed of
small nodes including wireless communication modules, and in most of the cases
are able to autonomously con gure themselves into networks, to ensure sensed data
delivery. As more and more sensor nodes and networks join the Internet of Things,
collaboration between geographically distributed systems are expected. Peer to peer
overlay networks can assist in the federation of these systems, for them to collaborate.
Since participating peers/proxies contribute to storage and processing, there is no
burden on speci c servers and bandwidth bottlenecks are avoided.
Network coding can be used to improve the performance of wireless sensor networks.
The idea is for data from multiple links to be combined at intermediate encoding
nodes, before further transmission. This technique proved to have a lot of potential
in a wide range of applications. In the particular case of sensor networks, network
coding based protocols and algorithms try to achieve a balance between low packet
error rate and energy consumption. For network coding based constrained networks
to be federated using peer to peer overlays, it is necessary to enable the storage
of encoding vectors and coded data by such distributed storage systems. Packets
can arrive to the overlay through any gateway/proxy (peers in the overlay), and lost
packets can be recovered by the overlay (or client) using original and coded data that
has been stored. The decoding process requires a decoding service at the overlay
network. Such architecture, which is the focus of this thesis, will allow constrained
networks to reduce packet error rate in an energy e cient way, while bene ting from an e ective distributed storage solution for their federation. This will serve as
a basis for the proposal of mathematical models and algorithms that determine the
most e ective routing trees, for packet forwarding toward sink/gateway nodes, and
best amount and placement of encoding nodes.As redes de sensores sem fios são usadas em muitas aplicações e são hoje consideradas um elemento-chave para o desenvolvimento da Internet das Coisas. Compostas por nós de pequena dimensão que incorporam módulos de comunicação sem fios, grande parte destas redes possuem a capacidade de se configurarem de forma autónoma, formando sistemas em rede para garantir a entrega dos dados recolhidos. (…
Sequential Decision Algorithms for Measurement-Based Impromptu Deployment of a Wireless Relay Network along a Line
We are motivated by the need, in some applications, for impromptu or
as-you-go deployment of wireless sensor networks. A person walks along a line,
starting from a sink node (e.g., a base-station), and proceeds towards a source
node (e.g., a sensor) which is at an a priori unknown location. At equally
spaced locations, he makes link quality measurements to the previous relay, and
deploys relays at some of these locations, with the aim to connect the source
to the sink by a multihop wireless path. In this paper, we consider two
approaches for impromptu deployment: (i) the deployment agent can only move
forward (which we call a pure as-you-go approach), and (ii) the deployment
agent can make measurements over several consecutive steps before selecting a
placement location among them (which we call an explore-forward approach). We
consider a light traffic regime, and formulate the problem as a Markov decision
process, where the trade-off is among the power used by the nodes, the outage
probabilities in the links, and the number of relays placed per unit distance.
We obtain the structures of the optimal policies for the pure as-you-go
approach as well as for the explore-forward approach. We also consider natural
heuristic algorithms, for comparison. Numerical examples show that the
explore-forward approach significantly outperforms the pure as-you-go approach.
Next, we propose two learning algorithms for the explore-forward approach,
based on Stochastic Approximation, which asymptotically converge to the set of
optimal policies, without using any knowledge of the radio propagation model.
We demonstrate numerically that the learning algorithms can converge (as
deployment progresses) to the set of optimal policies reasonably fast and,
hence, can be practical, model-free algorithms for deployment over large
regions.Comment: 29 pages. arXiv admin note: text overlap with arXiv:1308.068
On Modeling Geometric Joint Sink Mobility with Delay-Tolerant Cluster-less Wireless Sensor Networks
Moving Sink (MS) in Wireless Sensor Networks (WSNs) has appeared as a
blessing because it collects data directly from the nodes where the concept of
relay nodes is becomes obsolete. There are, however, a few challenges to be
taken care of, like data delay tolerance and trajectory of MS which is NP-hard.
In our proposed scheme, we divide the square field in small squares. Middle
point of the partitioned area is the sojourn location of the sink, and nodes
around MS are in its transmission range, which send directly the sensed data in
a delay-tolerant fashion. Two sinks are moving simultaneously; one inside and
having four sojourn locations and other in outer trajectory having twelve
sojourn locations. Introduction of the joint mobility enhances network life and
ultimately throughput. As the MS comes under the NP-hard problem, we convert it
into a geometric problem and define it as, Geometric Sink Movement (GSM). A set
of linear programming equations has also been given in support of GSM which
prolongs network life time
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