4,635 research outputs found
Energy Efficient and Reliable Wireless Sensor Networks - An Extension to IEEE 802.15.4e
Collecting sensor data in industrial environments from up to some tenth of
battery powered sensor nodes with sampling rates up to 100Hz requires energy
aware protocols, which avoid collisions and long listening phases. The IEEE
802.15.4 standard focuses on energy aware wireless sensor networks (WSNs) and
the Task Group 4e has published an amendment to fulfill up to 100 sensor value
transmissions per second per sensor node (Low Latency Deterministic Network
(LLDN) mode) to satisfy demands of factory automation. To improve the
reliability of the data collection in the star topology of the LLDN mode, we
propose a relay strategy, which can be performed within the LLDN schedule.
Furthermore we propose an extension of the star topology to collect data from
two-hop sensor nodes. The proposed Retransmission Mode enables power savings in
the sensor node of more than 33%, while reducing the packet loss by up to 50%.
To reach this performance, an optimum spatial distribution is necessary, which
is discussed in detail
On the Power Efficiency of Sensory and Ad Hoc Wireless Networks
We consider the power efficiency of a communications channel, i.e., the maximum bit rate that can be achieved per unit power (energy rate). For additive white Gaussian noise (AWGN) channels, it is well known that power efficiency is attained in the low signal-to-noise ratio (SNR) regime where capacity is proportional to the transmit power. In this paper, we first show that for a random sensory wireless network with n users (nodes) placed in a domain of fixed area, with probability converging to one as n grows, the power efficiency scales at least by a factor of sqrt n. In other words, each user in a wireless channel with n nodes can support the same communication rate as a single-user system, but by expending only 1/(sqrt n) times the energy. Then we look at a random ad hoc network with n relay nodes and r simultaneous transmitter/receiver pairs located in a domain of fixed area. We show that as long as r ≤ sqrt n, we can achieve a power efficiency that scales by a factor of sqrt n. We also give a description of how to achieve these gains
Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey
Wireless sensor networks (WSNs) consist of autonomous and resource-limited
devices. The devices cooperate to monitor one or more physical phenomena within
an area of interest. WSNs operate as stochastic systems because of randomness
in the monitored environments. For long service time and low maintenance cost,
WSNs require adaptive and robust methods to address data exchange, topology
formulation, resource and power optimization, sensing coverage and object
detection, and security challenges. In these problems, sensor nodes are to make
optimized decisions from a set of accessible strategies to achieve design
goals. This survey reviews numerous applications of the Markov decision process
(MDP) framework, a powerful decision-making tool to develop adaptive algorithms
and protocols for WSNs. Furthermore, various solution methods are discussed and
compared to serve as a guide for using MDPs in WSNs
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
Robotic Wireless Sensor Networks
In this chapter, we present a literature survey of an emerging, cutting-edge,
and multi-disciplinary field of research at the intersection of Robotics and
Wireless Sensor Networks (WSN) which we refer to as Robotic Wireless Sensor
Networks (RWSN). We define a RWSN as an autonomous networked multi-robot system
that aims to achieve certain sensing goals while meeting and maintaining
certain communication performance requirements, through cooperative control,
learning and adaptation. While both of the component areas, i.e., Robotics and
WSN, are very well-known and well-explored, there exist a whole set of new
opportunities and research directions at the intersection of these two fields
which are relatively or even completely unexplored. One such example would be
the use of a set of robotic routers to set up a temporary communication path
between a sender and a receiver that uses the controlled mobility to the
advantage of packet routing. We find that there exist only a limited number of
articles to be directly categorized as RWSN related works whereas there exist a
range of articles in the robotics and the WSN literature that are also relevant
to this new field of research. To connect the dots, we first identify the core
problems and research trends related to RWSN such as connectivity,
localization, routing, and robust flow of information. Next, we classify the
existing research on RWSN as well as the relevant state-of-the-arts from
robotics and WSN community according to the problems and trends identified in
the first step. Lastly, we analyze what is missing in the existing literature,
and identify topics that require more research attention in the future
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