7,638 research outputs found
Energy Consumption Of Visual Sensor Networks: Impact Of Spatio-Temporal Coverage
Wireless visual sensor networks (VSNs) are expected to play a major role in
future IEEE 802.15.4 personal area networks (PAN) under recently-established
collision-free medium access control (MAC) protocols, such as the IEEE
802.15.4e-2012 MAC. In such environments, the VSN energy consumption is
affected by the number of camera sensors deployed (spatial coverage), as well
as the number of captured video frames out of which each node processes and
transmits data (temporal coverage). In this paper, we explore this aspect for
uniformly-formed VSNs, i.e., networks comprising identical wireless visual
sensor nodes connected to a collection node via a balanced cluster-tree
topology, with each node producing independent identically-distributed
bitstream sizes after processing the video frames captured within each network
activation interval. We derive analytic results for the energy-optimal
spatio-temporal coverage parameters of such VSNs under a-priori known bounds
for the number of frames to process per sensor and the number of nodes to
deploy within each tier of the VSN. Our results are parametric to the
probability density function characterizing the bitstream size produced by each
node and the energy consumption rates of the system of interest. Experimental
results reveal that our analytic results are always within 7% of the energy
consumption measurements for a wide range of settings. In addition, results
obtained via a multimedia subsystem show that the optimal spatio-temporal
settings derived by the proposed framework allow for substantial reduction of
energy consumption in comparison to ad-hoc settings. As such, our analytic
modeling is useful for early-stage studies of possible VSN deployments under
collision-free MAC protocols prior to costly and time-consuming experiments in
the field.Comment: to appear in IEEE Transactions on Circuits and Systems for Video
Technology, 201
Spatial networks with wireless applications
Many networks have nodes located in physical space, with links more common
between closely spaced pairs of nodes. For example, the nodes could be wireless
devices and links communication channels in a wireless mesh network. We
describe recent work involving such networks, considering effects due to the
geometry (convex,non-convex, and fractal), node distribution,
distance-dependent link probability, mobility, directivity and interference.Comment: Review article- an amended version with a new title from the origina
Big Data Model Simulation on a Graph Database for Surveillance in Wireless Multimedia Sensor Networks
Sensors are present in various forms all around the world such as mobile
phones, surveillance cameras, smart televisions, intelligent refrigerators and
blood pressure monitors. Usually, most of the sensors are a part of some other
system with similar sensors that compose a network. One of such networks is
composed of millions of sensors connect to the Internet which is called
Internet of things (IoT). With the advances in wireless communication
technologies, multimedia sensors and their networks are expected to be major
components in IoT. Many studies have already been done on wireless multimedia
sensor networks in diverse domains like fire detection, city surveillance,
early warning systems, etc. All those applications position sensor nodes and
collect their data for a long time period with real-time data flow, which is
considered as big data. Big data may be structured or unstructured and needs to
be stored for further processing and analyzing. Analyzing multimedia big data
is a challenging task requiring a high-level modeling to efficiently extract
valuable information/knowledge from data. In this study, we propose a big
database model based on graph database model for handling data generated by
wireless multimedia sensor networks. We introduce a simulator to generate
synthetic data and store and query big data using graph model as a big
database. For this purpose, we evaluate the well-known graph-based NoSQL
databases, Neo4j and OrientDB, and a relational database, MySQL.We have run a
number of query experiments on our implemented simulator to show that which
database system(s) for surveillance in wireless multimedia sensor networks is
efficient and scalable
Renormalization group theory for percolation in time-varying networks
Motivated by multi-hop communication in unreliable wireless networks, we
present a percolation theory for time-varying networks. We develop a
renormalization group theory for a prototypical network on a regular grid,
where individual links switch stochastically between active and inactive
states. The question whether a given source node can communicate with a
destination node along paths of active links is equivalent to a percolation
problem. Our theory maps the temporal existence of multi-hop paths on an
effective two-state Markov process. We show analytically how this Markov
process converges towards a memory-less Bernoulli process as the hop distance
between source and destination node increases. Our work extends classical
percolation theory to the dynamic case and elucidates temporal correlations of
message losses. Quantification of temporal correlations has implications for
the design of wireless communication and control protocols, e.g. in
cyber-physical systems such as self-organized swarms of drones or smart traffic
networks.Comment: 8 pages, 3 figure
Towards Energy Neutrality in Energy Harvesting Wireless Sensor Networks: A Case for Distributed Compressive Sensing?
This paper advocates the use of the emerging distributed compressive sensing
(DCS) paradigm in order to deploy energy harvesting (EH) wireless sensor
networks (WSN) with practical network lifetime and data gathering rates that
are substantially higher than the state-of-the-art. In particular, we argue
that there are two fundamental mechanisms in an EH WSN: i) the energy diversity
associated with the EH process that entails that the harvested energy can vary
from sensor node to sensor node, and ii) the sensing diversity associated with
the DCS process that entails that the energy consumption can also vary across
the sensor nodes without compromising data recovery. We also argue that such
mechanisms offer the means to match closely the energy demand to the energy
supply in order to unlock the possibility for energy-neutral WSNs that leverage
EH capability. A number of analytic and simulation results are presented in
order to illustrate the potential of the approach.Comment: 6 pages. This work will be presented at the 2013 IEEE Global
Communications Conference (GLOBECOM), Atlanta, US, December 201
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