4,532 research outputs found
Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications
Wireless sensor networks monitor dynamic environments that change rapidly
over time. This dynamic behavior is either caused by external factors or
initiated by the system designers themselves. To adapt to such conditions,
sensor networks often adopt machine learning techniques to eliminate the need
for unnecessary redesign. Machine learning also inspires many practical
solutions that maximize resource utilization and prolong the lifespan of the
network. In this paper, we present an extensive literature review over the
period 2002-2013 of machine learning methods that were used to address common
issues in wireless sensor networks (WSNs). The advantages and disadvantages of
each proposed algorithm are evaluated against the corresponding problem. We
also provide a comparative guide to aid WSN designers in developing suitable
machine learning solutions for their specific application challenges.Comment: Accepted for publication in IEEE Communications Surveys and Tutorial
From carbon nanotubes and silicate layers to graphene platelets for polymer nanocomposites
In spite of extensive studies conducted on carbon nanotubes and silicate layers for their polymer-based nanocomposites, the rise of graphene now provides a more promising candidate due to its exceptionally high mechanical performance and electrical and thermal conductivities. The present study developed a facile approach to fabricate epoxy–graphene nanocomposites by thermally expanding a commercial product followed by ultrasonication and solution-compounding with epoxy, and investigated their morphologies, mechanical properties, electrical conductivity and thermal mechanical behaviour. Graphene platelets (GnPs) of 3.5
Spectrum cartography techniques, challenges, opportunities, and applications: A survey
The spectrum cartography finds applications in several areas such as cognitive radios, spectrum aware communications, machine-type communications, Internet of Things, connected vehicles, wireless sensor networks, and radio frequency management systems, etc. This paper presents a survey on state-of-the-art of spectrum cartography techniques for the construction of various radio environment maps (REMs). Following a brief overview on spectrum cartography, various techniques considered to construct the REMs such as channel gain map, power spectral density map, power map, spectrum map, power propagation map, radio frequency map, and interference map are reviewed. In this paper, we compare the performance of the different spectrum cartography methods in terms of mean absolute error, mean square error, normalized mean square error, and root mean square error. The information presented in this paper aims to serve as a practical reference guide for various spectrum cartography methods for constructing different REMs. Finally, some of the open issues and challenges for future research and development are discussed.publishedVersio
Optimisation of Mobile Communication Networks - OMCO NET
The mini conference “Optimisation of Mobile Communication Networks” focuses on advanced methods for search and optimisation applied to wireless communication networks. It is sponsored by Research & Enterprise Fund Southampton Solent University.
The conference strives to widen knowledge on advanced search methods capable of optimisation of wireless communications networks. The aim is to provide a forum for exchange of recent knowledge, new ideas and trends in this progressive and challenging area. The conference will popularise new successful approaches on resolving hard tasks such as minimisation of transmit power, cooperative and optimal routing
A Crosslayer Routing Protocol (XLRP) for Wireless Sensor Networks
The advent of wireless sensor networks with emphasis on the information being routed, rather than routing information has redefined networking from that of conventional wireless networked systems. Demanding that need for contnt based routing techniques and development of low cost network modules, built to operate in large numbers in a networked fashion with limited resources and capabilities. The unique characteristics of wireless sensor networks have the applicability and effectiveness of conventional algorithms defined for wireless ad-hoc networks, leading to the design and development of protocols specific to wireless sensor network. Many network layer protocols have been proposed for wireless sensor networks, identifying and addressing factors influencing network layer design, this thesis defines a cross layer routing protocol (XLRP) for sensor networks. The submitted work is suggestive of a network layer design with knowledge of application layer information and efficient utilization of physical layer capabilities onboard the sensor modules. Network layer decisions are made based on the quantity of information (size of the data) that needs to be routed and accordingly transmitter power leels are switched as an energy efficient routing strategy. The proposed routing protocol switches radio states based on the received signal strength (RSSI) acquiring only relevant information and piggybacks information in data packets for reduced controlled information exchange. The proposed algorithm has been implemented in Network Simulator (NS2) and the effectiveness of the protocol has been proved in comparison with diffusion paradigm
Modeling the Behavior of an Electronically Switchable Directional Antenna for Wireless Sensor Networks
Reducing power consumption is among the top concerns in Wireless Sensor Networks,
as the lifetime of a Wireless Sensor Network depends on its power consumption. Directional
antennas help achieve this goal contrary to the commonly used omnidirectional
antennas that radiate electromagnetic power equally in all directions, by concentrating
the radiated electromagnetic power only in particular directions. This enables increased
communication range at no additional energy cost and reduces contention on the wireless
medium.
The SPIDA (SICS Parasitic Interference Directional Antenna) prototype is one of the
few real-world prototypes of electronically switchable directional antennas for Wireless
Sensor Networks. However, building several prototypes of SPIDA and conducting
real-world experiments using them may be expensive and impractical. Modeling SPIDA
based on real-world experiments avoids the expenses incurred by enabling simulation
of large networks equipped with SPIDA. Such a model would then allow researchers
to develop new algorithms and protocols that take advantage of the provided
directional communication on existing Wireless Sensor Network simulators.
In this thesis, a model of SPIDA for Wireless Sensor Networks is built based on thoroughly
designed real-world experiments. The thesis builds a probabilistic model that
accounts for variations in measurements, imperfections in the prototype construction,
and fluctuations in experimental settings that affect the values of the measured metrics.
The model can be integrated into existing Wireless Sensor Network simulators to foster
the research of new algorithms and protocols that take advantage of directional communication.
The model returns the values of signal strength and packet reception rate
from a node equipped with SPIDA at a certain point in space given the two-dimensional
distance coordinates of the point and the configuration of SPIDA as inputs
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