10,227 research outputs found
Scale-free topology optimization for software-defined wireless sensor networks: A cyber-physical system
Due to the limited resource and vulnerability in wireless sensor networks, maximizing the network lifetime and improving
network survivability have become the top priority problem in network topology optimization. This article presents
a wireless sensor networks topology optimization model based on complex network theory and cyber-physical systems
using software-defined wireless sensor network architecture. The multiple-factor-driven virtual force field and network
division–oriented particle swarm algorithm are introduced into the deployment strategy of super-node for the implementation
in wireless sensor networks topology initialization, which help to rationally allocate heterogeneous network
resources and balance the energy consumption in wireless sensor networks. Furthermore, the preferential attachment
scheme guided by corresponding priority of crucial sensors is added into scale-free structure for optimization in topology
evolution process and for protection of vulnerable nodes in wireless sensor networks. Software-defined wireless
sensor network–based functional architecture is adopted to optimize the network evolution rules and algorithm parameters
using information cognition and flow-table configure mode. The theoretical analysis and experimental results
demonstrate that the proposed wireless sensor networks topology optimization model possesses both the small-world
effect and the scale-free property, which can contribute to extend the lifetime of wireless sensor networks with energy
efficiency and improve the robustness of wireless sensor networks with structure invulnerability
Un nuevo esquema de agrupación para redes sensoras inalámbricas de radio cognitivas heterogéneas
Introduction: This article is the product of the research “Learning-based Spectrum Analysis and Prediction in Cognitive Radio Sensor Networks”, developed at Sejong University in the year 2019.
Problem: Most of the clustering schemes for distributed cognitive radio-enabled wireless sensor networks consider homogeneous cognitive radio-enabled wireless sensors. Many clustering schemes for such homogeneouscognitive radio-enabled wireless sensor networks waste resources and suffer from energy inefficiency because of the unnecessary overheads.
Objective: The objective of the research is to propose a node clustering scheme that conserves energy and prolongs network lifetime.
Methodology: A heterogeneous cognitive radio-enabled wireless sensor network in which only a few nodes have a cognitive radio module and the other nodes are normal sensor nodes. Along with the hardware cost, theproposed scheme is efficient in energy consumption.
Results: We simulated the proposed scheme and compared it with the homogeneous cognitive radio-enabled wireless sensor networks. The results show that the proposed scheme is efficient in terms of energyconsumption.
Conclusion: The proposed node clustering scheme performs better in terms of network energy conservation and network partition.
Originality: There are heterogeneous node clustering schemes in the literature for cooperative spectrum sensing and energy efficiency, but to the best of our knowledge, there is no study that proposes a non-cognitiveradio-enabled sensor clustering for energy conservation along with cognitive radio-enabled wireless sensors.
Limitations: The deployment of the proposed special device for cognitive radio-enabled wireless sensors is complicated and requires special hardware with better battery powered cognitive sensor nodes
Performance Comparison of Heterogeneous EESAA in Two and Three Dimensional Wireless Sensor Networks
Wireless Sensor Network is the network of limited power, computational and storage sensing devices called sensors. These sensors sense and send out data to other sensors present in the network. A considerable amount of energy is dissipated in these tasks. Clustered techniques have been employed to optimize energy consumption in the energy constrained wireless sensor networks. The paper presents analysis of heterogeneous Energy Efficient Sleep Awake Aware (EESAA) Intelligent Sensor Network Routing Protocol in three dimensional spaces of a WSN in order to prolong the network lifetime. The reason behind 3D space, instead of 2D plane is its feasible and practical equivalence to the real world
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
Movement-Efficient Sensor Deployment in Wireless Sensor Networks With Limited Communication Range.
We study a mobile wireless sensor network (MWSN) consisting of multiple
mobile sensors or robots. Three key factors in MWSNs, sensing quality, energy
consumption, and connectivity, have attracted plenty of attention, but the
interaction of these factors is not well studied. To take all the three factors
into consideration, we model the sensor deployment problem as a constrained
source coding problem. %, which can be applied to different coverage tasks,
such as area coverage, target coverage, and barrier coverage. Our goal is to
find an optimal sensor deployment (or relocation) to optimize the sensing
quality with a limited communication range and a specific network lifetime
constraint. We derive necessary conditions for the optimal sensor deployment in
both homogeneous and heterogeneous MWSNs. According to our derivation, some
sensors are idle in the optimal deployment of heterogeneous MWSNs. Using these
necessary conditions, we design both centralized and distributed algorithms to
provide a flexible and explicit trade-off between sensing uncertainty and
network lifetime. The proposed algorithms are successfully extended to more
applications, such as area coverage and target coverage, via properly selected
density functions. Simulation results show that our algorithms outperform the
existing relocation algorithms
M-GEAR: Gateway-Based Energy-Aware Multi-Hop Routing Protocol for WSNs
In this research work, we advise gateway based energy-efficient routing
protocol (M-GEAR) for Wireless Sensor Networks (WSNs). We divide the sensor
nodes into four logical regions on the basis of their location in the sensing
field. We install Base Station (BS) out of the sensing area and a gateway node
at the centre of the sensing area. If the distance of a sensor node from BS or
gateway is less than predefined distance threshold, the node uses direct
communication. We divide the rest of nodes into two equal regions whose
distance is beyond the threshold distance. We select cluster heads (CHs)in each
region which are independent of the other region. These CHs are selected on the
basis of a probability. We compare performance of our protocol with LEACH (Low
Energy Adaptive Clustering Hierarchy). Performance analysis and compared
statistic results show that our proposed protocol perform well in terms of
energy consumption and network lifetime.Comment: IEEE 8th International Conference on Broadband and Wireless
Computing, Communication and Applications (BWCCA'13), Compiegne, Franc
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