9,490 research outputs found
Performance Review of Selected Topology-Aware Routing Strategies for Clustering Sensor Networks
In this paper, cluster-based routing (CBR) protocols for addressing issues pertinent to energy consumption, network lifespan, resource allocation and network coverage are reviewed. The paper presents an indepth performance analysis and critical review of selected CBR algorithms. The study is domain-specific and simulation-based with emphasis on the tripartite trade-off between coverage, connectivity and lifespan. The rigorous statistical analysis of selected CBR schemes was also presented. Network simulation was conducted with Java-based Atarraya discrete-event simulation toolkit while statistical analysis was carried out using MATLAB. It was observed that the Periodic, Event-Driven and Query-Based Routing (PEQ) schemes performs better than Low-Energy Adaptive Clustering Hierarchy (LEACH), Threshold-Sensitive Energy-Efficient Sensor Network (TEEN) and Geographic Adaptive Fidelity (GAF) in terms of network lifespan, energy consumption and network throughput.Keywords: Wireless sensor network, Hierarchical topologies, Cluster-based routing, Statistical analysis, Network simulatio
MODLEACH: A Variant of LEACH for WSNs
Wireless sensor networks are appearing as an emerging need for mankind.
Though, Such networks are still in research phase however, they have high
potential to be applied in almost every field of life. Lots of research is done
and a lot more is awaiting to be standardized. In this work, cluster based
routing in wireless sensor networks is studied precisely. Further, we modify
one of the most prominent wireless sensor network's routing protocol "LEACH" as
modified LEACH (MODLEACH) by introducing \emph{efficient cluster head
replacement scheme} and \emph{dual transmitting power levels}. Our modified
LEACH, in comparison with LEACH out performs it using metrics of cluster head
formation, through put and network life. Afterwards, hard and soft thresholds
are implemented on modified LEACH (MODLEACH) that boast the performance even
more. Finally a brief performance analysis of LEACH, Modified LEACH (MODLEACH),
MODLEACH with hard threshold (MODLEACHHT) and MODLEACH with soft threshold
(MODLEACHST) is undertaken considering metrics of throughput, network life and
cluster head replacements.Comment: IEEE 8th International Conference on Broadband and Wireless
Computing, Communication and Applications (BWCCA'13), Compiegne, Franc
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
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