3,722 research outputs found
FEHCA: A Fault-Tolerant Energy-Efficient Hierarchical Clustering Algorithm for Wireless Sensor Networks
Technological advancements have led to increased confidence in the design of large-scale wireless networks that comprise small energy constraint devices. Despite the boost in technological advancements, energy dissipation and fault tolerance are amongst the key deciding factors while designing and deploying wireless sensor networks. This paper proposes a Fault-tolerant Energy-efficient Hierarchical Clustering Algorithm (FEHCA) for wireless sensor networks (WSNs), which demonstrates energy-efficient clustering and fault-tolerant operation of cluster heads (CHs). It treats CHs as no special node but equally prone to faults as normal sensing nodes of the cluster. The proposed scheme addresses some of the limitations of prominent hierarchical clustering algorithms, such as the randomized election of the cluster heads after each round, which results in significant energy dissipation; non-consideration of the residual energy of the sensing nodes while selecting cluster heads, etc. It utilizes the capability of vector quantization to partition the deployed sensors into an optimal number of clusters and ensures that almost the entire area to be monitored is alive for most of the networkâs lifetime. This supports better decision-making compared to decisions made on the basis of limited area sensing data after a few rounds of communication. The scheme is implemented for both friendly as well as hostile deployments. The simulation results are encouraging and validate the proposed algorithm.articl
Analyzing Energy-efficiency and Route-selection of Multi-level Hierarchal Routing Protocols in WSNs
The advent and development in the field of Wireless Sensor Networks (WSNs) in
recent years has seen the growth of extremely small and low-cost sensors that
possess sensing, signal processing and wireless communication capabilities.
These sensors can be expended at a much lower cost and are capable of detecting
conditions such as temperature, sound, security or any other system. A good
protocol design should be able to scale well both in energy heterogeneous and
homogeneous environment, meet the demands of different application scenarios
and guarantee reliability. On this basis, we have compared six different
protocols of different scenarios which are presenting their own schemes of
energy minimizing, clustering and route selection in order to have more
effective communication. This research is motivated to have an insight that
which of the under consideration protocols suit well in which application and
can be a guide-line for the design of a more robust and efficient protocol.
MATLAB simulations are performed to analyze and compare the performance of
LEACH, multi-level hierarchal LEACH and multihop LEACH.Comment: NGWMN with 7th IEEE Inter- national Conference on Broadband and
Wireless Computing, Communication and Applications (BWCCA 2012), Victoria,
Canada, 201
Overlapping Multi-hop Clustering for Wireless Sensor Networks
Clustering is a standard approach for achieving efficient and scalable
performance in wireless sensor networks. Traditionally, clustering algorithms
aim at generating a number of disjoint clusters that satisfy some criteria. In
this paper, we formulate a novel clustering problem that aims at generating
overlapping multi-hop clusters. Overlapping clusters are useful in many sensor
network applications, including inter-cluster routing, node localization, and
time synchronization protocols. We also propose a randomized, distributed
multi-hop clustering algorithm (KOCA) for solving the overlapping clustering
problem. KOCA aims at generating connected overlapping clusters that cover the
entire sensor network with a specific average overlapping degree. Through
analysis and simulation experiments we show how to select the different values
of the parameters to achieve the clustering process objectives. Moreover, the
results show that KOCA produces approximately equal-sized clusters, which
allows distributing the load evenly over different clusters. In addition, KOCA
is scalable; the clustering formation terminates in a constant time regardless
of the network size
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 epoxyâgraphene 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
The Energy Complexity of Broadcast
Energy is often the most constrained resource in networks of battery-powered
devices, and as devices become smaller, they spend a larger fraction of their
energy on communication (transceiver usage) not computation. As an imperfect
proxy for true energy usage, we define energy complexity to be the number of
time slots a device transmits/listens; idle time and computation are free.
In this paper we investigate the energy complexity of fundamental
communication primitives such as broadcast in multi-hop radio networks. We
consider models with collision detection (CD) and without (No-CD), as well as
both randomized and deterministic algorithms. Some take-away messages from this
work include:
1. The energy complexity of broadcast in a multi-hop network is intimately
connected to the time complexity of leader election in a single-hop (clique)
network. Many existing lower bounds on time complexity immediately transfer to
energy complexity. For example, in the CD and No-CD models, we need
and energy, respectively.
2. The energy lower bounds above can almost be achieved, given sufficient
() time. In the CD and No-CD models we can solve broadcast using
energy and energy,
respectively.
3. The complexity measures of Energy and Time are in conflict, and it is an
open problem whether both can be minimized simultaneously. We give a tradeoff
showing it is possible to be nearly optimal in both measures simultaneously.
For any constant , broadcast can be solved in
time with
energy, where is the diameter of the network
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