Optimal Placement of Wireless Sensor Nodes with Fault Tolerance and Minimal Energy Consumption

2006 ◽  
Author(s):  
Shafaq Chaudhry ◽  
Victor Hung ◽  
Ratan Guha
Keyword(s):  
Energy Consumption ◽  
Fault Tolerance ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Optimal Placement ◽  
Minimal Energy ◽  
Wireless Sensor Nodes

scholarly journals Calculating the Number of Cluster Heads Based on the Rate-Distortion Function in Wireless Sensor Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-7
Author(s):  
Mingxin Yang ◽  
Jingsha He ◽  
Yuqiang Zhang
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Fusion ◽  
Rate Distortion ◽  
Distortion Function ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Wireless Sensor Nodes ◽  
Cluster Heads

Due to limited resources in wireless sensor nodes, energy efficiency is considered as one of the primary constraints in the design of the topology of wireless sensor networks (WSNs). Since data that are collected by wireless sensor nodes exhibit the characteristics of temporal association, data fusion has also become a very important means of reducing network traffic as well as eliminating data redundancy as far as data transmission is concerned. Another reason for data fusion is that, in many applications, only some of the data that are collected can meet the requirements of the sink node. In this paper, we propose a method to calculate the number of cluster heads or data aggregators during data fusion based on the rate-distortion function. In our discussion, we will first establish an energy consumption model and then describe a method for calculating the number of cluster heads from the point of view of reducing energy consumption. We will also show through theoretical analysis and experimentation that the network topology design based on the rate-distortion function is indeed more energy-efficient.

A New Clustering Routing Algorithm for WSN Based on PSO

2013 ◽  
Vol 850-851 ◽  
pp. 689-692
Author(s):  
Li Fu Wang ◽  
Jian Ding ◽  
Zhi Kong
Keyword(s):  
Energy Consumption ◽  
Clustering Algorithm ◽  
Routing Algorithm ◽  
Cluster Head ◽  
Pso Algorithm ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Long Distance ◽  
Wireless Sensor Nodes ◽  
Spatially Distributed

A wireless sensor network (WSN) consists of spatially distributed wireless sensor nodes. The node power constrains the development of WSN. Employing techniques of clustering can reduce energy consumption of wireless sensor nodes and prolong the network lifetime. Therefore, in the study a new clustering routing algorithm is presented. The clustering algorithm uses the double-layer sensor nodes to communicate. And in order to optimize power energy consumption for WSN node energy, PSO algorithm is employed to find cluster head in each layer. Simulation results show that the algorithm not only can equal power energy of node, but also can reduce consumption in the long distance data transmission.

scholarly journals A Novel Hybrid HNN and Firefly Algorithm to Overcome Denial of Sleep Attack on Wireless Sensor Nodes

2021 ◽  
Vol 2 (4) ◽  
pp. 223-227
Author(s):  
Vivekanadam B
Keyword(s):  
Energy Consumption ◽  
Firefly Algorithm ◽  
Data Transfer ◽  
Hopfield Neural Network ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sleep Mode ◽  
Wireless Sensor Nodes ◽  
Sleep Attack ◽  
Energy Consumption Patterns

A typical Wireless Sensor Network (WSN) comprises of multiple nodes that are used to control as well as monitor the environment and perform pre-described actions. Based on the network, the sensor nodes are distributed and their energy consumption proves to be challenging. When the nodes are located near the sink, they serve as the interface for data transfer between the sink and the node. Because of this, there is a decrease in the networks lifetime and further the energy consumption of the nodes increases significantly. Denial-of-sleep attack is a threat that sensor nodes face in WSNs. DoSA is the condition when there is much loss of energy at the nodes by preventing them from entering into sleep mode and power save mode. We propose a hybrid methodology of Hopfield neural network and firefly algorithm using leach to tackle this issue such that there is a significant increase in network lifetime and energy consumption patterns.

Petri net based evaluation of energy consumption in wireless sensor nodes

2013 ◽  
Vol 19 (4) ◽  
pp. 339-358 ◽  
Author(s):  
Maurizio D'Arienzo ◽  
Mauro Iacono ◽  
Stefano Marrone ◽  
Roberto Nardone
Keyword(s):  
Energy Consumption ◽  
Petri Net ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Wireless Sensor Nodes

Short-Hops vs. Long-Hops

2014 ◽  
pp. 74-83
Author(s):  
Mekkaoui Kheireddine ◽  
Rahmoun Abdellatif
Keyword(s):  
Energy Source ◽  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Large Area ◽  
Wireless Sensor Nodes ◽  
Energy Consuming

Sensor networks are composed of miniaturized wireless sensor nodes with limited capacity and energy source. Generally, these sensor networks are used, in many applications, to monitor inaccessible environments (battlefields, volcano monitoring, animal tracking…), hence the impossibility to replace or to recharge the batteries. As sensors may be deployed in a large area, radio transceivers are the most energy consuming of sensor nodes, which means that their usage needs to be very efficient in order to maximize node life, which leads us to maximize the network's life. In wireless sensor networks and in order to transmit its data, a node can route its messages towards destination, generally the base station, either by using small or large hops, so optimizing the hop length can extend significantly the lifetime of the network. This chapter provides a simple way to verify, which makes the energy consumption minimal by choosing proper hop length.

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