Countermeasure for intelligent cluster-head jamming attack in wireless sensor network

2013 ◽  
Author(s):  
Sachin D. Babar ◽  
Neeli R. Prasad ◽  
Ramjee Prasad
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Cluster Head ◽  
Wireless Sensor ◽  
Jamming Attack

Jamming Attack in Wireless Sensor Network: From Time to Space

2012 ◽  
Vol E95.B (6) ◽  
pp. 2113-2116
Author(s):  
Yanqiang SUN ◽  
Xiaodong WANG ◽  
Xingming ZHOU
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Wireless Sensor ◽  
Jamming Attack

scholarly journals E-FUCA: enhancement in fuzzy unequal clustering and routing for sustainable wireless sensor network

2021 ◽  
Author(s):  
Pawan Singh Mehra
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Cluster Head ◽  
Average Energy ◽  
Base Station ◽  
Wireless Sensor ◽  
Unequal Clustering ◽  
Energy Hole ◽  
Intelligent Decision ◽  
Improved Performance

AbstractWith huge cheap micro-sensing devices deployed, wireless sensor network (WSN) gathers information from the region and delivers it to the base station (BS) for further decision. The hotspot problem occurs when cluster head (CH) nearer to BS may die prematurely due to uneven energy depletion resulting in partitioning the network. To overcome the issue of hotspot or energy hole, unequal clustering is used where variable size clusters are formed. Motivated from the aforesaid discussion, we propose an enhanced fuzzy unequal clustering and routing protocol (E-FUCA) where vital parameters are considered during CH candidate selection, and intelligent decision using fuzzy logic (FL) is taken by non-CH nodes during the selection of their CH for the formation of clusters. To further extend the lifetime, we have used FL for the next-hop choice for efficient routing. We have conducted the simulation experiments for four scenarios and compared the propound protocol’s performance with recent similar protocols. The experimental results validate the improved performance of E-FUCA with its comparative in respect of better lifetime, protracted stability period, and enhanced average energy.

scholarly journals Honey Bee Optimization based Sink Mobility Aware Heterogeneous Protocol for Wireless Sensor Network

2019 ◽  
Vol 20 (4) ◽  
pp. 591-598 ◽  
Author(s):  
Ashish Kumar Luhach ◽  
Aditya Khamparia ◽  
Ravindra Sihag ◽  
Raj Kumar
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Honey Bee ◽  
Heterogeneous Network ◽  
Cluster Head ◽  
Wireless Sensor ◽  
Research Issues ◽  
Data Packets ◽  
Industrial Monitoring ◽  
The Stability

Wireless Sensor Network (WSN) has emerged as one of the most important technologies serving an array of solutions for critical applications such as defense, industrial monitoring and decision purposes. Data routing in WSN is effective or non-effective depending upon the energy saving for nodes while transferring data packets to the sink. Mainly WSN divided into two modes; heterogeneous and homogeneous. Heterogeneous network in WSN mainly focused on the cluster head selection. Sink mobility in the heterogeneous network has still many open research issues, it is observed that it makes the network more energy efficient. The optimization in the network leads to the stability of the network at a much higher level. In this paper, the sink mobility is optimized for WSN using Honey Bee Optimization (HBO) technique by considering the parameters such as energy and distance. The proposed protocol shows significant improvement in the stability period by 33 % by covering 2928 rounds and enhanced network lifetime by 1500 rounds in compared with 2033 and 14084 rounds for iMBEENISH protocol respectively.

scholarly journals An Enhanced Clustering Method for Extending Sensing Lifetime of Wireless Sensor Network

2021 ◽  
pp. 67-82
Author(s):  
Yakubu Abdul-Wahab Nawusu ◽  
Alhassan Abdul-Barik ◽  
Salifu Abdul-Mumin
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Network Performance ◽  
Rank Order ◽  
Cluster Head ◽  
Residual Energy ◽  
Base Station ◽  
Wireless Sensor ◽  
Cluster Heads ◽  
Heterogeneous Wireless Sensor Network

Extending the lifetime of a wireless sensor network is vital in ensuring continuous monitoring functions in a target environment. Many techniques have appeared that seek to achieve such prolonged sensing gains. Clustering and improved selection of cluster heads play essential roles in the performance of sensor network functions. Cluster head in a hierarchical arrangement is responsible for transmitting aggregated data from member nodes to a base station for further user-specific data processing and analysis. Minimising the quick dissipation of cluster heads energy requires a careful choice of network factors when selecting a cluster head to prolong the lifetime of a wireless sensor network. In this work, we propose a multi-criteria cluster head selection technique to extend the sensing lifetime of a heterogeneous wireless sensor network. The proposed protocol incorporates residual energy, distance, and node density in selecting a cluster head. Each factor is assigned a weight using the Rank Order Centroid based on its relative importance. Several simulation tests using MATLAB 7.5.0 (R2007b) reveal improved network lifetime and other network performance indicators, including stability and throughput, compared with popular protocols such as LEACH and the SEP. The proposed scheme will be beneficial in applications requiring reliable and stable data sensing and transmission functions.

scholarly journals Unequal Clustering Multipath Routing Algorithm for Wireless Sensor Network based on Clustering and Ant Colony

2021 ◽  
Vol 3 (3) ◽  
pp. 156-160
Author(s):  
Jin Yong-xian
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Routing Algorithm ◽  
Multipath Routing ◽  
Cluster Head ◽  
Optimal Number ◽  
Wireless Sensor ◽  
Unequal Clustering ◽  
Selection Probability ◽  
Factor Node

To improve the energy efficiency of the wireless sensor network (WSN), and extend the network life. This paper proposes an improved unequal clustering multipath routing algorithm (UCMRA). The algorithm improves the formula of cluster head selection probability and competition radius, and considers the energy factor, node density, optimal number of cluster heads, etc. Experimental results show that, compared with the traditional algorithm, UCMRA has more stable cluster head distribution, less energy consumption and longer network lifetime.

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