Design of a shaped beam base station antenna using genetic algorithm

2003 ◽  
Vol 20 (1) ◽  
pp. 78-80
Author(s):  
Ying Liu ◽  
Antao Bu ◽  
Shuxi Gong ◽  
Zongzhen Shen ◽  
Liangyong Xiao
Keyword(s):  
Genetic Algorithm ◽  
Base Station ◽  
Shaped Beam

scholarly journals GENETIC ALGORITHM-BASED CLUSTERING OF WIRELESS SENSOR NETWORK WITH NOVEL DATA ENCRYPTION

2017 ◽  
Vol 10 (13) ◽  
pp. 94
Author(s):  
Bachujayendra Kumar ◽  
Rajya Lakshmidevi K ◽  
M Verginraja Sarobin
Keyword(s):  
Genetic Algorithm ◽  
Energy Efficiency ◽  
Information Security ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Data Encryption ◽  
Base Station ◽  
Wireless Sensor ◽  
Clustering Techniques ◽  
Main Challenge

Wireless sensor networks (WSNs) have been used widely in so many applications. It is the most efficient way to monitor the information. There areso many ways to deploy the sensors. Many problems are not identified and solved. The main challenge of WSN is energy efficiency and information security. WSN power consumption is reduced by genetic algorithm-based clustering algorithm. Information from cluster head to base station may have a lot of chances to get hacked. The most reliable way to manage energy consumption is clustering, and encryption will suit best for information security. In this paper, we explain clustering techniques and a new algorithm to encrypt the data in the network.

A Heuristic Optimized Algorithm for Energy Optimization in Wireless Sensor Networks

2010 ◽  
Vol 34-35 ◽  
pp. 1019-1023
Author(s):  
Zhao Feng Yang ◽  
Ai Wan Fan
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Routing Protocols ◽  
Optimal Algorithm ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Adaptive Clustering ◽  
Battery Capacity

Wireless sensor networks consist of hundreds or thousands of sensor nodes that involve numerous restrictions including computation capability and battery capacity. In this paper we propose an optimal algorithm with genetic algorithm taken into consideration, and compare it with three well known and widely used approaches, i.e., LEACH and LEACH-C, in performance evaluation. Experimental results show that the proposed approach increases the overall network lifetime, and data delivery at the base station than the other routing protocols. Key words: Wireless sensor networks, base station, heuristic optimized genetic algorithm, low energy adaptive clustering hierarchy

scholarly journals Energy-efficient genetic algorithm variants of PEGASIS for 3D Wireless Sensor Networks

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Aaqil Somauroo ◽  
Vandana Bassoo
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Residual Energy ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Efficient Routing ◽  
Delay Performance

Due to its boundless potential applications, Wireless Sensor Networks have been subject to much research in the last two decades. WSNs are often deployed in remote environments making replacement of batteries not feasible. Low energy consumption being of prime requisite led to the development of energy-efficient routing protocols. The proposed routing algorithms seek to prolong the lifetime of sensor nodes in the relatively unexplored area of 3D WSNs. The schemes use chain-based routing technique PEGASIS as basis and employ genetic algorithm to build the chain instead of the greedy algorithm. Proposed schemes will incorporate an energy and distance aware CH selection technique to improve load balancing. Clustering of the network is also implemented to reduce number of nodes in a chain and hence reduce delay. Simulation of our proposed protocols is carried out for homogeneous networks considering separately cases for a static base-station inside and outside the network. Results indicate considerable improvement in lifetime over PEGASIS of 817% and 420% for base station inside and outside the network respectively. Residual energy and delay performance are also considered.

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