scholarly journals Enhanced Artificial Bee Colony method for node deployment and routing in Wireless Sensor Networks

2021 ◽  
pp. 28-37
Author(s):  
Basavaraj Madagouda ◽  
R. Sumathi
Keyword(s):  
Sensor Networks ◽  
Artificial Bee Colony ◽  
Wireless Networking ◽  
Home Automation ◽  
Coverage Area ◽  
Bee Colony ◽  
Implementation Techniques ◽  
Military Applications ◽  
A New Technique ◽  
Architectural Survey

Wireless networks provide small sensing, machine and wireless networking nodes. Different designs and implementation techniques were built based on the device requirements for wireless network sensors (WSN). Sensor networks are used in various applications, such as environmental monitoring, home automation, military applications, etc. In this study introduce an architectural survey and deployment of nodes in the Wi-Fi Sensor network in this article. The environmental features that can be added to the sensor networks are given. The program relies on the node installed in the WSN and is deterministic or random. But the biggest issue in both cases is the coverage of the region involved. Researcher also describe WSN routing protocols. In this paper, a new technique to deployment problem is proposed based on the artificial bee colony (ABC) algorithm which is enhanced for the deployment of sensor networks to gain better performance by trying to increase the coverage area of the network and energy consumption. The good performance of the proposed EABC algorithm shows that it can be utilized in the deployment of WSN.

scholarly journals Ayurvedic Plant Identification using Image Processing and Artificial Intelligence

2021 ◽  
pp. 212-218
Author(s):  
Amey Sunil Deshmukh ◽  
Pushppavisha Mani Mudhaliar ◽  
Dr. Surabhi Thorat
Keyword(s):  
Sensor Networks ◽  
Wireless Networking ◽  
Home Automation ◽  
Plant Identification ◽  
Coverage Area ◽  
Bee Colony ◽  
Implementation Techniques ◽  
Military Applications ◽  
A New Technique ◽  
Architectural Survey

Wireless networks provide small sensing, machine and wireless networking nodes. Different designs and implementation techniques were built based on the device requirements for wireless network sensors (WSN). Sensor networks are used in various applications, such as environmental monitoring, home automation, military applications, etc. In this study introduce an architectural survey and deployment of nodes in the Wi-Fi Sensor network in this article. The environmental features that can be added to the sensor networks are given. The program relies on the node installed in the WSN and is deterministic or random. But the biggest issue in both cases is the coverage of the region involved. Researcher also describe WSN routing protocols. In this paper, a new technique to deployment problem is proposed based on the artificial bee colony (ABC) algorithm which is enhanced for the deployment of sensor networks to gain better performance by trying to increase the coverage area of the network and energy consumption. The good performance of the proposed EABC algorithm shows that it can be utilized in the deployment of WSN.

scholarly journals Deployment in wireless sensor networks by parallel and cooperative parallel artificial bee colony algorithms

2018 ◽  
Vol 9 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Selcuk Aslan
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Artificial Bee Colony ◽  
Experimental Studies ◽  
Wireless Sensor ◽  
Main Concern ◽  
Computational Power ◽  
Cooperative Model ◽  
Bee Colony ◽  
Algorithmic Approaches

Increasing number of cores in a processor chip and decreasing cost of distributed memory based system setup have led to emerge of a new work theme in which the main concern focused on the parallelization of the well-known algorithmic approaches for utilizing the computational power of the current architectures. In this study, the performances of the conventional parallel and cooperative model based parallel Artificial Bee Colony (ABC) algorithms on the deployment problem related to the wireless sensor networks were investigated. The results obtained from the experimental studies showed that parallelized ABC algorithm with the cooperative model is capable of finding similar or better coverage ratios with the increased convergence speeds than its serial counterpart and parallelized implementation in which the emigrant is chosen as the best food source in the current subcolony.

scholarly journals A Hybrid Artificial Bee Colony and Bacterial Foraging Algorithm for Optimized Clustering in Wireless Sensor Network

2019 ◽  
Vol 8 (10) ◽  
pp. 2186-2190
Keyword(s):  
Sensor Networks ◽  
Network Lifetime ◽  
Artificial Bee Colony ◽  
Weather Forecasting ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Bacterial Foraging Optimization ◽  
Bacterial Foraging ◽  
Bee Colony ◽  
Bacterial Foraging Algorithm

The emerging ubiquitous nature of wireless sensor networks has made it suitable and applicable to a diversified number of vital applications that include environment surveillance, health monitoring using implantable sensors, weather forecasting and other plethora of contexts. The critical issues such as computation time, limited memory and energy are more common due to the tiny sized hundred and thousands of sensor nodes existing in the networks. In this context, the network lifetime completely depends on the potential use of available resources. The process of organizing closely located sensor nodes into clusters is convenient for effective management of cluster and improving the lifetime of the complete network. At this juncture, swarm intelligent and evolutionary algorithms the pertains to the problem of NP-complete is determined to achieve a superior optimal solution. In this paper, a Hybrid Artificial Bee Colony and Bacterial Foraging Algorithm-based Optimized Clustering (HABC-BFA-OC) is proposed for achieving enhanced network lifetime in sensor networks. In this proposed HABC-BFA-OC technique, the benefits of Bacterial Foraging Optimization is included for improving the local search potential of ABC algorithm in order to attain maximum exploitation and exploration over the parameters considered for cluster head selection. The simulation experiments of the proposed HABC-BFA-OC technique confirmed an enhanced network lifetime with minimized energy consumptions during its investigation with a different number of sensor nodes.

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