Reducing Energy Consumption in Wireless Sensor Networks Using a Routing Protocol Based on Multi-level Clustering and Genetic Algorithm

Rezaeipanah, Amin; Nazari, Hamed; Abdollahi, MohammadJavad

doi:10.5815/ijwmt.2020.03.01

Cited by 13 publications

(6 citation statements)

References 18 publications

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“…Considering that binary coding cannot directly reflect the individual structure, and the binary length is long, accounting for large memory, the positioning algorithm in this article is code type genetic algorithm, because of the real number encoding, easy operation, and transformation (4) Genetic positioning operator design genetic operator mainly includes selection, crossing, and variation operations. The selection operation adopts the 3 Wireless Communications and Mobile Computing adaptive gambling selection method; the crossadopted multipoint intersection, that is, the X-axis parameters and the Y-axis parameters, corresponds to cross; the variation operation selects the discrete single-point variant mode (5) Genetic positioning algorithm termination determination when the number of iterations reaches a predetermined number, or when the maturity of the group satisfies certain conditions, the iteration is stopped [16][17][18]…”

Section: ) Constraint Conditions For Positioning Optimization Modelsmentioning

confidence: 99%

[Retracted] Research on Wireless Sensor Network Positioning Based on Genetic Algorithm

Zhang

2021

Wireless Communications and Mobile Computing

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For smart city wireless sensing network construction needs, a network positioning algorithm based on genetic algorithm is proposed. The genetic algorithm uses a real number encoding, and the positioning model is constructed by analyzing the communication constraint between unknown nodes and a small amount of anchor nodes and constructs the positioning model, and the model is solved. The results show that when the ranging error is 50%, the positioning error is only increased by approximately 15% compared to the nonranging error. In a more harsh environment, if the ranging error is equal to the node wireless range, the ranging error is 100%, and the positioning error and the positioning ratio are not significantly changed. The scheme obtained by this algorithm can be well approarded with an ideal limit. In the case where the sensor node is given, the algorithm can obtain the maximum coverage.

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Section: ) Constraint Conditions For Positioning Optimization Modelsmentioning

confidence: 99%

[Retracted] Research on Wireless Sensor Network Positioning Based on Genetic Algorithm

Zhang

2021

Wireless Communications and Mobile Computing

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“…A greater number of anchor nodes may improve the location estimation's accuracy [16] . For more information see [18][19][20][21] .…”

Section: Classification Of Localization Techniques In Wsnsmentioning

confidence: 99%

“…The implement of The target and anchors are randomly deployed inside a box with an edge length B = 15 m for each Monte Carlo run (Mc) in [5] . To increase the lifespan of these kinds of networks, in [19] . Rezaeipanah, A., H. Nazari, and M. Abdollahi a multi-level genetic-based clustering approach suggested.…”

Section: _ Geographic Areamentioning

confidence: 99%

Localization in WSN based on Area of field and mobility : A Survey

Ayed¹

2023

Jour. Kufa Math. Comp.

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Abstract— Localization in Wireless Sensor Networks (WSNs) is process to determine the locations of sensors connected within a network. Several applications need to determine the location of sensor nodes in the network to help increasing network performance. Some applications, such as item tracking, military operations, routing protocols, robotics, and inventory management, are made feasible by sensor network’s ability to accurately locate the sensor nodes. For each of these applications, different criteria for position estimation. These are speed, accuracy, and reliability. In this paper we going to classify the localization algorithms with a new perspective based on three criteria (area of fields, cooperation between nodes and node’s mobility). Following along this paper may give’s an idea to the researchers to develop efficient algorithms to localize nodes with accuracy adapting to different techniques with respect to the geographic area and anchor type to be designed

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“…Third parties' big data transfer problem is intermediate attacks and data protection, confidentiality, authentication, and credibility issues [16]. Data security in the distributed cluster head is significant when exchanging data [17].…”

Section: Overview Of Managing Data Security Using Keyed-hash Message Authentication Code-based Encryption Algorithmmentioning

confidence: 99%

Code-based encryption techniques with distributed cluster head and energy consumption routing protocol

Jalasri

Lakshmanan

2021

Complex Intell. Syst.

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Fog computing and the Internet of Things (IoT) played a crucial role in storing data in the third-party server. Fog computing provides various resources to collect data by managing data security. However, intermediate attacks and data sharing create enormous security challenges like data privacy, confidentiality, authentication, and integrity issues. Various researchers introduce several cryptographic techniques; security is still significant while sharing data in the distributed environment. Therefore, in this paper, Code-Based Encryption with the Energy Consumption Routing Protocol (CBE-ECR) has been proposed for managing data security and data transmission protocols using keyed-hash message authentication. Initially, the data have been analyzed, and the distributed cluster head is selected, and the stochastically distributed energy clustering protocol is utilized for making the data transmission. Code-driven cryptography relies on the severity of code theory issues such as disorder demodulation and vibration required to learn equivalence. These crypto-systems are based on error codes to build a single-way function. The encryption technique minimizes intermediate attacks, and the data have protected all means of transmission. In addition to data security management, the introduced CBE-ECR reduces unauthorized access and manages the network lifetime successfully, leading to the effective data management of 96.17% and less energy consumption of 21.11% than other popular methods.The effectiveness of the system is compared to the traditional clustering techniques.

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Reducing Energy Consumption in Wireless Sensor Networks Using a Routing Protocol Based on Multi-level Clustering and Genetic Algorithm

Cited by 13 publications

References 18 publications

[Retracted] Research on Wireless Sensor Network Positioning Based on Genetic Algorithm

[Retracted] Research on Wireless Sensor Network Positioning Based on Genetic Algorithm

Localization in WSN based on Area of field and mobility : A Survey

Code-based encryption techniques with distributed cluster head and energy consumption routing protocol

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