Data aggregation techniques in wireless sensors networks (WSNs): Taxonomy and an accurate literature survey

Abdalkafor, Ahmed Subhi; Aliesawi, Salah A.

doi:10.1063/5.0112212

Cited by 9 publications

(4 citation statements)

References 65 publications

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“…Therefore, data redundancy, reduction of energy consumption, security problems, and routing security are the major issues caused by WSNs. Some of the major security requirements in WSN are information gathering, version of a node, false malfunction, and message corruption 21 . At the same time, the minor security requirements in WSN are data freshness, self‐organization, time synchronization, and secure localization 22 .…”

Section: Related Workmentioning

confidence: 99%

“…Some of the major security requirements in WSN are information gathering, version of a node, false malfunction, and message corruption. 21 At the same time, the minor security requirements in WSN are data freshness, self-organization, time synchronization, and secure localization. 22 Many mechanisms and methods have been invented to improve the trustworthiness of routing nodes, such as cryptographic systems, trust management, and centralized routing decisions.…”

Section: Problem Statementmentioning

confidence: 99%

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An improved blockchain based encryption scheme for secure routing in wireless sensor network using machine learning technique

Meena

Sharma

2022

Trans Emerging Tel Tech

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A secure routing scheme plays an integral role in ensuring the secure routing and efficiency of wireless sensor networks (WSNs). Recently, many studies have been undertaken to improve the data aggregation process, data security, and routing security. However, these approaches are highly suffered due to major limitations like time complexity, malicious attacks, and data insecurity. This research aims to develop an improved blockchain based encryption scheme for secure routing in wireless sensor networks using machine learning techniques. An improved artificial quantum beetle swarm neural network approach is proposed to perform the data aggregation among the sensor nodes. The cosine equivalent function and packet density correlation degree approach is emphasized to perform clustering in sensor nodes. The cluster head (CH) is selected based on the similarity of each sensor node. The Kalman filtering technique is introduced to filter out the data from unwanted malicious. This technique helps to filter the data before it is sent to the CH. Blockchain‐based encryption scheme is emphasized for data security by preventing malicious attacks during data transmission. The enhanced differential evaluation based firefly routing protocol is presented to maintain secure routing by choosing the optimal routing for the protected data transmission. Performance metrics such as latency, throughput, routing performance, energy consumption, FPR, blockchain (BC) computational performance, dead sensor count and average hop count are analyzed and compared with existing techniques. In an experimental scenario, the proposed approach achieves a maximum packet delay of 500 slots, throughput of 581 times/s, a latency of 0.31 ms, a computation complexity of 0.6, and a routing complexity of 2081 ms with a BC computation time of 95 ms. The performance of the proposed approach shows a better result than other existing approaches.

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Section: Related Workmentioning

confidence: 99%

Section: Problem Statementmentioning

confidence: 99%

An improved blockchain based encryption scheme for secure routing in wireless sensor network using machine learning technique

Meena

Sharma

2022

Trans Emerging Tel Tech

View full text Add to dashboard Cite

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“…There are studies that focus on energy management at the node level through optimized operations of the node [ 20 ]. There are also approaches based on the optimization of information transfers, for example, by optimizing communication protocols [ 21 , 22 ], by compressing information [ 23 ], or by data aggregation [ 24 ]. Some solutions also propose embedding intelligence in the nodes where the knowledge is derived from a model [ 25 ] or learned via deep learning technologies [ 26 ].…”

Section: Introductionmentioning

confidence: 99%

ConnecSenS, a Versatile IoT Platform for Environment Monitoring: Bring Water to Cloud

Moiroux-Arvis

Royer

Sarramia

et al. 2023

Sensors

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Climate change is having an increasingly rapid impact on ecosystems and particularly on the issue of water resources. The Internet of Things and communication technologies have now reached a level of maturity that allows sensors to be deployed more easily on sites to monitor them. The communicating node based on LoRaWAN technology presented in this article is open and allows the interfacing of numerous sensors for designing long-term environmental monitoring systems of isolated sites. The data integration in the cloud is ensured by a workflow driving the storage and indexing of data, allowing a simple and efficient use of the data for different users (scientists, administration, citizens) through specific dashboards and extractions. This article presents this infrastructure through environmental monitoring use cases related to water resources.

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“…In addition, an uncompleted description of the network architecture is also presented and a slight comparative study of the cluster-based routing protocol is also performed. Abdalkafor et al focused on a description of wireless sensor networks and their general structure with the main components of sensors [25]. Although different types of data aggregation techniques were reviewed, followed by a brief discussion of their role in wireless sensor networks, it was overall an incomplete review that left the researcher with many questions about the intricacies of the topic, especially structured data aggregation techniques.…”

mentioning

confidence: 99%

Data collection in IoT networks: Architecture, solutions, protocols and challenges

Abba Ari,

Aziz,

Njoya

et al. 2024

IET Wireless Sensor Systems

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The Internet of Things (IoT) is the recent technology intended to facilitate the daily life of humans by providing the power to connect, control and automate objects in the physical world. In this logic, the IoT helps to improve our way of producing and working in various areas (e.g. agriculture, industry, healthcare, transportation etc). Basically, an IoT network comprises physical devices, equipped with sensors and transmitters, that are interconnected with each other and/or connected to the Internet. Its main objective is to gather and transmit data to a storage system such as a server or cloud to enable processing and analysis, ultimately facilitating rapid decision‐making or enhancements to the user experience. In the realm of Connected Objects, an effective IoT data collection system plays a vital role by providing several benefits, such as real‐time data monitoring, enhanced decision‐making, increased operational efficiency etc. However, because of the resource limitations linked to connected objects, such as low memory and battery, or even single‐use devices etc. IoT data collecting presents several challenges including scalability, security, interoperability, flexibility etc. for both researchers and companies. The authors categorise current IoT data collection techniques and perform a comparative evaluation of these methods based on the topics analysed and elaborated by the authors. In addition, a comprehensive analysis of recent advances in IoT data collection is provided, highlighting different data types and sources, transmission protocols from connected sensors to a storage platform (server or cloud), the IoT data collection framework, and principles for streamlining the collection process. Finally, the most important research questions and future prospects for the effective collection of IoT data are summarised.

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Data aggregation techniques in wireless sensors networks (WSNs): Taxonomy and an accurate literature survey

Cited by 9 publications

References 65 publications

An improved blockchain based encryption scheme for secure routing in wireless sensor network using machine learning technique

An improved blockchain based encryption scheme for secure routing in wireless sensor network using machine learning technique

ConnecSenS, a Versatile IoT Platform for Environment Monitoring: Bring Water to Cloud

Data collection in IoT networks: Architecture, solutions, protocols and challenges

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