A new data aggregation approach for WSNs based on open pits mining

Ramezanifar, Hadi; Ghazvini, Mahdieh; Shojaei, Maryam

doi:10.1007/s11276-020-02442-9

Cited by 15 publications

(7 citation statements)

References 24 publications

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“…In addition, it emphasizes the importance of surpassing the blockage example and clarifies the UED issue. Open mining is proposed in [19] as a strategy for data aggregation that is both efficient and cost-effective. This data mining technique employs several.…”

Section: Ijici Issn: 2791-2868 Rmentioning

confidence: 99%

Increase Efficiency And Lifetime In Wsns Through Data Reduction

Alsawad

2022

IJICI

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The mining and processing of data for wireless sensor networks (WSNs) have been a significant research area in a number of computer science disciplines, including distributed applications, database management systems, and information gathering. The main goal of implementing applications based on WSNs is to make real-time choices, which have proven very difficult due to the limitations of computing, communication, and data mining capacity for WSNs. Thus, due to the nature and unique characteristics of sensor data and the limitations of WSNs, traditional data mining methods cannot be easily applied to them. This paper presents a new approach, the Kalman Filter (KF) with K-Nearest Neighbors (KNN) named (KF-KNN) which is proposed for data classification and collection as well as noise elimination in WSNs, increasing the network efficiency and lifetime. The proposed technique is compared to KNN to illustrate the effectiveness of the recommended ways in increasing energy consumption and prolonging network lifetime.

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Section: Ijici Issn: 2791-2868 Rmentioning

confidence: 99%

Increase Efficiency And Lifetime In Wsns Through Data Reduction

Alsawad

2022

IJICI

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“…As a result, a lot of redundant or raw data products that cause various types of traffic are generated in WSNs such as packet losses, high energy consumption, data representation, data accuracy, data redundancy, network overload, high transmission cost rate, data latency, congestion, data delivery ratio, etc. In recent years, various studies have been proposed to tackle these challenges and issues [86][87][88][89].…”

Section: Time-driven Modelmentioning

confidence: 99%

“…A large-scale WSN includes many sensor nodes and thus faces issues in terms of data analysis and gathering; it has some limitations regarding data redundancy, sensor energy, and network lifetime. Ramezanifar et al [89] propose an open-pit mining data aggregation technique for heterogeneous clustering sensor networks. Heterogeneous sensor data aggregation is difficult as compared to homogeneous data.…”

Section: Time-driven Modelmentioning

confidence: 99%

“…High energy cost has a harmful impact on the sensors lifetime due to redundant data, data congestion, high traffic data, and network overload. For less energy consumption, data aggregation, clustering, data redundancy reduction, and routing protocols are used in WSNs [86][87][88][89]. Previous studies used a combination of time-driven and event-driven (hybrid) models.…”

Section: Hybrid-driven Modelmentioning

confidence: 99%

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Recent Advancement of Data-Driven Models in Wireless Sensor Networks: A Survey

et al. 2021

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Wireless sensor networks (WSNs) are considered producers of large amounts of rich data. Four types of data-driven models that correspond with various applications are identified as WSNs: query-driven, event-driven, time-driven, and hybrid-driven. The aim of the classification of data-driven models is to get real-time applications of specific data. Many challenges occur during data collection. Therefore, the main objective of these data-driven models is to save the WSN’s energy for processing and functioning during the data collection of any application. In this survey article, the recent advancement of data-driven models and application types for WSNs is presented in detail. Each type of WSN is elaborated with the help of its routing protocols, related applications, and issues. Furthermore, each data model is described in detail according to current studies. The open issues of each data model are highlighted with their challenges in order to encourage and give directions for further recommendation.

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“…Additionally, it brings up the point of outdoing the obstruction example and elucidates the Unbalanced Energy Depletion (UED) problem in the network. [19]  Open-Pit Mining  Open mining is presented as a method for aggregating data that is both efficient and cost-effective to use.  This data mining method uses a lot of wsns.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Data Aggregation Approach to Enhance Energy-Efficient Routing Protocol for HWSNs

Alshawi¹,

Alhijaj²,

Khudor³

2022

IJCAI

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The sensor nodes' computing capability, communication capabilities, and power supply are severely constrained in WSNs, making sensor battery replacement or recharging difficult or even impossible. Therefore, energy is an important challenge to consider while creating WSNs. In hazardous circumstances, accurate data aggregation and routing are crucial, and the energy consumption of sensors must be closely controlled. Due to environmental conditions and short-distance sensors, however, there is a high possibility of duplicating data. Large datasets include a range of data, some of which are helpful while others are entirely unnecessary. This redundancy reduces performance in terms of redundant transmission and computation expense. Data aggregation, on the other hand, may reduce duplicate data in a network, hence reducing the volume of data sent and increasing the network's lifespan. In this context, two novel energy-conscious approaches called Fuzzy Data Aggregation with Spider monkey optimization (FDA-SMORP) for data aggregation in the cluster head and routing to the sink are presented. These strategies attempt to offset the energy consumption among all nodes in a wireless network such that these nodes exhaust all of their energy and die almost simultaneously. To demonstrate the efficacy of the suggested approaches in terms of minimizing delay caused by route planning, balancing energy usage, and extending network lifetime, the proposed methods are compared to some of the most well-known WSN systems. Povzetek: Razvit je sistem za nadzorovanje potrošnje energije v senzorskih brezžičnih omrežjih.

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A new data aggregation approach for WSNs based on open pits mining

Cited by 15 publications

References 24 publications

Increase Efficiency And Lifetime In Wsns Through Data Reduction

Increase Efficiency And Lifetime In Wsns Through Data Reduction

Recent Advancement of Data-Driven Models in Wireless Sensor Networks: A Survey

Fuzzy Data Aggregation Approach to Enhance Energy-Efficient Routing Protocol for HWSNs

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