Real time flood disaster monitoring based on energy efficient ensemble clustering mechanism in wireless sensor network

Wilson, Allan J; Radhamani, A. S.

doi:10.1002/spe.3019

Cited by 12 publications

(8 citation statements)

References 52 publications

(53 reference statements)

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“…The connected nodes are first removed from REM[ ] and then added to PAR[ ] to act as parent nodes for the next layer of nodes. While there are nodes present in PAR[ ] or REM[ ], the closest "m" nodes from REM[ ] will be attached to PAR [1]. These "m" nodes will then be removed from REM[ ], and the parent will be removed from PAR[ ] (steps 5-10).…”

Section: F I G U R Ementioning

confidence: 99%

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HSCR: Hierarchical structured cluster routing protocol for load balanced wireless sensor networks

Pal

2022

Softw Pract Exp

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The robustness of wireless sensor networks (WSNs) has made it a preferred choice for many applications. WSNs should perform the intended sensing task with a limited amount of energy. Clustering methodology is used to reduce sensor nodes' energy consumption and increase the network lifetime by organizing nodes into independent groups. In this article, a hierarchical structured cluster routing (HSCR) protocol based on the principle of an m‐way balanced tree has been proposed for multi‐hop intra‐cluster communication and offload the cluster head. It enhances the network performance by providing an underlying architecture that reduces the intra‐cluster communication distance and the amount of data sent to the cluster head. In the proposed HSCR protocol, an m‐way tree‐based hierarchical structure has been proposed in which balanced structure is formed within each cluster so that data aggregation is performed at each intermediate parent node. The proposed approach can be implemented over any communication protocol used in WSNs. Simulation results prove that the proposed algorithms outperform traditional clustering algorithms, LEACH and CT‐RPL, in terms of network stability, energy consumption, and network lifetime. Simulation results affirm that the proposed algorithms outperform traditional clustering algorithms, LEACH and CT‐RPL, in terms of network stability, energy consumption, average intra‐cluster communication distance and network lifetime by 105.32%, 49.23%, 14.98%, 109.31%, and 35.75%, 15.32%, 17%, 24.31%, respectively.

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Section: F I G U R Ementioning

confidence: 99%

“…If the BUFF[ ] is not empty, then preference will be given to the nodes in BUFF[ ] and they will be connected before other nodes. The nodes in BUFF[ ] will be connected to the closest parent nodes, PAR [1] to PAR[P]. 1 to P is the number of parent nodes at a certain layer where the index starts from 1.…”

Section: Number Of Mns Levelsmentioning

confidence: 99%

HSCR: Hierarchical structured cluster routing protocol for load balanced wireless sensor networks

Pal

2022

Softw Pract Exp

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“…Natural disaster monitoring [21], [33], [14] is a very important use case for WSNs. Active volcanoes typically occur when broken slabs of the Earth's outer shell, which is the small sphere, collide.…”

Section: Natural Disaster Monitoringmentioning

confidence: 99%

Wireless Sensor Network Applications

Koffka¹

2022

IJFMR

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In this paper we explore some important applications of wireless sensor networks (WSNs). There are 8 Sections. In Section 2 we discuss structural monitoring. We present how WSNs are used in traffic control in Section 3. Section 4 shows the use of WSNs in the field of telemedicine. Pipeline monitoring with WSNs are illustrated in Section 5 and WSN precision agriculture in Section 6. In Section 7 WSNs usage in natural disaster monitoring is explored. Finally, the conclusion is given in Section 8.

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“…Typically, reconfiguration is performed at the level of the CH, which does not affect the other SNs in the cluster. In summary, clustering can achieve several objectives, such as improved scalability, uniform network energy, efficient resource use, and enhanced QoS [3], [4]. These clustering algorithms for WSNs executed on data streams are divided into two main steps: the clustering and data transmission phases.…”

Section: Introductionmentioning

confidence: 99%

Enhanced Network QoS in Large Scale and High Sensor Node Density Wireless Sensor Networks Using (IR-DV-Hop) Localization Algorithm and Mobile Data Collector (MDC)

Gantassi,

Messous,

Masood

et al. 2024

IEEE Access

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This paper poses new challenges, especially when designing routing protocols to improve the quality of service (QoS) criteria and the lifetime of large-scale wireless sensor networks (LS-WSNs) and high sensor node density WSNs (HSND-WSN). Some of these challenging problems for routing protocols are minimizing the distance between a base station (BS) and the cluster head (CH), latency in the transmission phase, power consumption in the clustering phase, and determining the precise SN location without error. Thus, for a dynamic WSN, it is important to support an intelligent mobile data collector (MDC) to continue data propagation despite the inevitable changes in the WSN topology. Considering these challenges, we propose a novel intelligent routing protocol based on the improved recursive distance vector-hop (IR-DV-Hop) localization algorithm to determine the accurate location of SNs without errors in LS-WSNs and determine the CHs and optimal route traversed by the MDC for energy efficiency, latency, and reliability. Specifically, the proposed mobile data collector-improved recursive distance vectorhop (MDC-IR-DV-Hop) protocol uses the MDC as an intermediate between the CH and BS to enhance the QoS of WSNs, reduce delays while collecting data, and improve the transmission phase of the routing protocol. Simulation results prove the performance of the proposed protocol compared with the energy aware cluster based multi-hop (EACBM), tree clustering algorithm with mobile data collector (TCMDC), mobile data collector maximum residual energy low energy adaptive clustering hierarchy (MDC maximum residual energy leach), MDC minimum distance leach, mobile data collector-K-means (MDC-K), mobile data collector-traveling salesman problem-low energy adaptive clustering hierarchy-K-means (MDC-TSP-LEACH-K), a three-layer hierarchical architecture for optimized routing protocol based on clustering and the Khalimsky topology for mobile WSN (AMWSN), and node density-based clustering and mobile collection (NDCM) protocols. In addition, this article proposes a comparative analysis of the best clustering, CH election, localization and MDC by discussing and describing their functionalities, advantages, disadvantages and their main performance parameters.INDEX TERMS High sensor-node density wireless sensor network (HSND-WSN), improved recursive distance vector-hop (IR-DV-Hop), large-scale wireless sensor network (LS-WSN), mobile data collector (MDC), quality of service (QoS), routing protocol.

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Real time flood disaster monitoring based on energy efficient ensemble clustering mechanism in wireless sensor network

Cited by 12 publications

References 52 publications

HSCR: Hierarchical structured cluster routing protocol for load balanced wireless sensor networks

HSCR: Hierarchical structured cluster routing protocol for load balanced wireless sensor networks

Wireless Sensor Network Applications

Enhanced Network QoS in Large Scale and High Sensor Node Density Wireless Sensor Networks Using (IR-DV-Hop) Localization Algorithm and Mobile Data Collector (MDC)

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