Adaptive energy-efficient clustering path planning routing protocols for heterogeneous wireless sensor networks

Aslam, Muhammad; Munir, Ehsan Ullah; Rafique, M. Mustafa; Hu, Xiaopeng

doi:10.1016/j.suscom.2016.09.001

Cited by 35 publications

(34 citation statements)

References 21 publications

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“…If it is also assumed to be ( ) = V , then the sum of all possible states of is 1. This case is also true for (11).…”

Section: Deec Modelmentioning

confidence: 59%

“…For this purpose, an LEACH variant combined with HEED and LEACH protocol is proposed and this method is approved by simulation. In [11], two energy efficient route planning routing protocols are proposed for three levels of heterogeneous WSNs, namely, Central Energy Efficiency Clustering (CEEC) with Two-Hop Heterogeneity awareness (THCEEC) and Advanced Equalization (ACEEC). Comprehensive simulation results have provided CEEC, ACEEC, and THCEEC central cluster deployments with improved reliability and energy efficiency performance, providing better network lifetime and successful data transmission than LEEC, SEP, ESEP, and DEEC's traditional distributed routing protocols.…”

Section: Related Workmentioning

confidence: 99%

“…Heterogeneous WSNs consist of two, three, or multiple types sensor nodes in terms of energy levels, hardware structure, and other special properties [20]. The DEEC protocol is based on a two-level heterogeneous WSN in which the sensor nodes are assumed to have normal and advanced battery levels [11]. However, multilevel heterogeneity can be considered for DEEC.…”

Section: Deec Modelmentioning

confidence: 99%

“…Since is the number of nodes in the network, the numbers of normal, advanced, and super nodes in the network are , V , and , respectively. Thus, the total first energy of the three-level heterogeneous WSNs is calculated as given in Also, the proposed probabilities for the CH selection for the EDEEC model are given in (11).…”

Section: Edeec Modelmentioning

confidence: 99%

See 3 more Smart Citations

Threshold Balanced Sampled DEEC Model for Heterogeneous Wireless Sensor Networks

Vançin

Erdem

2018

Wireless Communications and Mobile Computing

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Due to the restricted hardware resources of the sensor nodes, modelling and designing energy efficient routing methods to increase the overall network lifetime have become one of the most significant strategies in wireless sensor networks (WSNs). Cluster-based heterogeneous routing protocols, a popular part of routing technology, have proven effective in management of topology, energy consumption, data collection or fusion, reliability, or stability in a distributed sensor network. In this article, an energy efficient three-level heterogeneous clustering method (DEEC) based distributed energy efficient clustering protocol named TBSDEEC (Threshold balanced sampled DEEC) is proposed. Contrary to most other studies, this study considers the effect of the threshold balanced sampled in the energy consumption model. Our model is compared with the DEEC, EDEEC (Enhanced Distributed Energy Efficient Clustering Protocol), and EDDEEC (Enhanced Developed Distributed Energy Efficient Clustering Protocol) using MATLAB as two different scenarios based on quality metrics, including living nodes on the network, network efficiency, energy consumption, number of packets received by base station (BS), and average latency. After, our new method is compared with artificial bee colony optimization (ABCO) algorithm and energy harvesting WSN (EH-WSN) clustering method. Simulation results demonstrate that the proposed model is more efficient than the other protocols and significantly increases the sensor network lifetime.

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“…If it is also assumed to be ( ) = V , then the sum of all possible states of is 1. This case is also true for (11).…”

Section: Deec Modelmentioning

confidence: 59%

Section: Related Workmentioning

confidence: 99%

Section: Deec Modelmentioning

confidence: 99%

Section: Edeec Modelmentioning

confidence: 99%

See 2 more Smart Citations

Threshold Balanced Sampled DEEC Model for Heterogeneous Wireless Sensor Networks

Vançin

Erdem

2018

Wireless Communications and Mobile Computing

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show abstract

“…Hao Zhang,Wei Liu, et al [30][31][32] proposed and proved that flip ambiguity detection for three-dimensional node localization is equivalent to the intersecting plane that intersects with all range error spheres of the reference nodes of unknown node in the ideal radio model, which is called the existence of intersecting plane (EIP) problem. They proposed common tangent plane algorithm (CTP) and orthogonal projection algorithm (OP).…”

Section: Background and Researchmentioning

confidence: 99%

Wireless Sensor Network Dynamic Mathematics Modeling and Node Localization

Liu

2018

Wireless Communications and Mobile Computing

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With the rapid development of wireless sensor network (WSN) technology and its localization method, localization is one of the basic services for data collection in WSN. The localization accuracy often depends on the accuracy of distance estimation. Because of the constraint in size, power, and cost of sensor nodes, the investigation of efficient location algorithms which satisfy the basic accuracy requirement for WSN meets new challenges. This paper proposes a novel intelligent node localization algorithm in WSN based on beacon nodes to improve the precision in location estimation. Firstly, system model of WSN node localization is constructed according to the WSN environment. Then traditional WSN node localization methods such as DV-HOP, GA, and PSO are studied. Localization algorithm of WSN is proposed by using dynamic mathematics modeling. And the result of simulation, which is compared to the traditional algorithm, indicated that this algorithm is better to improve the accuracy and coverage of WSN. The simulation results show that the performance of the proposed WSN location algorithm is better than the traditional localization algorithms.

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Application of Computer Vision Technology Based on Neural Network in Path Planning

Wen

Chen

Jiang

et al. 2023

Lecture Notes on Data Engineering and Communications Technologies

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Adaptive energy-efficient clustering path planning routing protocols for heterogeneous wireless sensor networks

Cited by 35 publications

References 21 publications

Threshold Balanced Sampled DEEC Model for Heterogeneous Wireless Sensor Networks

Threshold Balanced Sampled DEEC Model for Heterogeneous Wireless Sensor Networks

Wireless Sensor Network Dynamic Mathematics Modeling and Node Localization

Application of Computer Vision Technology Based on Neural Network in Path Planning

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