A Clustering WSN Routing Protocol Based on k-d Tree Algorithm

Anzola, John; Pascual, Jordan; Bermúdez, Giovanny Mauricio Tarazona; Crespo, Rubén González

doi:10.3390/s18092899

Cited by 46 publications

(17 citation statements)

References 52 publications

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“…The k-d tree creates a two-hop hierarchical network, based on which the corresponding tree is constructed according to the position of each node to transfer data to the base station. The results show an improvement in network latency and performance [12].…”

Section: Introductionmentioning

confidence: 84%

An improved cluster formation process in wireless sensor network to decrease energy consumption

et al. 2020

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Wireless sensor network has special features and many applications, which have attracted attention of many scientists. High energy consumption of these networks, as a drawback, can be reduced by a hierarchical routing algorithm. The proposed algorithm is based on the Low Energy Adaptive Clustering Hierarchy (LEACH) and Quadrant Cluster based LEACH (Q-LEACH) protocols. To reduce energy consumption and provide a more appropriate coverage, the network was divided into several regions and clusters were formed within each region. In selecting the cluster head (CH) in each round, the amount of residual energy and the distance from the center of each node were calculated by the base station (including the location and residual energy of each node) for all living nodes in each region. In this regard, the node with the largest value had the highest priority to be selected as the CH in each network region. The base station calculates the CH due to the lack of energy constraints and is also responsible for informing it throughout the network, which reduces the load consumption and tasks of nodes in the network. The information transfer steps in this protocol are similar to the LEACH protocol stages. To better evaluate the results, the proposed method was implemented with LEACH LEACH-SWDN, and Q-LEACH protocols using MATLAB software. The results showed better performance of the proposed method in network lifetime, first node death time, and the last node death time.

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Section: Introductionmentioning

confidence: 84%

An improved cluster formation process in wireless sensor network to decrease energy consumption

et al. 2020

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“…The network lifetime of WPO‐EECRP is 1.4 greater than the existing IACO‐PEGASIS and ICFSFDP schemes. Finally, a kd‐tree algorithm is proposed based on the merits of hierarchical routing structures for effective organization of sensor nodes into clusters by taking a kd‐tree‐based reactive data structure into account 20 . This kd‐tree algorithm involves a dynamic CH selection approach that incorporates the benefits of hierarchy for enforcing low preservation in the network.…”

Section: Related Workmentioning

confidence: 99%

An Energy‐Proficient Clustering‐Inspired Routing Protocol using Improved Bkd‐tree for Enhanced Node Stability and Network Lifetime in Wireless Sensor Networks

Janakiraman¹,

Priya

2020

Int J Communication

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Energy conservation in Wireless Sensor Networks (WSNs) is essential for improving the stability of sensor nodes and network lifetime. An energyproficient clustering-based routing protocol is necessary for efficient cluster formation and Cluster Head (CH) selection to sustain Quality of Service (QoS). In this paper, an Improved Bkd-Tree-Inspired Energy-eFficient Clusteringbased Routing Protocol (IBkd-Tree-IEFCRP) is propounded as a potential strategy for guaranteeing significant cluster formation and management. It is proposed as an effective strategy in CH node allocation that handles the impacts of QoS during the process of data dissemination. This IBkd-Tree-IEFCRP is proposed to deal with energy saving with respect to data traffic by including a strategy of cluster formation which incorporates the benefits of partition data structure that incorporates animprovedBkd-treealgorithm.Italsoconcentrates ontheprocessofCHselection by integrating a reactive approach that enhances throughput with minimized energy, delay and jitter. The simulation experiments of the proposed IBkd-Tree-IEFCRP confirm a better performance in improving the average throughput by 13.21%, reducing the energy consumptions by 12.96%, minimizing the delay by 11.98% and reducing the jitter by 14.24% when compared to the baseline kdimensional tree algorithm (kd-tree algorithm), Weighting and Parameter Optimization-based Energy-Efficient Clustering Routing Protocol (WPO-EECRP), Improved Clustering by Fast Search and Finding of Density Peaks (ICFSFDP), and Energy-based Cluster Centered Routing Protocol (ECCRP) taken for comparison. The proposed IBkd-Tree-IEFCRP is also identified to reduce delay by 8.42% and jitter by 7.18% and increase throughput by 6.84% when compared to the benchmarked protocols for different number of rounds.

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“…The first node death (FND) is the number of rounds in the network until the first node has depleted its energy and died. 48 In WSNs, performance tends to decline with the nodes' death. Normally, the network is in a stable period before the first node dies.…”

Section: Parameter Setting For Simulation Of Networkmentioning

confidence: 99%

Intelligent energy optimization for advanced IoT analytics edge computing on wireless sensor networks

Agbehadji

Frimpong

Millham

et al. 2020

International Journal of Distributed Sensor Networks

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The current dispensation of big data analytics requires innovative ways of data capturing and transmission. One of the innovative approaches is the use of a sensor device. However, the challenge with a sensor network is how to balance the energy load of wireless sensor networks, which can be achieved by selecting sensor nodes with an adequate amount of energy from a cluster. The clustering technique is one of the approaches to solve this challenge because it optimizes energy in order to increase the lifetime of the sensor network. In this article, a novel bio-inspired clustering algorithm was proposed for a heterogeneous energy environment. The proposed algorithm (referred to as DEEC-KSA) was integrated with a distributed energy-efficient clustering algorithm to ensure efficient energy optimization and was evaluated through simulation and compared with benchmarked clustering algorithms. During the simulation, the dynamic nature of the proposed DEEC-KSA was observed using different parameters, which were expressed in percentages as 0.1%, 4.5%, 11.3%, and 34% while the percentage of the parameter for comparative algorithms was 10%. The simulation result showed that the performance of DEEC-KSA is efficient among the comparative clustering algorithms for energy optimization in terms of stability period, network lifetime, and network throughput. In addition, the proposed DEEC-KSA has the optimal time (in seconds) to send a higher number of packets to the base station successfully. The advantage of the proposed bio-inspired technique is that it utilizes random encircling and half-life period to quickly adapt to different rounds of iteration and jumps out of any local optimum that might not lead to an ideal cluster formation and better network performance.

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A Clustering WSN Routing Protocol Based on k-d Tree Algorithm

Cited by 46 publications

References 52 publications

An improved cluster formation process in wireless sensor network to decrease energy consumption

An improved cluster formation process in wireless sensor network to decrease energy consumption

An Energy‐Proficient Clustering‐Inspired Routing Protocol using Improved Bkd‐tree for Enhanced Node Stability and Network Lifetime in Wireless Sensor Networks

Intelligent energy optimization for advanced IoT analytics edge computing on wireless sensor networks

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