Balanced Density-Based Clustering Technique Based on Distributed Spatial Analysis in Wireless Sensor Network

Abdellatief, Walaa; Youness, Osama S.; Abdelkader, Hatem; Hadhoud, Mohiy M.

doi:10.1007/s10776-019-00425-y

Cited by 4 publications

(4 citation statements)

References 29 publications

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“…In addition, the proposed method, considering the use of the density-based clustering method and the transfer of information through the closest distances, compared to other previous methods that are performed by other researchers in this field, in terms of average energy consumption and number of alive nodes on different cycles of information transmission, our proposed method has shown better results in the WSN. Given the importance of clustering in wireless sensor networks for optimal energy routing, future suggestions for the present study include the following: HGTD [6] HEED [6] LEACH [6] 100 round 500 round 1000 round 15 Wireless Communications and Mobile Computing…”

Section: Discussionmentioning

confidence: 99%

“…One of the most important evaluation criteria introduced is the method of average energy consumption and the number of live nodes in information transmission periods in the network. Therefore, the proposed method can be compared with the methods presented in other researches based on these two criteria [6]. Figure 11 shows a comparison of the proposed method with the methods presented in other studies based on the average energy consumption.…”

Section: Comparison Of the Proposed Methods With Previousmentioning

confidence: 99%

“…Abdellatief et al [6] proposed a distributed density-based clustering method called "spatial density-based clustering for WSNs" to reduce power consumption and ultimately increase grid life. This method was performed with the help of a simple initial spatial analysis for the distribution of nodes before the clustering process and divides the network into different regions according to their density level.…”

Section: Related Workmentioning

confidence: 99%

“…After density-based clustering in the network to transmit sensed data, the wireless sensor nodes after processing the data, if data is detected as critical data, sends the hole or node that has the most value based on the selection function in the cluster. The amount of 6 Wireless Communications and Mobile Computing competence in the proposed method is determined based on a combination of three parameters (including the distance of the nodes from each other, the direct distance of the node to the hole, and the remaining energy of the nodes). The node that has the shortest distance to its neighbors in the neighborhood radius and its direct distance to the hole is less than the rest and also has more residual energy will have the highest amount of merit.…”

Section: Proposed Routing In Thismentioning

confidence: 99%

See 3 more Smart Citations

Proposing a Density‐Based Clustering Approach (DBCA) to Aggregate Data Collected from the Environment in Arid Area for Desertification

Peng

Daraei

Ahmadpanahi

et al. 2021

Wireless Communications and Mobile Computing

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Nowadays, the expansion of desert areas has become one of the main problems in arid areas due to various reasons such as rising temperatures and vegetation fires. Establishment of wireless sensor networks in these areas can accelerate the process of environmental monitoring and integrate temperature and humidity information sending to base stations in order to make basic decisions on desertification. The main problem in this regard is the energy limitation of sensor nodes in wireless sensor networks, which is one of the main challenges in using these nodes due to the lack of a fixed power supply. Because the node consumes the most energy during data transmission, the node that transmits the most data or sends the packets over long distances runs out of energy faster than the others and the network work process is disrupted. Therefore, in this study, a density-based clustering approach is proposed to integrate data collected from the environment in arid areas for desertification. In the proposed method at each step, the node that has the most residual energy and is highly centralized will be selected to transfer information. The results of experiments for evaluating the performance of the proposed method show that the proposed method balances the energy consumption of the nodes and optimizes the lifespan of the nodes in the wireless sensor network installed in the arid area.

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Section: Discussionmentioning

confidence: 99%

Section: Comparison Of the Proposed Methods With Previousmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Proposed Routing In Thismentioning

confidence: 99%

See 2 more Smart Citations

Proposing a Density‐Based Clustering Approach (DBCA) to Aggregate Data Collected from the Environment in Arid Area for Desertification

Peng

Daraei

Ahmadpanahi

et al. 2021

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

show abstract

D-Leach: An Energy Optimized Deterministic Sub-clustering and Multi-hop Routing Protocol for Wireless Sensor Networks

Gupta

Amjad

2021

Communications in Computer and Information Science

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Communication MWSN Data Transmission Mechanism Based on a Wireless Sensor Network

2022

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A wireless sensor network (WSN) is considered to have a wide application prospect in a smart distribution network due to its unique low power consumption, fast self-organization, and superior coordination. In order to study the communication MWSN data transmission mechanism based on a wireless sensor network, the difficulty of applying a wireless sensor network to an intelligent distribution network communication is to meet the real-time and reliability requirements of power industry distribution network data communication specifications under the limited network resources. Firstly, the transmission probability is calculated by considering the path loss, the speed of the node, the direction of the node, and the residual energy of the node. In addition, the transmission and replacement order of the message is determined according to the survival time of the data message. Simulation experiments are carried out on MATLAB. The result shows the proposed routing algorithm, compared with the DT algorithm, flooding algorithm, and FAD algorithm, the delivery rate of data messages is increased by at least 6%, and the number of copies is reduced by at least 10% compared with the flooding algorithm and the FAD algorithm. On the basis of satisfying the mobility of sink nodes, the algorithm proposed in this paper can effectively save network energy consumption and prolong the network lifetime.

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Balanced Density-Based Clustering Technique Based on Distributed Spatial Analysis in Wireless Sensor Network

Cited by 4 publications

References 29 publications

Proposing a Density‐Based Clustering Approach (DBCA) to Aggregate Data Collected from the Environment in Arid Area for Desertification

Proposing a Density‐Based Clustering Approach (DBCA) to Aggregate Data Collected from the Environment in Arid Area for Desertification

D-Leach: An Energy Optimized Deterministic Sub-clustering and Multi-hop Routing Protocol for Wireless Sensor Networks

Communication MWSN Data Transmission Mechanism Based on a Wireless Sensor Network

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