Total energy consumption.
<div><p>In wireless sensor networks (WSNs), power consumption is a recurring issue. Compared to other modern routing approaches that aim to reduce power consumption, cluster-based forwarding algorithms have been shown to be more energy efficient. Static clustering optimization is the mai...
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2025
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| _version_ | 1852019847755464704 |
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| author | Fazia Akhtar (21453122) |
| author2 | Ijaz Ahmed (1545961) Ahmed F. Youssef (21453125) Idris H. Smaili (21453128) Mohamed Mostafa Ramdan Ahmed (21453131) Ali M. El-Rifaie (21453134) |
| author2_role | author author author author author |
| author_facet | Fazia Akhtar (21453122) Ijaz Ahmed (1545961) Ahmed F. Youssef (21453125) Idris H. Smaili (21453128) Mohamed Mostafa Ramdan Ahmed (21453131) Ali M. El-Rifaie (21453134) |
| author_role | author |
| dc.creator.none.fl_str_mv | Fazia Akhtar (21453122) Ijaz Ahmed (1545961) Ahmed F. Youssef (21453125) Idris H. Smaili (21453128) Mohamed Mostafa Ramdan Ahmed (21453131) Ali M. El-Rifaie (21453134) |
| dc.date.none.fl_str_mv | 2025-05-30T17:23:59Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pone.0321938.g011 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/figure/Total_energy_consumption_/29199146 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Evolutionary Biology Ecology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Chemical Sciences not elsewhere classified Information Systems not elsewhere classified wireless sensor networks static clustering optimization outperform existing protocols optimizing static clustering based forwarding algorithms 7 %, 7 34 %, respectively run using matlab network life time central base station lch optimum routing modern routing approaches reduce power consumption higher stability period energy constrained environment 1500 simulation cycles 2 %, 4 data transmission rate leach optimum routing optimum routing power consumption data transmission 14 %, optimal routing survival rate suggest using network endurance modern technique data transfer central cluster xlink "> units took substantial areas stability intervals robust solution recurring issue rectangular region main emphasis leach chose hopping techniques hopping approach findings indicate energy efficient energy efficiency clearly improved |
| dc.title.none.fl_str_mv | Total energy consumption. |
| dc.type.none.fl_str_mv | Image Figure info:eu-repo/semantics/publishedVersion image |
| description | <div><p>In wireless sensor networks (WSNs), power consumption is a recurring issue. Compared to other modern routing approaches that aim to reduce power consumption, cluster-based forwarding algorithms have been shown to be more energy efficient. Static clustering optimization is the main emphasis of this study on energy-efficient advanced zonal rectangular low energy adaptive clustering hierarchy (EE-AZR-LEACH) optimum routing, which takes a modern technique. To extend the lifespan of the cluster units and the system, we suggest using the multi-hopping approach. The proposed protocol significantly improves the network life time and energy efficiency of WSNs by optimizing static clustering and incorporating multi-hopping techniques. It can outperform existing protocols in power consumption, data transfer and stability, makes it a robust solution for large-scale and energy constrained environment. To help the Cluster Heads (CHs) with data transmission, EE-AZR-LEACH chose a Collaborator(CL) close to the central cluster. To increase the effectiveness of communication between the CHs located in the rectangular region and a central base station, these units took on the role of cluster leaders. The resilience, data transmission rate, power consumption, network endurance, and number of CHs of the system were clearly improved as a consequence. Our suggested routing system performs more effectively than AZR-LEACH, LEACH, MH-LEACH, and SEP in substantial areas. Furthermore, the proposed approach exhibits better convergence within 600 rounds when compared to AZR-LEACH, LEACH, MH-LEACH, and SEP. The findings indicate that after 1500 simulation cycles, the stability intervals for LEACH, MH-LEACH, SEP, and AZR-LEACH are 2.7%, 7.2%, 4.14%, and 5.34%, respectively. The simulation is run using MATLAB. The EE-AZR-LCH optimum routing, on the other hand, has a 6.8% survival rate. The MH-LEACH optimum routing has smaller total network tenure even if it provides a higher stability period than the EE-AZR-LEACH.</p></div> |
| eu_rights_str_mv | openAccess |
| id | Manara_dd1fb40e994ae4d7b9ce044b2a95a6b1 |
| identifier_str_mv | 10.1371/journal.pone.0321938.g011 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/29199146 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Total energy consumption.Fazia Akhtar (21453122)Ijaz Ahmed (1545961)Ahmed F. Youssef (21453125)Idris H. Smaili (21453128)Mohamed Mostafa Ramdan Ahmed (21453131)Ali M. El-Rifaie (21453134)Evolutionary BiologyEcologyBiological Sciences not elsewhere classifiedMathematical Sciences not elsewhere classifiedChemical Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedwireless sensor networksstatic clustering optimizationoutperform existing protocolsoptimizing static clusteringbased forwarding algorithms7 %, 734 %, respectivelyrun using matlabnetwork life timecentral base stationlch optimum routingmodern routing approachesreduce power consumptionhigher stability periodenergy constrained environment1500 simulation cycles2 %, 4data transmission rateleach optimum routingoptimum routingpower consumptiondata transmission14 %,optimal routingsurvival ratesuggest usingnetwork endurancemodern techniquedata transfercentral clusterxlink ">units tooksubstantial areasstability intervalsrobust solutionrecurring issuerectangular regionmain emphasisleach chosehopping techniqueshopping approachfindings indicateenergy efficientenergy efficiencyclearly improved<div><p>In wireless sensor networks (WSNs), power consumption is a recurring issue. Compared to other modern routing approaches that aim to reduce power consumption, cluster-based forwarding algorithms have been shown to be more energy efficient. Static clustering optimization is the main emphasis of this study on energy-efficient advanced zonal rectangular low energy adaptive clustering hierarchy (EE-AZR-LEACH) optimum routing, which takes a modern technique. To extend the lifespan of the cluster units and the system, we suggest using the multi-hopping approach. The proposed protocol significantly improves the network life time and energy efficiency of WSNs by optimizing static clustering and incorporating multi-hopping techniques. It can outperform existing protocols in power consumption, data transfer and stability, makes it a robust solution for large-scale and energy constrained environment. To help the Cluster Heads (CHs) with data transmission, EE-AZR-LEACH chose a Collaborator(CL) close to the central cluster. To increase the effectiveness of communication between the CHs located in the rectangular region and a central base station, these units took on the role of cluster leaders. The resilience, data transmission rate, power consumption, network endurance, and number of CHs of the system were clearly improved as a consequence. Our suggested routing system performs more effectively than AZR-LEACH, LEACH, MH-LEACH, and SEP in substantial areas. Furthermore, the proposed approach exhibits better convergence within 600 rounds when compared to AZR-LEACH, LEACH, MH-LEACH, and SEP. The findings indicate that after 1500 simulation cycles, the stability intervals for LEACH, MH-LEACH, SEP, and AZR-LEACH are 2.7%, 7.2%, 4.14%, and 5.34%, respectively. The simulation is run using MATLAB. The EE-AZR-LCH optimum routing, on the other hand, has a 6.8% survival rate. The MH-LEACH optimum routing has smaller total network tenure even if it provides a higher stability period than the EE-AZR-LEACH.</p></div>2025-05-30T17:23:59ZImageFigureinfo:eu-repo/semantics/publishedVersionimage10.1371/journal.pone.0321938.g011https://figshare.com/articles/figure/Total_energy_consumption_/29199146CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/291991462025-05-30T17:23:59Z |
| spellingShingle | Total energy consumption. Fazia Akhtar (21453122) Evolutionary Biology Ecology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Chemical Sciences not elsewhere classified Information Systems not elsewhere classified wireless sensor networks static clustering optimization outperform existing protocols optimizing static clustering based forwarding algorithms 7 %, 7 34 %, respectively run using matlab network life time central base station lch optimum routing modern routing approaches reduce power consumption higher stability period energy constrained environment 1500 simulation cycles 2 %, 4 data transmission rate leach optimum routing optimum routing power consumption data transmission 14 %, optimal routing survival rate suggest using network endurance modern technique data transfer central cluster xlink "> units took substantial areas stability intervals robust solution recurring issue rectangular region main emphasis leach chose hopping techniques hopping approach findings indicate energy efficient energy efficiency clearly improved |
| status_str | publishedVersion |
| title | Total energy consumption. |
| title_full | Total energy consumption. |
| title_fullStr | Total energy consumption. |
| title_full_unstemmed | Total energy consumption. |
| title_short | Total energy consumption. |
| title_sort | Total energy consumption. |
| topic | Evolutionary Biology Ecology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Chemical Sciences not elsewhere classified Information Systems not elsewhere classified wireless sensor networks static clustering optimization outperform existing protocols optimizing static clustering based forwarding algorithms 7 %, 7 34 %, respectively run using matlab network life time central base station lch optimum routing modern routing approaches reduce power consumption higher stability period energy constrained environment 1500 simulation cycles 2 %, 4 data transmission rate leach optimum routing optimum routing power consumption data transmission 14 %, optimal routing survival rate suggest using network endurance modern technique data transfer central cluster xlink "> units took substantial areas stability intervals robust solution recurring issue rectangular region main emphasis leach chose hopping techniques hopping approach findings indicate energy efficient energy efficiency clearly improved |