Hybrid algorithm for fault node recovery and energy efficiency in wireless sensor networks
The Wireless Sensor Networks (WSNs) are designed for the monitoring of remote areas in various places with a variety of different applications. The main challenges with the WSN are energy efficiency and fault recovery. In order to optimize the network lifetime of the WSN, fault node recovery and ene...
Gespeichert in:
| Veröffentlicht in: | Journal of information & optimization sciences Jg. 45; H. 8; S. 2347 - 2367 |
|---|---|
| Hauptverfasser: | , , , , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
2024
|
| ISSN: | 0252-2667, 2169-0103 |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| Abstract | The Wireless Sensor Networks (WSNs) are designed for the monitoring of remote areas in various places with a variety of different applications. The main challenges with the WSN are energy efficiency and fault recovery. In order to optimize the network lifetime of the WSN, fault node recovery and energy efficient clustering are required in order to efficiently utilize the energy supply device of battery-powered sensors. The purpose of this paper is to develop a hybrid algorithm that combines the K-means clustering technique with fault node recovery in the WSN in order to reduce energy consumption and extend sensor lifetimes. A hybrid algorithm combine’s fault node recovery with energy-efficient clustering methods in order to reduce energy usage. We are using Grade Diffusion (GD) with Genetic Algorithm (GA) to detect fault nodes. In complex or large WSNs, K-means clustering can be used to reduce the complexity of the hybrid algorithm in order to reduce its complexity. As the hybrid algorithm is used for identifying fault nodes and replacing nodes with neighbor nodes, it is primarily used for the computation of grade values. With the proposed fault node recovery and energy efficient clustering methods, the energy consumption of each node can be minimized and the network lifetime can be improved as well. Using the MATLAB platform, we compared the suggested method to several existing ones including “Low Energy Adaptive Clustering Hierarchy (LEACH), Hybrid Hierarchical Clustering Approach (HHCA), Novel Energy Aware Hierarchical Cluster (NEAHC), and Heuristic Algorithm for Clustering Hierarchical Protocol (HACH)”, among others in terms of residual and consumption energy, as well as receiving packet data. |
|---|---|
| AbstractList | The Wireless Sensor Networks (WSNs) are designed for the monitoring of remote areas in various places with a variety of different applications. The main challenges with the WSN are energy efficiency and fault recovery. In order to optimize the network lifetime of the WSN, fault node recovery and energy efficient clustering are required in order to efficiently utilize the energy supply device of battery-powered sensors. The purpose of this paper is to develop a hybrid algorithm that combines the K-means clustering technique with fault node recovery in the WSN in order to reduce energy consumption and extend sensor lifetimes. A hybrid algorithm combine’s fault node recovery with energy-efficient clustering methods in order to reduce energy usage. We are using Grade Diffusion (GD) with Genetic Algorithm (GA) to detect fault nodes. In complex or large WSNs, K-means clustering can be used to reduce the complexity of the hybrid algorithm in order to reduce its complexity. As the hybrid algorithm is used for identifying fault nodes and replacing nodes with neighbor nodes, it is primarily used for the computation of grade values. With the proposed fault node recovery and energy efficient clustering methods, the energy consumption of each node can be minimized and the network lifetime can be improved as well. Using the MATLAB platform, we compared the suggested method to several existing ones including “Low Energy Adaptive Clustering Hierarchy (LEACH), Hybrid Hierarchical Clustering Approach (HHCA), Novel Energy Aware Hierarchical Cluster (NEAHC), and Heuristic Algorithm for Clustering Hierarchical Protocol (HACH)”, among others in terms of residual and consumption energy, as well as receiving packet data. |
| Author | Kulkarni, Omkaresh Sule, Bipin Banchhor, Chitrakant Patil, Rahul Takale, Dattatray G. Ghuge, Kalyani Mahalle, Parikshit N. |
| Author_xml | – sequence: 1 givenname: Dattatray G. surname: Takale fullname: Takale, Dattatray G. – sequence: 2 givenname: Parikshit N. surname: Mahalle fullname: Mahalle, Parikshit N. – sequence: 3 givenname: Omkaresh surname: Kulkarni fullname: Kulkarni, Omkaresh – sequence: 4 givenname: Bipin surname: Sule fullname: Sule, Bipin – sequence: 5 givenname: Chitrakant surname: Banchhor fullname: Banchhor, Chitrakant – sequence: 6 givenname: Kalyani surname: Ghuge fullname: Ghuge, Kalyani – sequence: 7 givenname: Rahul surname: Patil fullname: Patil, Rahul |
| BookMark | eNot0L1OwzAYhWELFYm2sHAFnpEC_osdj6gCWlSpA7CwRI79uRhSG9mBKndfCkxnes_wzNAkpggIXVJyLZRW4uZxtXmqaMPpCZoyKnVFKOETNCWsZhWTUp2hWSnvhAgtiZqi1-XY5eCw6bcph-Fth33K2JuvfsAxOcAZbPqGPGITHYYIeTti8D7YANGOOES8Dxl6KAUXiOUnjjDsU_4o5-jUm77Axf_O0cv93fNiWa03D6vF7bqylJGh6jxTVMgaBIjaCSG49R5q2XlpXNc0xjgDSmvLa7CsaYRxkkvQ3oDtrOB8jq7-fm1OpWTw7WcOO5PHlpL2V6U9qrRHFX4AjrpZtA |
| ContentType | Journal Article |
| DBID | AAYXX CITATION |
| DOI | 10.47974/JIOS-1831 |
| DatabaseName | CrossRef |
| DatabaseTitle | CrossRef |
| DatabaseTitleList | CrossRef |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Computer Science |
| EISSN | 2169-0103 |
| EndPage | 2367 |
| ExternalDocumentID | 10_47974_JIOS_1831 |
| GroupedDBID | -~X .DC 29K 30N 4.4 5GY AAIKQ AAKBW AAYXX ABCCY ABFIM ABJNI ABPEM ABTAI ABXYU ACAGQ ACFPA ACGFS ACTIO ADCVX ADXHL AEYOC AGDLA AGLEN AGROQ AIJEM AKOOK ALCKM ALMA_UNASSIGNED_HOLDINGS ALQZU AMATQ AMXXU AQRUH AVBZW AWYRJ BCCOT BLEHA BPLKW C06 CCCUG CITATION CRFIH D-I DGEBU DKSSO DMQIW DWIFK EBS EJD E~A E~B GTTXZ H13 HZ~ H~P IPNFZ IVXBP KYCEM LJTGL M4Z NUSFT O9- P2P PQQKQ PZZ QCRFL S-T SJN SNACF TAQ TDBHL TFMCV TFW TN5 TOXWX TTHFI UT5 |
| ID | FETCH-LOGICAL-c120t-bf271465e4e45d4443cffe56bf6adb88aadae799c35ec2884ad636e9faecbc433 |
| ISICitedReferencesCount | 0 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001386390500021&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 0252-2667 |
| IngestDate | Sat Nov 29 03:19:22 EST 2025 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 8 |
| Language | English |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c120t-bf271465e4e45d4443cffe56bf6adb88aadae799c35ec2884ad636e9faecbc433 |
| PageCount | 21 |
| ParticipantIDs | crossref_primary_10_47974_JIOS_1831 |
| PublicationCentury | 2000 |
| PublicationDate | 2024-00-00 |
| PublicationDateYYYYMMDD | 2024-01-01 |
| PublicationDate_xml | – year: 2024 text: 2024-00-00 |
| PublicationDecade | 2020 |
| PublicationTitle | Journal of information & optimization sciences |
| PublicationYear | 2024 |
| SSID | ssj0049607 |
| Score | 2.242396 |
| Snippet | The Wireless Sensor Networks (WSNs) are designed for the monitoring of remote areas in various places with a variety of different applications. The main... |
| SourceID | crossref |
| SourceType | Index Database |
| StartPage | 2347 |
| Title | Hybrid algorithm for fault node recovery and energy efficiency in wireless sensor networks |
| Volume | 45 |
| WOSCitedRecordID | wos001386390500021&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVAWR databaseName: Taylor & Francis Online Journals customDbUrl: eissn: 2169-0103 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0049607 issn: 0252-2667 databaseCode: TFW dateStart: 19800101 isFulltext: true titleUrlDefault: https://www.tandfonline.com providerName: Taylor & Francis |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1Lj9MwELbKwoELbwS7gCzBLQq0sR0nR17LIlAXaQusuFSOY7NR23TVpqvdP8bvY8Z20oiHtBy4RJXTadXOp3llvhlCnpWclUPIZeM0zUXMrQQ7yEYi1uAbEw0xdOGenn_5KMfj7Pg4_zQY_Gi5MGdzWdfZ-Xl--l9VDWegbKTO_oO6uw-FA3gNSocrqB2ul1L8wQWSsCI1_76ExP9k4RoJrdrMm6helrglRWPbpp-7ZDz1z7hBEo6FWSGvGzepgAVcQ44LwrVvFV__JZANs1c7IC3BCi0CvTMKHraL3CdqFjqY36gGAt2VuojePd_Wxd1uFx_arqrZ-qRqonF3-8NmPsNKDt4_XMyQOtVVs482Xu4VLuPu1zI8eToYu0QkMQQL3vkad5aMUuzlGrK-tfbDJwMqs77pZVz23DhOpvuTi-ASMihcf_3-8CgGezbaOsL24f8v_rHrWoR8yUlPUXaKslfI1USKHFeGTPa_thEAh6zQ0fTb3-TH4jrZF9339gKhXkQzuUVuBA3Slx5Ct8nA1HfIzXbNBw1W_y755hFFO0RR0Dd1iKKIKNoiigKiqEcU3SKKVjVtEUU9omiLqHvk8_7byeuDOKzkiPUoGTZxYRMJvlUYbrgoOedMW2tEWthUlUWWKVUqI_NcM2F0kmVclSlLTW6V0YXmjN0nO_WyNg8IFVwVEM3L0mSKa2sKaaximI8Ipfkwf0ietv_P9NRPXpn-roHdS71rj1xHuPnS2SOy06w25jG5ps-aar164pT3E0N_fro |
| linkProvider | Taylor & Francis |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Hybrid+algorithm+for+fault+node+recovery+and+energy+efficiency+in+wireless+sensor+networks&rft.jtitle=Journal+of+information+%26+optimization+sciences&rft.au=Takale%2C+Dattatray+G.&rft.au=Mahalle%2C+Parikshit+N.&rft.au=Kulkarni%2C+Omkaresh&rft.au=Sule%2C+Bipin&rft.date=2024&rft.issn=0252-2667&rft.eissn=2169-0103&rft.volume=45&rft.issue=8&rft.spage=2347&rft.epage=2367&rft_id=info:doi/10.47974%2FJIOS-1831&rft.externalDBID=n%2Fa&rft.externalDocID=10_47974_JIOS_1831 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0252-2667&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0252-2667&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0252-2667&client=summon |