Energy-aware evolutionary routing protocol for dynamic clustering of wireless sensor networks
The main challenges in designing and planning the operations of Wireless Sensor Networks (WSNs) are to optimize energy consumption and prolong network lifetime. Cluster-based routing techniques, such as the well-known low-energy adaptive clustering hierarchy (LEACH), are used to achieve scalable sol...
Saved in:
| Published in: | Swarm and evolutionary computation Vol. 1; no. 4; pp. 195 - 203 |
|---|---|
| Main Authors: | , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Elsevier B.V
01.12.2011
|
| Subjects: | |
| ISSN: | 2210-6502 |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Abstract | The main challenges in designing and planning the operations of Wireless Sensor Networks (WSNs) are to optimize energy consumption and prolong network lifetime. Cluster-based routing techniques, such as the well-known low-energy adaptive clustering hierarchy (LEACH), are used to achieve scalable solutions and extend the network lifetime until the last node dies (LND). Also, evolutionary algorithms (EAs), have been successfully used in recent years as meta-heuristics to address energy-aware routing challenges by designing intelligent models that collaborate together to optimize an appropriate energy-aware objective function. On the other hand, some protocols, such as stable election protocol (SEP), are concerned with another objective: extending the stability time until the first node dies (FND). Often, there is a tradeoff between extending the time until FND and the time until LND. To our knowledge, no attempt has been made to obtain a better compromise between the stability time and network lifetime. This paper reformulates the design of the most important characteristic of the EA (i.e., the objective function), so as to obtain a routing protocol that can provide more robust results than the existing heuristic and meta-heuristic protocols in terms of network stability period, lifetime, and energy consumption. An evolutionary-based routing protocol is proposed, which can guarantee better tradeoff between the lifespan and the stability period of the network with efficient energy utilization. To support this claim, extensive simulations on 90 homogeneous and heterogeneous WSN models are evaluated and compared against the LEACH, SEP, and one of the existing evolutionary-based routing protocols, hierarchical clustering-algorithm-based genetic algorithm (HCR).
► We model a new evolutionary-based routing protocol for dynamic clustering in WSN. ► Our results are compared with other protocols (LEACH, SEP, and HCR). ► Our protocol derives better tradeoff between network stability and network lifetime. |
|---|---|
| AbstractList | The main challenges in designing and planning the operations of Wireless Sensor Networks (WSNs) are to optimize energy consumption and prolong network lifetime. Cluster-based routing techniques, such as the well-known low-energy adaptive clustering hierarchy (LEACH), are used to achieve scalable solutions and extend the network lifetime until the last node dies (LND). Also, evolutionary algorithms (EAs), have been successfully used in recent years as meta-heuristics to address energy-aware routing challenges by designing intelligent models that collaborate together to optimize an appropriate energy-aware objective function. On the other hand, some protocols, such as stable election protocol (SEP), are concerned with another objective: extending the stability time until the first node dies (FND). Often, there is a tradeoff between extending the time until FND and the time until LND. To our knowledge, no attempt has been made to obtain a better compromise between the stability time and network lifetime. This paper reformulates the design of the most important characteristic of the EA (i.e., the objective function), so as to obtain a routing protocol that can provide more robust results than the existing heuristic and meta-heuristic protocols in terms of network stability period, lifetime, and energy consumption. An evolutionary-based routing protocol is proposed, which can guarantee better tradeoff between the lifespan and the stability period of the network with efficient energy utilization. To support this claim, extensive simulations on 90 homogeneous and heterogeneous WSN models are evaluated and compared against the LEACH, SEP, and one of the existing evolutionary-based routing protocols, hierarchical clustering-algorithm-based genetic algorithm (HCR).
► We model a new evolutionary-based routing protocol for dynamic clustering in WSN. ► Our results are compared with other protocols (LEACH, SEP, and HCR). ► Our protocol derives better tradeoff between network stability and network lifetime. |
| Author | Attea, Bara’a A. Khalil, Enan A. |
| Author_xml | – sequence: 1 givenname: Enan A. surname: Khalil fullname: Khalil, Enan A. email: enanameen@yahoo.com – sequence: 2 givenname: Bara’a A. surname: Attea fullname: Attea, Bara’a A. email: baraaali@yahoo.com |
| BookMark | eNqFkM1KAzEQgHOoYK19Ai95gV2T7GbXPXiQUn-g4EWPEtJkUlK3SUnSLn17s9aTBx0YZmDmG5jvCk2cd4DQDSUlJbS53ZZxgKMvGaG0JE1JSD1BU8YoKRpO2CWax7glORrCOO-m6GPpIGxOhRxkAJzR_pCsdzKccPC5dRu8Dz555XtsfMD65OTOKqz6Q0wQxrk3eLABeogRR3AxbzlIgw-f8RpdGNlHmP_UGXp_XL4tnovV69PL4mFVqIpUqWj5ur2jNa-4aulaU9kZ1XDJOsYA2pYbwjVpAXJqpjStteJGctZp2taVIdUMdee7KvgYAxihbJLjIylI2wtKxKhHbMW3HjHqEaQRWU9mq1_sPthdFvAPdX-mIL91tBBEVBacAp1VqCS0t3_yXxXNh0A |
| CitedBy_id | crossref_primary_10_1007_s00500_014_1462_y crossref_primary_10_1007_s11277_017_3973_1 crossref_primary_10_1007_s11277_013_1033_z crossref_primary_10_1016_j_adhoc_2023_103255 crossref_primary_10_1007_s11277_019_06788_y crossref_primary_10_1049_cmu2_12072 crossref_primary_10_1016_j_swevo_2013_06_002 crossref_primary_10_1520_JTE20180487 crossref_primary_10_1007_s11276_020_02438_5 crossref_primary_10_1007_s00521_019_04251_4 crossref_primary_10_1007_s11277_015_3006_x crossref_primary_10_1007_s10766_024_00775_y crossref_primary_10_1109_ACCESS_2019_2911190 crossref_primary_10_1016_j_jnca_2015_03_004 crossref_primary_10_1016_j_compeleceng_2018_03_036 crossref_primary_10_1007_s00521_018_3542_x crossref_primary_10_1007_s11042_021_10901_4 crossref_primary_10_1007_s11277_013_1262_1 crossref_primary_10_1007_s12652_017_0515_3 crossref_primary_10_1016_j_suscom_2017_08_006 crossref_primary_10_1007_s11276_016_1206_2 crossref_primary_10_1016_j_heliyon_2024_e34455 crossref_primary_10_1007_s12652_022_03711_5 crossref_primary_10_1007_s11276_017_1459_4 crossref_primary_10_1016_j_asoc_2022_109444 crossref_primary_10_1007_s11276_015_1013_1 crossref_primary_10_1007_s40998_022_00587_1 crossref_primary_10_1051_matecconf_201821803019 crossref_primary_10_1007_s12652_017_0619_9 crossref_primary_10_1007_s00500_017_2815_0 crossref_primary_10_1007_s10462_017_9564_4 crossref_primary_10_1007_s12083_016_0511_y crossref_primary_10_1016_j_asoc_2015_03_018 crossref_primary_10_1002_cpe_7809 crossref_primary_10_1016_j_comnet_2019_05_019 crossref_primary_10_1007_s11277_022_09966_7 crossref_primary_10_1007_s00500_012_0970_x crossref_primary_10_1002_dac_3463 crossref_primary_10_1007_s11276_019_02123_2 crossref_primary_10_1016_j_compag_2016_09_016 crossref_primary_10_1007_s11277_017_4572_x crossref_primary_10_1007_s11276_023_03598_w crossref_primary_10_1007_s11277_018_6043_4 crossref_primary_10_1134_S1064226917060122 crossref_primary_10_1016_j_suscom_2018_08_007 crossref_primary_10_1007_s11277_019_06413_y crossref_primary_10_1016_j_jnca_2017_01_031 crossref_primary_10_1007_s11277_021_08253_1 crossref_primary_10_1016_j_swevo_2015_07_007 crossref_primary_10_1007_s11277_019_06701_7 crossref_primary_10_4028_www_scientific_net_AMM_678_482 crossref_primary_10_1016_j_engappai_2016_10_014 crossref_primary_10_3390_app13052801 crossref_primary_10_1155_2014_415415 crossref_primary_10_1007_s11277_016_3564_6 crossref_primary_10_1007_s11277_019_06736_w crossref_primary_10_1109_JSEN_2017_2711660 crossref_primary_10_26634_jcs_7_4_15805 crossref_primary_10_3233_JIFS_210858 crossref_primary_10_1145_3414315 crossref_primary_10_1049_iet_com_2018_5778 crossref_primary_10_1155_2016_7950348 crossref_primary_10_1007_s11276_015_1156_0 crossref_primary_10_3390_s16101702 crossref_primary_10_1016_j_jnca_2015_02_004 crossref_primary_10_3390_s131114301 crossref_primary_10_1016_j_engappai_2014_04_009 crossref_primary_10_1016_j_asoc_2020_106115 crossref_primary_10_1016_j_asoc_2018_03_053 crossref_primary_10_1002_dac_4902 crossref_primary_10_3233_HIS_220012 crossref_primary_10_1016_j_cie_2022_108655 crossref_primary_10_1016_j_ins_2019_05_094 crossref_primary_10_3390_s21030791 crossref_primary_10_1109_MCE_2017_2684960 crossref_primary_10_1109_TCSS_2023_3262273 crossref_primary_10_4018_ijbdcn_2014070103 crossref_primary_10_3390_s17051084 crossref_primary_10_1016_j_engappai_2017_11_003 crossref_primary_10_1007_s42979_024_03301_6 crossref_primary_10_1080_0954898X_2023_2279971 crossref_primary_10_1155_2015_715740 crossref_primary_10_1016_j_asoc_2014_08_064 crossref_primary_10_1007_s11277_018_5683_8 crossref_primary_10_1016_j_cosrev_2021_100396 crossref_primary_10_1002_dac_4337 crossref_primary_10_1007_s11277_012_0664_9 crossref_primary_10_1007_s11277_015_2535_7 crossref_primary_10_1007_s11277_023_10486_1 crossref_primary_10_1007_s11277_012_0811_3 crossref_primary_10_1109_JIOT_2019_2940988 crossref_primary_10_1016_j_eswa_2023_119706 crossref_primary_10_1007_s00500_020_05563_7 crossref_primary_10_1007_s11277_020_07094_8 crossref_primary_10_1007_s11277_020_07030_w crossref_primary_10_1155_2015_409503 crossref_primary_10_1016_j_swevo_2013_04_002 crossref_primary_10_1016_j_swevo_2013_04_001 crossref_primary_10_3390_computers2040152 crossref_primary_10_1109_JSEN_2015_2463112 |
| Cites_doi | 10.1504/IJWMC.2009.028898 10.1145/937503.937505 10.1109/MCOM.2002.1024422 10.1109/HICSS.2000.926982 10.1109/TWC.2002.804190 10.1109/MWC.2004.1368897 10.1109/MWC.2004.1368893 10.1109/SURV.2011.040310.00002 10.1109/ICCW.2010.5503895 10.1109/MCI.2008.930983 |
| ContentType | Journal Article |
| Copyright | 2011 Elsevier B.V. |
| Copyright_xml | – notice: 2011 Elsevier B.V. |
| DBID | AAYXX CITATION |
| DOI | 10.1016/j.swevo.2011.06.004 |
| DatabaseName | CrossRef |
| DatabaseTitle | CrossRef |
| DatabaseTitleList | |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Computer Science |
| EndPage | 203 |
| ExternalDocumentID | 10_1016_j_swevo_2011_06_004 S2210650211000277 |
| GroupedDBID | --K --M .~1 0R~ 1~. 1~5 4.4 457 4G. 5VS 7-5 8P~ AAAKF AABVA AACTN AAEDT AAEDW AAIAV AAIKJ AAKOC AALRI AAOAW AAQFI AARIN AATLK AAXUO AAYFN ABAOU ABBOA ABGRD ABMAC ABUCO ABXDB ABYKQ ACAZW ACDAQ ACGFS ACNNM ACRLP ACZNC ADBBV ADEZE ADMUD ADQTV ADTZH AEBSH AECPX AEKER AENEX AEQOU AFKWA AFTJW AFXIZ AGHFR AGUBO AGYEJ AHJVU AHZHX AIALX AIEXJ AIKHN AITUG AJBFU AJOXV ALMA_UNASSIGNED_HOLDINGS AMFUW AMRAJ AOUOD APLSM ARUGR AXJTR BJAXD BKOJK BLXMC CBWCG EBS EFJIC EFLBG EJD FDB FEDTE FIRID FNPLU FYGXN GBLVA GBOLZ HAMUX HVGLF HZ~ J1W JJJVA KOM M41 MHUIS MO0 N9A O-L O9- OAUVE P-8 P-9 PC. Q38 RIG ROL SDF SES SPC SPCBC SSA SSB SSD SST SSV SSW SSZ T5K ~G- AATTM AAXKI AAYWO AAYXX ABJNI ABWVN ACLOT ACRPL ACVFH ADCNI ADNMO AEIPS AEUPX AFJKZ AFPUW AIGII AIIUN AKBMS AKRWK AKYEP ANKPU APXCP CITATION EFKBS ~HD |
| ID | FETCH-LOGICAL-c303t-75b7814535c71bd1a9fc65a2922ee775f05d07ee07ed2cd14dc5fa529d1743f03 |
| ISICitedReferencesCount | 130 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000209360200002&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 2210-6502 |
| IngestDate | Sat Nov 29 08:13:11 EST 2025 Tue Nov 18 22:43:16 EST 2025 Fri Feb 23 02:26:28 EST 2024 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 4 |
| Keywords | Wireless sensor network Meta-heuristic Energy-aware Clustering Routing protocol Evolutionary algorithm |
| Language | English |
| License | https://www.elsevier.com/tdm/userlicense/1.0 |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c303t-75b7814535c71bd1a9fc65a2922ee775f05d07ee07ed2cd14dc5fa529d1743f03 |
| PageCount | 9 |
| ParticipantIDs | crossref_citationtrail_10_1016_j_swevo_2011_06_004 crossref_primary_10_1016_j_swevo_2011_06_004 elsevier_sciencedirect_doi_10_1016_j_swevo_2011_06_004 |
| PublicationCentury | 2000 |
| PublicationDate | 2011-12-01 |
| PublicationDateYYYYMMDD | 2011-12-01 |
| PublicationDate_xml | – month: 12 year: 2011 text: 2011-12-01 day: 01 |
| PublicationDecade | 2010 |
| PublicationTitle | Swarm and evolutionary computation |
| PublicationYear | 2011 |
| Publisher | Elsevier B.V |
| Publisher_xml | – name: Elsevier B.V |
| References | Romer, Mattern (br000015) 2004; 11 A.W. Matin, S. Hussain, Intelligent hierarchical cluster-based routing, in: Proceedings of the International Workshop on Mobility and Scalability in Wireless Sensor Networks, MSWSN, in: IEEE International Conference on Distributed Computing in Sensor Networks, DCOSS, June 2006, pp. 165–172. D.C. Hoang, P. Yadav, R. Kumar, S.K. Panda, A robust harmony search algorithm based clustering protocol for wireless sensor networks, in: IEEE International Conference on Communications Workshops, 2010. Venayagamoorthy (br000050) 2009; 4 S. Mudundi, H.H. Ali, A new robust genetic algorithm for dynamic cluster formation in wireless sensor networks, in: Proceedings of Wireless and Optical Communications, Montreal, Quebec, Canada, May 2007. S. Hussain, A.W. Matin, Hierarchical cluster-based routing in wireless sensor networks, in: IEEE/ACM International Conference on Information Processing in Sensor Networks, IPSN, 2006. Engelbrecht (br000055) 2007 X.-S. Yang, Harmony search as a metaheuristic algorithm, in: Z.W. Geem (Ed.), Music-Inspired Harmony Search Algorithm Theory and Applications, 2009. Kulkarni, Förster, Venayagamoorthy (br000115) 2011; 13 Shakshuki, Malik (br000105) 2009; 3 Ammari (br000030) 2009; vol. 215 G. Smaragdakis, I. Matta, A. Bestavros, SEP: a stable election protocol for clustered heterogeneous wireless sensor networks, in: Second International Workshop on Sensor and Actor Network Protocols and Applications, SANPA 2004, Boston MA, Aug. 2004. Blum, Roli (br000070) 2003; 35 Heinzelman, Chandrakasan, Balakrishnan (br000035) 2002; 1 Hussain, Islam, Matin (br000095) 2007 S. Jin, M. Zhou, A.S. Wu, Sensor network optimization using a genetic algorithm, in: Proceedings of the 7th World Multiconference on Systemics, Cybernetics and Informatics, 2003. Al-Karaki, Kamal (br000025) 2004; 11 W. Heinzelman, A. Chandrakasan, H. Balakrishnan, Energy-efficient communication protocol for wireless microsensor networks, in: Proceedings of the 33rd International Conference on System Science, HICSS’00, Hawaii, USA, Jan. 2000, pp. 1–10. Hussain, Matin, Islam (br000090) 2007; 2 Konar (br000060) 2005 Das, Abraham, Konar (br000110) 2009; vol. 178 Akyildiz, Su, Sankarasubramaniam, Cayirci (br000020) 2002 Murthy, Manoj (br000010) 2004 MIT (br000005) 2004 Yang (br000065) 2008 MIT (10.1016/j.swevo.2011.06.004_br000005) 2004 Hussain (10.1016/j.swevo.2011.06.004_br000095) 2007 10.1016/j.swevo.2011.06.004_br000080 Al-Karaki (10.1016/j.swevo.2011.06.004_br000025) 2004; 11 Yang (10.1016/j.swevo.2011.06.004_br000065) 2008 Blum (10.1016/j.swevo.2011.06.004_br000070) 2003; 35 Akyildiz (10.1016/j.swevo.2011.06.004_br000020) 2002 Hussain (10.1016/j.swevo.2011.06.004_br000090) 2007; 2 Romer (10.1016/j.swevo.2011.06.004_br000015) 2004; 11 10.1016/j.swevo.2011.06.004_br000075 Konar (10.1016/j.swevo.2011.06.004_br000060) 2005 Murthy (10.1016/j.swevo.2011.06.004_br000010) 2004 Heinzelman (10.1016/j.swevo.2011.06.004_br000035) 2002; 1 Ammari (10.1016/j.swevo.2011.06.004_br000030) 2009; vol. 215 10.1016/j.swevo.2011.06.004_br000045 10.1016/j.swevo.2011.06.004_br000100 Kulkarni (10.1016/j.swevo.2011.06.004_br000115) 2011; 13 Venayagamoorthy (10.1016/j.swevo.2011.06.004_br000050) 2009; 4 Das (10.1016/j.swevo.2011.06.004_br000110) 2009; vol. 178 10.1016/j.swevo.2011.06.004_br000125 10.1016/j.swevo.2011.06.004_br000085 Shakshuki (10.1016/j.swevo.2011.06.004_br000105) 2009; 3 10.1016/j.swevo.2011.06.004_br000120 10.1016/j.swevo.2011.06.004_br000040 Engelbrecht (10.1016/j.swevo.2011.06.004_br000055) 2007 |
| References_xml | – start-page: 147 year: 2007 end-page: 154 ident: br000095 article-title: Genetic algorithm for energy efficient clusters in wireless sensor networks publication-title: Proceedings of the 4th International Conference on Information Technology: New Generations, ITNG – reference: X.-S. Yang, Harmony search as a metaheuristic algorithm, in: Z.W. Geem (Ed.), Music-Inspired Harmony Search Algorithm Theory and Applications, 2009. – year: 2004 ident: br000010 article-title: Ad Hoc Wireless Networks: Architectures and Protocols – year: 2005 ident: br000060 article-title: Computational Intelligence: Principles, Techniques and applications – reference: A.W. Matin, S. Hussain, Intelligent hierarchical cluster-based routing, in: Proceedings of the International Workshop on Mobility and Scalability in Wireless Sensor Networks, MSWSN, in: IEEE International Conference on Distributed Computing in Sensor Networks, DCOSS, June 2006, pp. 165–172. – volume: vol. 215 year: 2009 ident: br000030 publication-title: Challenges and Opportunities of Connected k-Covered Wireless Sensor Networks From Sensor Deployment to Data Gathering – volume: 35 start-page: 268 year: 2003 end-page: 308 ident: br000070 article-title: Metaheuristics in combinatorial optimization: overview and conceptual comparison publication-title: ACM Computing Surveys – volume: 11 start-page: 6 year: 2004 end-page: 28 ident: br000025 article-title: Routing techniques in wireless sensor networks: a survey publication-title: IEEE Wireless Communications – volume: 4 start-page: 14 year: 2009 end-page: 23 ident: br000050 article-title: A successful interdisciplinary course on computational intelligence publication-title: IEEE Computational Intelligence Magazine – volume: vol. 178 year: 2009 ident: br000110 publication-title: Metaheuristic Clustering – reference: D.C. Hoang, P. Yadav, R. Kumar, S.K. Panda, A robust harmony search algorithm based clustering protocol for wireless sensor networks, in: IEEE International Conference on Communications Workshops, 2010. – volume: 3 start-page: 165 year: 2009 end-page: 176 ident: br000105 article-title: Multi-agent-based clustering approach to wireless sensor networks publication-title: Int. J. Wireless and Mobile Computing – reference: S. Hussain, A.W. Matin, Hierarchical cluster-based routing in wireless sensor networks, in: IEEE/ACM International Conference on Information Processing in Sensor Networks, IPSN, 2006. – volume: 13 start-page: 68 year: 2011 end-page: 96 ident: br000115 article-title: Computational intelligence in wireless sensor networks: A survey publication-title: IEEE Communications Surveys & Tutorials – reference: W. Heinzelman, A. Chandrakasan, H. Balakrishnan, Energy-efficient communication protocol for wireless microsensor networks, in: Proceedings of the 33rd International Conference on System Science, HICSS’00, Hawaii, USA, Jan. 2000, pp. 1–10. – reference: S. Jin, M. Zhou, A.S. Wu, Sensor network optimization using a genetic algorithm, in: Proceedings of the 7th World Multiconference on Systemics, Cybernetics and Informatics, 2003. – reference: S. Mudundi, H.H. Ali, A new robust genetic algorithm for dynamic cluster formation in wireless sensor networks, in: Proceedings of Wireless and Optical Communications, Montreal, Quebec, Canada, May 2007. – volume: 2 start-page: 87 year: 2007 end-page: 97 ident: br000090 article-title: Genetic algorithm for hierarchical wireless sensor networks publication-title: Journal of Networks (JNW) – year: 2008 ident: br000065 article-title: Nature-Inspired Metaheuristic Algorithms – start-page: 20 year: 2004 end-page: 30 ident: br000005 article-title: Emerging technologies that will change the world publication-title: IEEE Engineering Management Review – year: 2007 ident: br000055 article-title: Computational Intelligence: An Introduction – reference: G. Smaragdakis, I. Matta, A. Bestavros, SEP: a stable election protocol for clustered heterogeneous wireless sensor networks, in: Second International Workshop on Sensor and Actor Network Protocols and Applications, SANPA 2004, Boston MA, Aug. 2004. – start-page: 102 year: 2002 end-page: 114 ident: br000020 article-title: A survey on sensor networks publication-title: IEEE Communications Magazine – volume: 1 start-page: 660 year: 2002 end-page: 670 ident: br000035 article-title: An application-specific protocol architecture for wireless microsensor networks publication-title: IEEE Transactions on Wireless Communications – volume: 11 start-page: 54 year: 2004 end-page: 61 ident: br000015 article-title: The design space of wireless sensor networks publication-title: IEEE Wireless Communications – year: 2008 ident: 10.1016/j.swevo.2011.06.004_br000065 – volume: 3 start-page: 165 issue: 3 year: 2009 ident: 10.1016/j.swevo.2011.06.004_br000105 article-title: Multi-agent-based clustering approach to wireless sensor networks publication-title: Int. J. Wireless and Mobile Computing doi: 10.1504/IJWMC.2009.028898 – volume: 35 start-page: 268 year: 2003 ident: 10.1016/j.swevo.2011.06.004_br000070 article-title: Metaheuristics in combinatorial optimization: overview and conceptual comparison publication-title: ACM Computing Surveys doi: 10.1145/937503.937505 – start-page: 102 issue: Aug. year: 2002 ident: 10.1016/j.swevo.2011.06.004_br000020 article-title: A survey on sensor networks publication-title: IEEE Communications Magazine doi: 10.1109/MCOM.2002.1024422 – ident: 10.1016/j.swevo.2011.06.004_br000040 doi: 10.1109/HICSS.2000.926982 – volume: 1 start-page: 660 issue: 4 year: 2002 ident: 10.1016/j.swevo.2011.06.004_br000035 article-title: An application-specific protocol architecture for wireless microsensor networks publication-title: IEEE Transactions on Wireless Communications doi: 10.1109/TWC.2002.804190 – ident: 10.1016/j.swevo.2011.06.004_br000085 – year: 2004 ident: 10.1016/j.swevo.2011.06.004_br000010 – volume: 11 start-page: 54 issue: 6 year: 2004 ident: 10.1016/j.swevo.2011.06.004_br000015 article-title: The design space of wireless sensor networks publication-title: IEEE Wireless Communications doi: 10.1109/MWC.2004.1368897 – ident: 10.1016/j.swevo.2011.06.004_br000075 – volume: 11 start-page: 6 issue: 6 year: 2004 ident: 10.1016/j.swevo.2011.06.004_br000025 article-title: Routing techniques in wireless sensor networks: a survey publication-title: IEEE Wireless Communications doi: 10.1109/MWC.2004.1368893 – year: 2007 ident: 10.1016/j.swevo.2011.06.004_br000055 – volume: 13 start-page: 68 issue: 1 year: 2011 ident: 10.1016/j.swevo.2011.06.004_br000115 article-title: Computational intelligence in wireless sensor networks: A survey publication-title: IEEE Communications Surveys & Tutorials doi: 10.1109/SURV.2011.040310.00002 – volume: vol. 215 year: 2009 ident: 10.1016/j.swevo.2011.06.004_br000030 – ident: 10.1016/j.swevo.2011.06.004_br000045 – ident: 10.1016/j.swevo.2011.06.004_br000100 – ident: 10.1016/j.swevo.2011.06.004_br000125 doi: 10.1109/ICCW.2010.5503895 – volume: 2 start-page: 87 issue: 7 year: 2007 ident: 10.1016/j.swevo.2011.06.004_br000090 article-title: Genetic algorithm for hierarchical wireless sensor networks publication-title: Journal of Networks (JNW) – ident: 10.1016/j.swevo.2011.06.004_br000080 – volume: vol. 178 year: 2009 ident: 10.1016/j.swevo.2011.06.004_br000110 – year: 2005 ident: 10.1016/j.swevo.2011.06.004_br000060 – start-page: 20 issue: Feb. year: 2004 ident: 10.1016/j.swevo.2011.06.004_br000005 article-title: Emerging technologies that will change the world publication-title: IEEE Engineering Management Review – ident: 10.1016/j.swevo.2011.06.004_br000120 – volume: 4 start-page: 14 issue: 1 year: 2009 ident: 10.1016/j.swevo.2011.06.004_br000050 article-title: A successful interdisciplinary course on computational intelligence publication-title: IEEE Computational Intelligence Magazine doi: 10.1109/MCI.2008.930983 – start-page: 147 year: 2007 ident: 10.1016/j.swevo.2011.06.004_br000095 article-title: Genetic algorithm for energy efficient clusters in wireless sensor networks |
| SSID | ssj0000602559 |
| Score | 2.2885573 |
| Snippet | The main challenges in designing and planning the operations of Wireless Sensor Networks (WSNs) are to optimize energy consumption and prolong network... |
| SourceID | crossref elsevier |
| SourceType | Enrichment Source Index Database Publisher |
| StartPage | 195 |
| SubjectTerms | Clustering Energy-aware Evolutionary algorithm Meta-heuristic Routing protocol Wireless sensor network |
| Title | Energy-aware evolutionary routing protocol for dynamic clustering of wireless sensor networks |
| URI | https://dx.doi.org/10.1016/j.swevo.2011.06.004 |
| Volume | 1 |
| WOSCitedRecordID | wos000209360200002&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: PRVESC databaseName: Elsevier SD Freedom Collection Journals 2021 issn: 2210-6502 databaseCode: AIEXJ dateStart: 20110301 customDbUrl: isFulltext: true dateEnd: 99991231 titleUrlDefault: https://www.sciencedirect.com omitProxy: false ssIdentifier: ssj0000602559 providerName: Elsevier |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV3da9swEBdbuoe9rNu6sX5s6GFvq4stW1H8GErGNkYZtIO8FCNLMlsJdomdtn9-7_ThOKSUbbCHmGDkXKL75XQn_e6OkI-xzpQARzXivGRRJmMRSSlLiFpVyTFXk6U2Ufi7ODubzOf5D38U09p2AqKuJ3d3-fV_VTXcA2Vj6uxfqLv_ULgB70HpcAW1w_WPFD-z2XyRvEVOl7nxspAct2xWnUs-b7oGAGAphtq1pP-kFiusmeBJ0FjBeIFGsIUwF0bVji3eDn3Zc5DgGmxsSFG2T8TmAf8v8PbtXvOsBnsyPelh1gHG_LGHDLyLXIYRut9e3WR2bKfJoCVjEFdG4Apumt0BurKBCU1c002_GjNbAWHb0Ls9h6uT9hZ-oq_EisdK2Xpd69mG5ygfxWN5PDyzfkp2GAB0MiI706-z-bd-Uy4e2xALGxKGrxwqVVlO4Ja0h72ZgYdy8ZK88KEFnTpIvCJPTP2a7Ia2HdRb8T1yOUQIHeqOeoTQgBAKCKEeIXSNENpUNCCEOoTQgJA35Ofn2cXpl8h32YgUuC9dJHiJZc94ypVISp3IvFJjLlnOmDFC8CrmOhbGwEszpZNMK15JznKNwWwVp2_JqG5q845QzaqkKuM8K2Wa5RJCeVYxDqtCyhQ3MdsnLMxWoXwJeuyEsigC1_CqsFNc4BQXlnGZ7ZPj_qFrV4Hl8eHjoIbCO5HOOSwAOo89ePCvDx6S5-t_whEZdcuVeU-eqZvud7v84CF2DydgmuM |
| linkProvider | Elsevier |
| 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=Energy-aware+evolutionary+routing+protocol+for+dynamic+clustering+of+wireless+sensor+networks&rft.jtitle=Swarm+and+evolutionary+computation&rft.au=Khalil%2C+Enan+A.&rft.au=Attea%2C+Bara%E2%80%99a+A.&rft.date=2011-12-01&rft.pub=Elsevier+B.V&rft.issn=2210-6502&rft.volume=1&rft.issue=4&rft.spage=195&rft.epage=203&rft_id=info:doi/10.1016%2Fj.swevo.2011.06.004&rft.externalDocID=S2210650211000277 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2210-6502&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2210-6502&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2210-6502&client=summon |