Optimal load balanced clustering in homogeneous wireless sensor networks

Summary Balancing the load among sensor nodes is a major challenge for the long run operation of wireless sensor networks. When a sensor node becomes overloaded, the likelihood of higher latency, energy loss, and congestion becomes high. In this paper, we propose an optimal load balanced clustering...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:International journal of communication systems Jg. 30; H. 10
Hauptverfasser: Souissi, Manel, Meddeb, Aref
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Chichester Wiley Subscription Services, Inc 10.07.2017
Schlagworte:
ISSN:1074-5351, 1099-1131
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Abstract Summary Balancing the load among sensor nodes is a major challenge for the long run operation of wireless sensor networks. When a sensor node becomes overloaded, the likelihood of higher latency, energy loss, and congestion becomes high. In this paper, we propose an optimal load balanced clustering for hierarchical cluster‐based wireless sensor networks. We formulate the network design problem as mixed‐integer linear programming. Our contribution is 3‐fold: First, we propose an energy aware cluster head selection model for optimal cluster head selection. Then we propose a delay and energy‐aware routing model for optimal inter‐cluster communication. Finally, we propose an equal traffic for energy efficient clustering for optimal load balanced clustering. We consider the worst case scenario, where all nodes have the same capability and where there are no ways to use mobile sinks or add some powerful nodes as gateways. Thus, our models perform load balancing and maximize network lifetime with no need for special node capabilities such as mobility or heterogeneity or pre‐deployment, which would greatly simplify the problem. We show that the proposed models not only increase network lifetime but also minimize latency between sensor nodes. Numerical results show that energy consumption can be effectively balanced among sensor nodes, and stability period can be greatly extended using our models. We propose a novel clustering scheme in homogeneous Wireless Sensor Networks (WSNs) that considers efficient CH election, assures efficient routing, and takes load balanced clustering into account. Three mixed‐integer linear programming (MILP) are proposed. Energy Aware Cluster Head Selection (EACHS) for optimal Cluster Head (CH) selection, Delay and Energy‐Aware Routing (DEAR) for optimal inter‐cluster communication, and EQual Traffic for Energy Efficient Clustering (EQTEEC) for optimal load balanced clustering.
AbstractList Summary Balancing the load among sensor nodes is a major challenge for the long run operation of wireless sensor networks. When a sensor node becomes overloaded, the likelihood of higher latency, energy loss, and congestion becomes high. In this paper, we propose an optimal load balanced clustering for hierarchical cluster‐based wireless sensor networks. We formulate the network design problem as mixed‐integer linear programming. Our contribution is 3‐fold: First, we propose an energy aware cluster head selection model for optimal cluster head selection. Then we propose a delay and energy‐aware routing model for optimal inter‐cluster communication. Finally, we propose an equal traffic for energy efficient clustering for optimal load balanced clustering. We consider the worst case scenario, where all nodes have the same capability and where there are no ways to use mobile sinks or add some powerful nodes as gateways. Thus, our models perform load balancing and maximize network lifetime with no need for special node capabilities such as mobility or heterogeneity or pre‐deployment, which would greatly simplify the problem. We show that the proposed models not only increase network lifetime but also minimize latency between sensor nodes. Numerical results show that energy consumption can be effectively balanced among sensor nodes, and stability period can be greatly extended using our models. We propose a novel clustering scheme in homogeneous Wireless Sensor Networks (WSNs) that considers efficient CH election, assures efficient routing, and takes load balanced clustering into account. Three mixed‐integer linear programming (MILP) are proposed. Energy Aware Cluster Head Selection (EACHS) for optimal Cluster Head (CH) selection, Delay and Energy‐Aware Routing (DEAR) for optimal inter‐cluster communication, and EQual Traffic for Energy Efficient Clustering (EQTEEC) for optimal load balanced clustering.
Summary Balancing the load among sensor nodes is a major challenge for the long run operation of wireless sensor networks. When a sensor node becomes overloaded, the likelihood of higher latency, energy loss, and congestion becomes high. In this paper, we propose an optimal load balanced clustering for hierarchical cluster-based wireless sensor networks. We formulate the network design problem as mixed-integer linear programming. Our contribution is 3-fold: First, we propose an energy aware cluster head selection model for optimal cluster head selection. Then we propose a delay and energy-aware routing model for optimal inter-cluster communication. Finally, we propose an equal traffic for energy efficient clustering for optimal load balanced clustering. We consider the worst case scenario, where all nodes have the same capability and where there are no ways to use mobile sinks or add some powerful nodes as gateways. Thus, our models perform load balancing and maximize network lifetime with no need for special node capabilities such as mobility or heterogeneity or pre-deployment, which would greatly simplify the problem. We show that the proposed models not only increase network lifetime but also minimize latency between sensor nodes. Numerical results show that energy consumption can be effectively balanced among sensor nodes, and stability period can be greatly extended using our models.
Balancing the load among sensor nodes is a major challenge for the long run operation of wireless sensor networks. When a sensor node becomes overloaded, the likelihood of higher latency, energy loss, and congestion becomes high. In this paper, we propose an optimal load balanced clustering for hierarchical cluster‐based wireless sensor networks. We formulate the network design problem as mixed‐integer linear programming. Our contribution is 3‐fold: First, we propose an energy aware cluster head selection model for optimal cluster head selection. Then we propose a delay and energy‐aware routing model for optimal inter‐cluster communication. Finally, we propose an equal traffic for energy efficient clustering for optimal load balanced clustering. We consider the worst case scenario, where all nodes have the same capability and where there are no ways to use mobile sinks or add some powerful nodes as gateways. Thus, our models perform load balancing and maximize network lifetime with no need for special node capabilities such as mobility or heterogeneity or pre‐deployment, which would greatly simplify the problem. We show that the proposed models not only increase network lifetime but also minimize latency between sensor nodes. Numerical results show that energy consumption can be effectively balanced among sensor nodes, and stability period can be greatly extended using our models.
Author Souissi, Manel
Meddeb, Aref
Author_xml – sequence: 1
  givenname: Manel
  surname: Souissi
  fullname: Souissi, Manel
  email: manel.souissi@gmail.com
  organization: University of Tunis El‐Manar
– sequence: 2
  givenname: Aref
  surname: Meddeb
  fullname: Meddeb, Aref
  organization: University of Sousse
BookMark eNp1kM1LAzEQxYNUsK2Cf0LAi5etk81-5VjqJxR60XPIZid1a5rUZJfS_96t9SR6moH5vTe8NyEj5x0Scs1gxgDSu0bpGU9TcUbGDIRIGONsdNzLLMl5zi7IJMYNAFRpkY_J82rXtVtlqfWqobWyymlsqLZ97DC0bk1bR9_91q_Roe8j3bcBLcZII7roA3XY7X34iJfk3Cgb8epnTsnb48Pr4jlZrp5eFvNlolPBRWLSqq4rZJrXVVNAZioQqigMQGGQq6YuDTaoh4NJM4Ba5ADc6HwQqUzkyKfk5uS7C_6zx9jJje-DG15KJoBlRV6W5UDdnigdfIwBjdyFIWY4SAby2JMcepLHngZ09gvVbae61rsuqNb-JUhOgn1r8fCvsbyfL775L_Jje4M
CitedBy_id crossref_primary_10_1007_s11277_021_08617_7
crossref_primary_10_1016_j_comnet_2020_107376
crossref_primary_10_1007_s11227_024_06242_2
crossref_primary_10_1007_s11277_019_06698_z
crossref_primary_10_1109_TNSE_2023_3274693
Cites_doi 10.1109/ICC.2003.1203919
10.1109/AERO.2002.1035242
10.1109/JSEN.2012.2227704
10.1007/s11276-007-0035-8
10.1002/dac.2669
10.1016/j.adhoc.2008.04.003
10.1109/ICEEE.2010.5661337
10.1007/978-3-642-36071-8_21
10.1109/IWCMC.2015.7289160
10.1016/j.compeleceng.2014.07.010
10.1109/IPDPS.2002.1016600
10.1109/ICEEI.2009.5254694
10.1109/ICC.2004.1312874
10.1016/j.swevo.2013.04.002
10.1016/j.engappai.2014.04.009
10.1109/MOBHOC.2007.4428638
10.1002/dac.2720
10.1016/j.comcom.2015.05.009
10.1016/j.apm.2013.10.044
10.1109/AIMSEC.2011.6010559
10.1016/j.comcom.2015.06.001
10.1016/j.comnet.2016.01.015
10.1002/dac.2954
10.14738/tnc.25.488
10.1016/j.compeleceng.2014.07.019
10.1016/j.asoc.2015.11.044
10.1109/CMC.2010.147
10.1016/j.comnet.2015.12.021
10.1109/TWC.2002.804190
10.1109/TMC.2004.41
10.1002/dac.2785
ContentType Journal Article
Copyright Copyright © 2016 John Wiley & Sons, Ltd.
Copyright © 2017 John Wiley & Sons, Ltd.
Copyright_xml – notice: Copyright © 2016 John Wiley & Sons, Ltd.
– notice: Copyright © 2017 John Wiley & Sons, Ltd.
DBID AAYXX
CITATION
7SP
8FD
JQ2
L7M
DOI 10.1002/dac.3229
DatabaseName CrossRef
Electronics & Communications Abstracts
Technology Research Database
ProQuest Computer Science Collection
Advanced Technologies Database with Aerospace
DatabaseTitle CrossRef
Technology Research Database
Advanced Technologies Database with Aerospace
Electronics & Communications Abstracts
ProQuest Computer Science Collection
DatabaseTitleList
Technology Research Database
CrossRef
DeliveryMethod fulltext_linktorsrc
Discipline Engineering
EISSN 1099-1131
EndPage n/a
ExternalDocumentID 10_1002_dac_3229
DAC3229
Genre article
GroupedDBID .3N
.GA
05W
0R~
10A
1L6
1OB
1OC
33P
3SF
3WU
4.4
50Y
50Z
51W
51X
52M
52N
52O
52P
52S
52T
52U
52W
52X
5GY
5VS
66C
702
7PT
8-0
8-1
8-3
8-4
8-5
8UM
930
A03
AAESR
AAEVG
AAHHS
AAHQN
AAMNL
AANLZ
AAONW
AASGY
AAXRX
AAYCA
AAZKR
ABCQN
ABCUV
ABDBF
ABIJN
ABPVW
ACAHQ
ACCFJ
ACCZN
ACGFS
ACIWK
ACPOU
ACUHS
ACXBN
ACXQS
ADBBV
ADEOM
ADIZJ
ADKYN
ADMGS
ADOZA
ADXAS
ADZMN
ADZOD
AEEZP
AEIGN
AEIMD
AENEX
AEQDE
AEUQT
AEUYR
AFBPY
AFFPM
AFGKR
AFPWT
AFWVQ
AHBTC
AITYG
AIURR
AIWBW
AJBDE
AJXKR
ALAGY
ALMA_UNASSIGNED_HOLDINGS
ALUQN
ALVPJ
AMBMR
AMYDB
ATUGU
AUFTA
AZBYB
AZVAB
BAFTC
BFHJK
BHBCM
BMNLL
BMXJE
BNHUX
BROTX
BRXPI
BY8
CS3
D-E
D-F
DCZOG
DPXWK
DR2
DRFUL
DRSTM
DU5
EBS
EJD
ESX
F00
F01
F04
G-S
G.N
GNP
GODZA
H.T
H.X
HGLYW
HHY
HZ~
I-F
IX1
J0M
JPC
KQQ
LATKE
LAW
LC2
LC3
LEEKS
LITHE
LOXES
LP6
LP7
LUTES
LYRES
MEWTI
MK4
MK~
ML~
MRFUL
MRSTM
MSFUL
MSSTM
MXFUL
MXSTM
N04
N05
N9A
NF~
O66
O9-
OIG
P2W
P2X
P4D
Q.N
Q11
QB0
QRW
R.K
ROL
RWI
RX1
RYL
SUPJJ
TUS
UB1
V2E
W8V
W99
WBKPD
WIH
WIK
WLBEL
WOHZO
WQJ
WRC
WWI
WXSBR
WYISQ
XG1
XV2
ZZTAW
~IA
~WT
AAMMB
AAYXX
AEFGJ
AEYWJ
AGHNM
AGXDD
AGYGG
AIDQK
AIDYY
CITATION
O8X
7SP
8FD
JQ2
L7M
ID FETCH-LOGICAL-c2939-f28bb8e1c3b8d604f809a66f006fe3adb7fedec04ff2400b95003fc5bb8a495e3
IEDL.DBID DRFUL
ISICitedReferencesCount 7
ISICitedReferencesURI http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000405969000004&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN 1074-5351
IngestDate Fri Jul 25 12:12:01 EDT 2025
Tue Nov 18 22:12:35 EST 2025
Sat Nov 29 07:46:57 EST 2025
Wed Jan 22 17:05:59 EST 2025
IsPeerReviewed true
IsScholarly true
Issue 10
Language English
License http://onlinelibrary.wiley.com/termsAndConditions#vor
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c2939-f28bb8e1c3b8d604f809a66f006fe3adb7fedec04ff2400b95003fc5bb8a495e3
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
PQID 1901465777
PQPubID 996367
PageCount 15
ParticipantIDs proquest_journals_1901465777
crossref_primary_10_1002_dac_3229
crossref_citationtrail_10_1002_dac_3229
wiley_primary_10_1002_dac_3229_DAC3229
PublicationCentury 2000
PublicationDate 10 July 2017
PublicationDateYYYYMMDD 2017-07-10
PublicationDate_xml – month: 07
  year: 2017
  text: 10 July 2017
  day: 10
PublicationDecade 2010
PublicationPlace Chichester
PublicationPlace_xml – name: Chichester
PublicationTitle International journal of communication systems
PublicationYear 2017
Publisher Wiley Subscription Services, Inc
Publisher_xml – name: Wiley Subscription Services, Inc
References 2011
2010
2015; 72
2002; 1
2009
2004; 3
2016; 101
2007
2005
2004
2003
2002
2011; 5
2016; 99
2015; 28
2015; 29
2014; 2
2001
2000
2013; 13
2013; 12
2015; 41
2014; 38
2016; 40
2009; 7
2015
2013
2010; 3
2010; 7
2014; 33
2009; 15
e_1_2_6_10_1
e_1_2_6_31_1
e_1_2_6_30_1
Nurhayati SHC (e_1_2_6_33_1) 2011; 5
Zarei B (e_1_2_6_35_1) 2010; 7
e_1_2_6_19_1
e_1_2_6_13_1
e_1_2_6_36_1
e_1_2_6_14_1
e_1_2_6_11_1
e_1_2_6_34_1
e_1_2_6_12_1
e_1_2_6_17_1
e_1_2_6_18_1
e_1_2_6_39_1
e_1_2_6_15_1
e_1_2_6_38_1
e_1_2_6_16_1
e_1_2_6_37_1
e_1_2_6_21_1
e_1_2_6_20_1
e_1_2_6_41_1
e_1_2_6_40_1
e_1_2_6_9_1
e_1_2_6_8_1
e_1_2_6_5_1
e_1_2_6_4_1
e_1_2_6_7_1
e_1_2_6_6_1
e_1_2_6_25_1
e_1_2_6_24_1
Akhtar A (e_1_2_6_32_1) 2010; 3
e_1_2_6_3_1
e_1_2_6_23_1
e_1_2_6_2_1
e_1_2_6_22_1
e_1_2_6_29_1
e_1_2_6_28_1
e_1_2_6_27_1
e_1_2_6_26_1
References_xml – start-page: 1
  year: 2007
  end-page: 4
– volume: 15
  start-page: 193
  issue: 2
  year: 2009
  end-page: 207
  article-title: An unequal cluster‐based routing protocol in wireless sensor networks
  publication-title: Wireless Networks
– start-page: 604
  year: 2005
  end-page: 612
– volume: 3
  start-page: 366
  issue: 4
  year: 2004
  end-page: 379
  article-title: Heed: a hybrid, energy‐efficient, distributed clustering approach for ad hoc sensor networks
  publication-title: IEEE Trans Mob Comput
– year: 2005
– volume: 101
  start-page: 144
  year: 2016
  end-page: 157
  article-title: Icp: Instantaneous clustering protocol for wireless sensor networks
  publication-title: Comput Networks
– volume: 5
  start-page: 67
  issue: 2
  year: 2011
  end-page: 74
  article-title: A cluster based energy efficient location routing protocol in wireless sensor networks
  publication-title: Int J Comput Commun
– volume: 72
  start-page: 93
  year: 2015
  end-page: 106
  article-title: Smooth path construction and adjustment for multiple mobile sinks in wireless sensor networks
  publication-title: Comput Commun
– start-page: 448
  year: 2009
  end-page: 452
– volume: 12
  start-page: 48
  year: 2013
  end-page: 56
  article-title: A novel evolutionary approach for load balanced clustering problem for wireless sensor networks
  publication-title: Swarm Evol Comput
– volume: 29
  start-page: 760
  issue: 4
  year: 2015
  end-page: 771
  article-title: Sparse deployment scheme in mobile sensor networks with prioritized event area
  publication-title: Int J Commun Syst
– volume: 72
  start-page: 78
  year: 2015
  end-page: 92
  article-title: A link‐and hop‐constrained clustering for multi‐hop wireless sensor networks
  publication-title: Comput Commun
– volume: 38
  start-page: 2280
  issue: 7
  year: 2014
  end-page: 2289
  article-title: Modeling and optimization of energy efficient routing in wireless sensor networks
  publication-title: Appl Math Modell
– start-page: 48
  year: 2002
  end-page: 55
– start-page: 1848
  year: 2003
  end-page: 1852
– volume: 1
  start-page: 660
  issue: 4
  year: 2002
  end-page: 670
  article-title: An application‐specific protocol architecture for wireless microsensor networks
  publication-title: IEEE Trans Wireless Commun
– volume: 28
  start-page: 296
  issue: 2
  year: 2015
  end-page: 308
  article-title: Bod‐leach: broadcasting over duty‐cycled radio using leach clustering for delay/power efficient dissimilation in wireless sensor networks
  publication-title: Int J Commun Syst
– start-page: 2009
  year: 2001
  end-page: 2015
– volume: 2
  start-page: 75
  issue: 5
  year: 2014
  end-page: 103
  article-title: A review study on analytical estimation of optimal number of clusters in wireless sensor networks
  publication-title: Trans Networks Commun
– start-page: 2019
  year: 2004
  end-page: 2023
– start-page: 1
  year: 2010
  end-page: 4
– volume: 28
  start-page: 972
  issue: 5
  year: 2015
  end-page: 989
  article-title: Energy‐efficient multi‐level and distance‐aware clustering mechanism for wsns
  publication-title: Int J Commun Syst
– start-page: 284
  year: 2010
  end-page: 287
– start-page: 3005
  year: 2000
  end-page: 3014
– start-page: 915
  year: 2011
  end-page: 918
– start-page: 54
  year: 2011
  end-page: 49
– volume: 99
  start-page: 134
  year: 2016
  end-page: 161
  article-title: Multi‐objective optimization in sensor networks: optimization classification, applications and solution approaches
  publication-title: Comput Networks
– start-page: 1125
  year: 2002
  end-page: 1130
– volume: 7
  start-page: 32
  issue: 4
  year: 2010
  end-page: 36
  article-title: Novel cluster based routing protocol in wireless sensor networks
  publication-title: IJCSI Int J Comput Sci Issues
– start-page: 653
  year: 2015
  end-page: 658
– volume: 13
  start-page: 1498
  issue: 5
  year: 2013
  end-page: 1506
  article-title: Load‐balanced clustering algorithm with distributed self‐organization for wireless sensor networks
  publication-title: IEEE Sensors Journal
– volume: 33
  start-page: 127
  year: 2014
  end-page: 140
  article-title: Energy efficient clustering and routing algorithms for wireless sensor networks: particle swarm optimization approach
  publication-title: Eng Appl Artif Intell
– volume: 7
  start-page: 665
  issue: 4
  year: 2009
  end-page: 676
  article-title: A genetic algorithm based approach for energy efficient routing in two‐tiered sensor networks
  publication-title: Ad Hoc Networks
– volume: 41
  start-page: 177
  year: 2015
  end-page: 190
  article-title: Energy efficient fault tolerant clustering and routing algorithms for wireless sensor networks
  publication-title: Comput Electr Eng
– volume: 40
  start-page: 495
  year: 2016
  end-page: 506
  article-title: Ducf: Distributed load balancing unequal clustering in wireless sensor networks using fuzzy approach
  publication-title: Applied Soft Comput
– volume: 3
  start-page: 29
  issue: 1
  year: 2010
  end-page: 48
  article-title: Energy aware intra cluster routing for wireless sensor networks
  publication-title: Int J Hybrid Inf Technol
– volume: 28
  start-page: 1789
  issue: 11
  year: 2015
  end-page: 1804
  article-title: An efficient distributed routing protocol for wireless sensor networks with mobile sinks
  publication-title: Int J Commun Syst
– volume: 41
  start-page: 357
  year: 2015
  end-page: 367
  article-title: Energy‐aware routing algorithm for wireless sensor networks
  publication-title: Comput Electr Eng
– start-page: 91
  end-page: 98
– start-page: 267
  year: 2013
  end-page: 277
– ident: e_1_2_6_23_1
  doi: 10.1109/ICC.2003.1203919
– ident: e_1_2_6_21_1
  doi: 10.1109/AERO.2002.1035242
– ident: e_1_2_6_38_1
  doi: 10.1109/JSEN.2012.2227704
– ident: e_1_2_6_26_1
  doi: 10.1007/s11276-007-0035-8
– ident: e_1_2_6_17_1
  doi: 10.1002/dac.2669
– ident: e_1_2_6_18_1
– ident: e_1_2_6_27_1
  doi: 10.1016/j.adhoc.2008.04.003
– ident: e_1_2_6_30_1
  doi: 10.1109/ICEEE.2010.5661337
– ident: e_1_2_6_37_1
– ident: e_1_2_6_28_1
  doi: 10.1007/978-3-642-36071-8_21
– ident: e_1_2_6_14_1
  doi: 10.1109/IWCMC.2015.7289160
– ident: e_1_2_6_10_1
  doi: 10.1016/j.compeleceng.2014.07.010
– ident: e_1_2_6_19_1
  doi: 10.1109/IPDPS.2002.1016600
– ident: e_1_2_6_29_1
  doi: 10.1109/ICEEI.2009.5254694
– ident: e_1_2_6_2_1
  doi: 10.1109/ICC.2004.1312874
– ident: e_1_2_6_4_1
  doi: 10.1016/j.swevo.2013.04.002
– ident: e_1_2_6_25_1
– ident: e_1_2_6_5_1
  doi: 10.1016/j.engappai.2014.04.009
– ident: e_1_2_6_22_1
  doi: 10.1109/MOBHOC.2007.4428638
– ident: e_1_2_6_11_1
  doi: 10.1002/dac.2720
– ident: e_1_2_6_12_1
  doi: 10.1016/j.comcom.2015.05.009
– ident: e_1_2_6_41_1
  doi: 10.1016/j.apm.2013.10.044
– ident: e_1_2_6_36_1
  doi: 10.1109/AIMSEC.2011.6010559
– ident: e_1_2_6_6_1
  doi: 10.1016/j.comcom.2015.06.001
– ident: e_1_2_6_9_1
  doi: 10.1016/j.comnet.2016.01.015
– ident: e_1_2_6_8_1
  doi: 10.1002/dac.2954
– volume: 7
  start-page: 32
  issue: 4
  year: 2010
  ident: e_1_2_6_35_1
  article-title: Novel cluster based routing protocol in wireless sensor networks
  publication-title: IJCSI Int J Comput Sci Issues
– ident: e_1_2_6_24_1
– ident: e_1_2_6_40_1
  doi: 10.14738/tnc.25.488
– ident: e_1_2_6_3_1
  doi: 10.1016/j.compeleceng.2014.07.019
– ident: e_1_2_6_13_1
– volume: 3
  start-page: 29
  issue: 1
  year: 2010
  ident: e_1_2_6_32_1
  article-title: Energy aware intra cluster routing for wireless sensor networks
  publication-title: Int J Hybrid Inf Technol
– ident: e_1_2_6_39_1
  doi: 10.1016/j.asoc.2015.11.044
– ident: e_1_2_6_31_1
  doi: 10.1109/CMC.2010.147
– volume: 5
  start-page: 67
  issue: 2
  year: 2011
  ident: e_1_2_6_33_1
  article-title: A cluster based energy efficient location routing protocol in wireless sensor networks
  publication-title: Int J Comput Commun
– ident: e_1_2_6_34_1
  doi: 10.1016/j.comnet.2015.12.021
– ident: e_1_2_6_16_1
  doi: 10.1109/TWC.2002.804190
– ident: e_1_2_6_15_1
– ident: e_1_2_6_20_1
  doi: 10.1109/TMC.2004.41
– ident: e_1_2_6_7_1
  doi: 10.1002/dac.2785
SSID ssj0008265
Score 2.1265526
Snippet Summary Balancing the load among sensor nodes is a major challenge for the long run operation of wireless sensor networks. When a sensor node becomes...
Balancing the load among sensor nodes is a major challenge for the long run operation of wireless sensor networks. When a sensor node becomes overloaded, the...
Summary Balancing the load among sensor nodes is a major challenge for the long run operation of wireless sensor networks. When a sensor node becomes...
SourceID proquest
crossref
wiley
SourceType Aggregation Database
Enrichment Source
Index Database
Publisher
SubjectTerms Clustering
Clusters
Communications traffic
Computer networks
Congestion
Energy conservation
Energy consumption
Energy management
Gateways
hierarchical routing
Integer programming
linear program
Linear programming
Load balancing
Manufacturing
optimization
Remote sensors
Sensors
Traffic flow
Traffic models
Wireless networks
Wireless sensor networks
Title Optimal load balanced clustering in homogeneous wireless sensor networks
URI https://onlinelibrary.wiley.com/doi/abs/10.1002%2Fdac.3229
https://www.proquest.com/docview/1901465777
Volume 30
WOSCitedRecordID wos000405969000004&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: PRVWIB
  databaseName: Wiley Online Library Full Collection 2020
  customDbUrl:
  eissn: 1099-1131
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0008265
  issn: 1074-5351
  databaseCode: DRFUL
  dateStart: 19960101
  isFulltext: true
  titleUrlDefault: https://onlinelibrary.wiley.com
  providerName: Wiley-Blackwell
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1LS8NAEF609aAH32K1ygqip2Deu3ssraWHUkWs9Bb2FSykiTStv9_ZPNoKCoKX5LAzJMzOc5n9BqFb4RAoZUNmOVwLy6dSWEIw29LEUdKDdM4vZka-DcloRCcT9lx1VZq7MCU-xOrAzVhG4a-NgXORP6xBQxV8D7SRbaOmuVMFhVez99IfD1d-GBLnoO44DLzAqaFnbfeh5v0ejNYZ5maeWgSa_sF_fvEQ7VfpJe6U-nCEtnR6jPY2QAdP0OAJvMQMiJKMKyxMa6PUCstkaTATgARPU_yezTJQLZ0tc2zQjBNwiDiHkjeb47TsHM9P0bj_-NodWNU8BUtCUGdW7FIhqHakJ6gKbT-mNuNhGIPhxdrjSpBYKy1hITadpYIFYPKxDICJQx2lvTPUSLNUnyNsK6KoYA5XHizJULhQChF4cAolkvRa6L4WbCQrsHEz8yKJSphkNwLZREY2LXSzovwoATZ-oGnXexNVJpZHJpPxw4AQ0kJ3xS78yh_1Ol3zvvgr4SXadU34NgCadhs1FvOlvkI78nMxzefXlaJ9AbhS1vw
linkProvider Wiley-Blackwell
linkToHtml http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1LS8NAEB5qK6gH32K16gqip2Deu8FTUUvFWEWs9Bayj6BQE2msv9_ZPKqCguAlOewMCbPzXGa_ATjiFsVS1g8MK1bccJngBueBaShqSeFgOucWMyMfQzoYsNEouGvAWX0XpsSHmB24acso_LU2cH0gffqJGirxg6iOwRy0XN-hrAmti_veMJw5Ysycvbrl0HM8q8aeNe3Tmvd7NPpMMb8mqkWk6a386x9XYblKMEm31Ig1aKh0HZa-wA5uQP8W_cQLEo2zWBKumxuFkkSMpxo1AUnIc0qespcMlUtl05xoPOMxukSSY9GbTUha9o7nmzDsXT6c941qooIhMKwHRmIzzpmyhMOZ9E03YWYQ-36CppcoJ5acJkoqgQuJ7i3lgYdGnwgPmWKspJSzBc00S9U2EFNSyXhgxdLBJeFzG4shio-YYZEknDac1JKNRAU3rqdejKMSKNmOUDaRlk0bDmeUryXExg80nXpzosrI8kjnMq7vUUrbcFxsw6_80UX3XL93_kp4AAv9h5swCq8G17uwaOtgruE0zQ403yZTtQfz4v3tOZ_sV1r3AZyX2uw
linkToPdf http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1ZS8NAEB60FdEHb7GeK4g-hebeLD6JtSiWWkSlbyF7BIWYlKb19zubo1ZQEHxJHnaWhNk5vgmTbwDOuEWxlPWZYUWKG24guME5Mw1FLSkchHNuMTPypUf7_WA4ZIMFuKz_hSn5IWYf3LRnFPFaO7gaybj9xRoq8YFojmwRmq7HPLcBzc5j97k3C8SInL265dBzPKvmnjXtdr33ezb6gpjzQLXINN31f73jBqxVAJNclRaxCQsq3YLVOdrBbbh9wDjxjkJJFknCdXOjUJKIZKpZE1CEvKXkNXvP0LhUNs2J5jNOMCSSHIvebEzSsnc834Hn7s3T9a1RTVQwBKZ1ZsR2wHmgLOHwQPqmGwcmi3w_RteLlRNJTmMllcCFWPeWcuah08fCw00RVlLK2YVGmqVqD4gpqQw4syLp4JLwuY3FEMVLFGCRJJwWXNSaDUVFN66nXiRhSZRsh6ibUOumBaczyVFJsfGDzGF9OGHlZHmosYzre5TSFpwXx_Dr_rBzda3v-38VPIHlQacb9u769wewYutcrtk0zUNoTMZTdQRL4mPylo-PK6P7BF6U2mc
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=Optimal+load+balanced+clustering+in+homogeneous+wireless+sensor+networks&rft.jtitle=International+journal+of+communication+systems&rft.au=Souissi%2C+Manel&rft.au=Meddeb%2C+Aref&rft.date=2017-07-10&rft.issn=1074-5351&rft.eissn=1099-1131&rft.volume=30&rft.issue=10&rft_id=info:doi/10.1002%2Fdac.3229&rft.externalDBID=n%2Fa&rft.externalDocID=10_1002_dac_3229
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1074-5351&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1074-5351&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1074-5351&client=summon