More Web Proxy on the site http://driver.im/

article

Survey on clustering in heterogeneous and homogeneous wireless sensor networks

Authors:

Ali Shokouhi Rostami,

Marzieh Badkoobe,

Farahnaz Mohanna,

Hengameh Keshavarz,

Ali Asghar Hosseinabadi,

Arun Kumar SangaiahAuthors Info & Claims

The Journal of Supercomputing, Volume 74, Issue 1

Pages 277 - 323

https://doi.org/10.1007/s11227-017-2128-1

Published: 01 January 2018 Publication History

Abstract

In wireless sensor networks (WSNs), nodes have limited energy and cannot be recharged. In order to tackle this problem, clustering methods are employed to optimize energy consumption, gather data and also enhance the effective lifetime of the network. In spite of the clustering methods advantages, there are still some important challenges such as choosing a sensor as a cluster head (CH), which has a significant effect in energy efficiency. In clustering phase, nodes are divided into some clusters and then some nodes, named CH, are selected to be the head of each cluster. In typical clustered WSNs, nodes sense the field and send the sensed data to the CH, then, after gathering and aggregating data, CH transmits them to the Base Station. Node clustering in WSNs has many advantages, such as scalability, energy efficiency, and reducing routing delay. In this paper, several clustering methods are studied to demonstrate advantages and disadvantages of them. Among them, some methods deal with homogenous network, whereas some deals with heterogeneous. In this paper, homogenous and heterogeneous methods of clustering are specifically investigated and compared to each other.

References

[1]

Abbasi AA, Younis M (2007) A survey on clustering algorithms for wireless sensor networks. Comput Commun 30:2826---2841

Digital Library

[2]

Abdullah M, Eldin HN, Al-Moshadak T, Alshaik R, Al-Anesi I (2015) Density grid-based clustering for wireless sensors networks. In: International Conference on Communication, Management and Information Technology (ICCMIT2015), Procedia Computer Science, vol 65, pp 35---47

[3]

Agrawal DP, Manjeshwar A (2001) TEEN: a protocol for enhanced efficiency in wireless sensor networks. In: Proceedings of the 1st international workshop on parallel and distributed computing issues in wireless networks and mobile computing, pp 2009---2015, Apr 2001

Digital Library

[4]

Ahmed G, Zou J, Fareed MMS, Zeeshan M (2016) Sleep-awake energy efficient distributed clustering algorithm for wireless sensor networks. Comput Electr Eng 56:385---398

Digital Library

[5]

Akyildiz WS, Sankarasubramaniam Y, Cayirci E (2002) Wireless sensor networks: a survey. J Comput Netw 38:393---422

Digital Library

[6]

Albath J, Thakur M, Madria S (2013) Energy constraint clustering algorithms for wireless sensor networks. Ad Hoc Netw 11:2512---2525

Digital Library

[7]

Azizi N, Karimpour J, Seifi F (2012) HCTE: hierarchical clustering based routing algorithm with applying the two cluster heads in each cluster for energy balancing in WSN. Int J Comput Sci Issues 09:57---61

[8]

Bandyopadhyay S, Coyle E (2003) An energy efficient hierarchical clustering algorithm for wireless sensor networks. In: Proceedings of the 22nd Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM 2003), San Francisco, California, Apr 2003

[9]

Banerjee S, Khuller S (2001) A clustering scheme for hierarchical control in multi-hop wireless networks. In: Proceedings of 20th Joint Conference of the IEEE Computer and Communications Societies (INFOCOM' 01), Anchorage, AK, Apr 2001

[10]

Behzad M, Ge Y (2017) Performance optimization in wireless sensor networks: a novel collaborative compressed sensing approach. In: 31st International Conference on Advanced Information Networking and Applications (AINA), 2017 IEEE, pp 749---756

[11]

Beth HW (2000) Application specific protocol architectures for wireless networks. Doctor of Philosophy at Massachusetts Institute of Technology, Cambridge

[12]

Bore Gowda SB, Puttamadappa C, Mruthyunjaya HS, Babu NV (2012) Sector based multi-hop clustering protocol for wireless sensor networks. Int J Comput Appl 43(13):32---38

[13]

Boyinbode O, Le H, Mbogho A, Takizawa M, Poliah R (2010) A survey on clustering algorithms for wireless sensor networks. In: 13th International Conference on Network-Based Information Systems (NBiS), Cape Town, South Africa: {s.n.}, pp 358---364

Digital Library

[14]

Cenedese A, Luvisotto M, Michieletto G (2017) Distributed clustering strategies in industrial wireless sensor networks. IEEE Trans Ind Inform 13(1):228---237

[15]

Chatterjee M, Das SK, Turgut D (2002) WCA: a weighted clustering algorithm for mobile Ad Hoc networks. Clust Comput 05:193---204

Digital Library

[16]

Dahane A, Loukil A, Kechar B, Berrached N (2015) Energy efficient weighted clustering algorithm in wireless sensor networks. Mob Inf Syst 2015:1---18

[17]

Dai F, Wu J (2005) On constructing k-connected k-dominating set in wireless networks. In: Proceedings of the 19th IEEE international parallel and distributed processing symposium (IPDPS'05), Denver, Colorado, pp. 81a, Apr 2005

Digital Library

[18]

Demirbas M, Arora A, Mittal V (2004) FLOC: a fast local clustering service for wireless sensor networks, In: Proceedings of workshop on dependability issues in wireless ad hoc networks and sensor networks (DIWANS'04), Palazzo dei Congressi, Florence, Italy, June 2004

[19]

Deshpande VV, Patil ARB (2013) Energy efficient clustering in wireless sensor network using cluster of cluster heads. In: Proceedings of WOCN, pp 1---5

[20]

Ding P, Holliday J, Celik A (2005) Distributed energy efficient hierarchical clustering for wireless sensor networks, In: Proceedings of the IEEE International Conference on Distributed Computing in Sensor Systems (DCOSS'05), Marina Del Rey, CA, June 2005

Digital Library

[21]

Ding P, Holliday J, Celik A (2005) Distributed energy efficient hierarchical clustering for wireless sensor networks. In: Proceedings of the IEEE International Conference on Distributed Computing in Sensor Systems (DCOSS'05), pp 322---339, June 2005

Digital Library

[22]

Elbhiri B, Saadane R, Aboutajdine D (2009) Stochastic distributed energy-efficient clustering (SDEEC) for heterogeneous wireless sensor networks. ICGST-CNIR J 09(02):11---17

[23]

Erdal C, Ramesh G, Taieb Z, Mani S (2003) Wireless sensor networks. Comput Netw 43(15):417---419

Digital Library

[24]

Fahmy S, Younis O (2004) HEED: a hybrid energy-efficient distributed clustering approach for Ad Hoc sensor networks. IEEE Trans Mob Comput 3:366---379

[25]

Fan C, Duan H (2007) A distributed energy balance clustering protocol for heterogeneous wireless sensor networks. In: Wireless Communications, Networking and Mobile Computing, pp 2469---2473

[26]

Garcia F, Solano J, Stojmenovic I (2003) Connectivity based k-hopclustering in wireless networks. Telecommun Syst 22:205---220

Digital Library

[27]

Garg D, Kumar P (2017) Performance analysis on energy efficient protocols in wireless sensor networks. Int J Adv Res Comput Sci 8(5):1862---1869

[28]

Guizani S, Ci M, Sharif H (2007) Adaptive clustering in wireless sensor networks by mining sensor energy data. Comput Commun 30:2968---2975

Digital Library

[29]

Guo L-Q, Xie Y, Yang C-H, Jing Z-W (2010) Improve by LEACH by combining adaptive cluster head election and two-hop transmission. Int Conf Mach Learn Cybern (ICMLC) 4:1678---1683

[30]

Gupta G, Younis M (2003) Fault-tolerant clustering of wireless sensor networks. : Proceedings of the IEEE Wireless Communication and Networks Conference (WCNC 2003), New Orleans, Louisiana, Mar 2003

[31]

Gupta G, Younis M (2003) Fault-tolerant clustering of wireless sensor networks. In: Proceedings of the IEEE Wireless Communication and Networks Conference (WCNC 2003), New Orleans, Louisiana, vol 3, pp 1579---1584

[32]

Gupta G, Younis M (2003) Load-balanced clustering in wireless sensor networks. In: Proceedings of the International Conference on Communication (ICC 2003), Anchorage, Alaska, May 2003

[33]

Hai DT, Son LH, Le VT (2017) Novel fuzzy clustering scheme for 3D wireless sensor networks. Appl Soft Comput 54:141---149

Digital Library

[34]

Haibo Z, Yuanming W, Yanqi H, Guangzhong X (2008) A novel stable selection and reliable transmission protocol for clustered heterogeneous wireless sensor networks. In: computer communications, pp 1843---1849 (in press, corrected proof)

Digital Library

[35]

Han G, Zhang C, Jiang J, Yang X, Guizani M (2017) Mobile anchor nodes path planning algorithms using network-density-based clustering in wireless sensor networks. J Netw Comput Appl 85:64---75

Digital Library

[36]

Heinzelman WB, Chandrakasan AP, Balakrishnan H (2002) Application specific protocol architecture for wireless microsensor networks. In: IEEE transactions on wireless networking

[37]

Heinzelman WR, Chandrakasan A, Balakrishnan H (2002) An application-specific protocol architecture for wireless microsensor networks. IEEE Trans Wirel Commun 01:660---670

Digital Library

[38]

Heo S, Yi J, Cho Y, Hong J (2007) PEACH: power-efficient and adaptive clustering hierarchy protocol for wireless sensor networks. Comput Commun 30:2842---2852

Digital Library

[39]

Hu Y, Niu Y, Lam J, Shu Z (2017) An energy-efficient adaptive overlapping clustering method for dynamic continuous monitoring in WSNs. IEEE Sens J 17(3):834---847

[40]

Hu X, Li Y, Xu H (2017) Multi-mode clustering model for hierarchical wireless sensor network. Phys A Stat Mech Appl 469:665---675

[41]

Ilker Oyman E, Ersoy C (2004) Multiple sink network design problem inlarge scale wireless sensor networks. In: Proceedings of the IEEE International Conference on Communications (ICC 2004), vol 6, pp 3663---3667

[42]

Jabeur N (2016) A firefly-inspired micro and macro clustering approach for wireless sensor networks. In: The 7th International Conference on Emerging Ubiquitous Systems and Pervasive Networks (EUSPN 2016), Procedia Computer Science, vol 98, pp. 132---139

Digital Library

[43]

Kang SH, Nguyen T (2012) Distance based thresholds for cluster head selection in wireless sensor networks. IEEE Commun Lett 16(9):1396---1399

[44]

Krishnamachari B, Estrin D, Wicker S (2002) Modeling data centric routing in wireless sensor networks, In: Proceedings of IEEE INFOCOM, New York, NY, June 2002

[45]

Kuila P, Jana PK (2014) Energy efficient clustering and routing algorithms for wireless sensor networks: particle swarm optimization approach. Eng Appl Artif Intell 30:127---140

[46]

Kumar D, Aseri TC, Patel RB (2009) EEHC: energy efficient heterogeneous clustered scheme for wireless sensor networks. Comput Commun 32:662---667

Digital Library

[47]

Kumar SS, MP S, DsssK S (2010) A survey of energy-efficient hierarchical cluster-based routing in wireless sensor networks. Int J Adv Netw Appl 02:570---580

[48]

Kumarawadu P, Dechene DJ, Luccini M, Sauer A (2008) Algorithms for node clustering in wireless sensor networks: a survey. In: Information and automation for sustainability, pp 295---300, Dec 2008

[49]

Lan KC, Wei M (2017) A compressibility-based clustering algorithm for hierarchical compressive data gathering. IEEE Sens J 17(8):2550---2562

[50]

Laurence YZ, Yang T, Chen J (2010) RFID and sensor networks. AUERBACH Pub, CRC Press, Lodon

[51]

Li B, Gong L, Wang S, Zhou X (2008) Multihop routing protocol with unequal clustering for wireless sensor networks. In: International colloquium on computing, communication, control, and management (ISECS2008), pp 552---556

Digital Library

[52]

Lindsey S, Raghavendra CS (2002) PEGASIS: power efficient gathering in sensor information systems, In: Proceedings of the IEEE Aerospace Conference, Big Sky, Montana, Mar 2002

[53]

Lindsey S, Raghavendra CS, Sivalingam K (2001) Data gathering in sensor networks using the energy*delay metric. In: Proceedings of the IPDPS Workshop on Issues in Wireless Networks and Mobile Computing, San Francisco, CA, Apr 2001

Digital Library

[54]

Li X, Tao X, Mao G (2017) Unbalanced expander based compressive data gathering in clustered wireless sensor networks. IEEE Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission, vol 5, pp 7553---7566

[55]

Liu Z, Zheng Q, Xue L, Guan X (2012) A distributed energy-efficient clustering algorithm with improved coverage in wireless sensor networks. Future Gener Comput Syst 28(05):780---790

Digital Library

[56]

Liu X, Li J, Dong Z, Xiong F (2017) Joint design of energy-efficient clustering and data recovery for wireless sensor networks. Exploiting the benefits of interference in wireless networks: energy harvesting and security, pp 3646---3656

[57]

Li C, Ye M, Chen G, Wu J (2005) An energy efficient unequal clustering mechanism for wireless sensor networks. In: Proceedings of 2005 IEEE International Conference on Mobile Adhoc and Sensor Systems Conference (MASS05), Washington, D.C. : {s.n.}, pp 604---611, Nov 2005

[58]

Loscri V, Morabito G, Marano S (2005) A two-level hierarchy for low-energy adaptive clustering hierarchy. Proc Veh Technol Conf 03:1809---1813

[59]

Low CP, Fang C, Ng JM, Ang YH (2008) Efficient load-balanced clustering algorithms for wireless sensor networks. Comput Commun 31:750---759

Digital Library

[60]

Marin-Perianu RS, Scholten J, Havinga PJM, Hartel PH (2008) Cluster-based service discovery for heterogeneous wireless sensor networks. Int J Parallel Emerg Distrib Syst 04:325---346

Digital Library

[61]

Min R, Bhardwaj M, Cho S, Shih E, Sinha A, Wang A, Chandrakasan A (2001) Low power wireless sensor networks. In: Proceedings of International Conference on VLSI Design, pp 205---210

Digital Library

[62]

Mirza MA, Garimella RM (2009) PASCAL: power aware sectoring based clustering algorithm for wireless sensor networks. The International Conference on Information Networking (ICOIN), Chiang Mai, Thailand, January 2009

Digital Library

[63]

Mohd O (2017) Dynamic relocation of mobile BSin wireless sensor networks using a cluster-based harmony search algorithm. Inf Sci 385---386:76---95

Digital Library

[64]

Narottam Chand VK, Soni S (2011) A survey on clustering algorithms for heterogeneous wireless sensor networks. Int. J. Adv Netw Appl 02:745---754

[65]

Nayak P, Vathasavai B (2017) Energy efficient clustering algorithm for multi hop wireless sensor network using type-2 fuzzy logic. IEEE Sens J 17(14):4492---4499

[66]

Ouchitachen H, Hair A, Idrissi N (2017) Improved multi-objective weighted clustering algorithm in wireless sensor network. Egypt Inform J 18:45---54

[67]

Pal V, Yogita, Singh G, Yadav RP (2015) Effect of Heterogeneous nodes location on the performance of clustering algorithms for wireless sensor networks. In: 3rd International Conference on Recent Trends in Computing 2015 (ICRTC-2015), vol 57, pp 1042---1048

[68]

Phanish D, Coyle EJ (2017) Application-based optimization of multi-level clustering in ad hoc and sensor networks. IEEE Trans Wirel Commun 16(7):4460---4475

Digital Library

[69]

Prasad D, Metta VP (2017) An improvement of energy efficiency clustering protocol by using K-Means algorithm. Int Res J Eng Technol (IRJET) 4(6):2486---2489

[70]

QIAN KAI-GUO (2013) A clustering routing protocol for sensor network based on distance probability. IEEE, pp 113---116

[71]

Rabeay JM, Ammer MJ, da Silva JL, Patel D, Roundry S (2000) PicoRadio supports ad hoc ultra-low power wireless networking. IEEE Comput Mag 33:42---48

Digital Library

[72]

Ram B, Chand N, Gupta P, Chauhan S (2011) A new approach layered architecture based a new approach layered architecture based. Int J Comput Appl 15(01):53---55

[73]

RS Lindsey, CS (2002) PEGASIS: Power-efficient gathering in sensor information system. In: Proceedings IEEE Aerospace Conference, Big Sky, MT: {s.n.}, 03, pp 1125---1130

[74]

Sabor N, Abo-Zahhad M, Sasaki S, Ahmed SM (2016) An unequal multi-hop balanced immune clustering protocol for wireless sensor networks. Appl Soft Comput 43:372---389

Digital Library

[75]

Sandeep DN, Kumar V (2017) Review on clustering, coverage and connectivity in underwater wireless sensor networks: a communication techniques perspective, IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission, pp 1---22

[76]

Shokouhifar M, Jalili A (2017) Optimized sugeno fuzzy clustering algorithm for wireless sensor networks. Eng Appl Artif Intell 60:16---25

Digital Library

[77]

Singh Mann P, Singh S (2017) Energy efficient clustering protocol based on improved metaheuristic in wireless sensor networks. J Netw Comput Appl 83:40---52

Digital Library

[78]

Singh J, kumar R, Mishra AK (2015) Clustering algorithms for wireless sensor networks: a review. In: 2nd International Conference on Computing for Sustainable Global Development (INDIACom), pp 637---642

[79]

Smaragdakis G, Matta I, Bestavros A (2004) SEP: a stable election protocol for clustered heterogeneous wireless sensor networks. In: Proceedings of the international workshop on SANPA, pp 251---261

[80]

Sohn I, Lee J, Lee SH (2016) Low-energy adaptive clustering hierarchy using affinity propagation for wireless sensor networks. IEEE Commun Lett 20(3):558---561

[81]

Subramanian L, Katz RH (2000) An architecture for building self configurable systems, In: Proceedings of IEEE/ACM workshop on mobile ad hoc networking and computing, Boston, MA, Aug 2000

Digital Library

[82]

Tandon R, Dey B, Nandi S (2013) Weight based clustering. In: Wireless sensor networks, IEEE, pp 1---5

Digital Library

[83]

Tyagi S, Gupta SK (2013) EHE-LEACH: Enhanced heterogeneous LEACH protocol for lifetime enhancement of wireless SNs. In: International Conference on Advances in Computing, Communications and Informatics (ICACCI), pp 1485---1490

[84]

Varma S, Nigam N, Tiwary US (2008) BSHeterogeneous wireless sensor network using clustering. In: Wireless communication and sensor networks, WCSN, pp 1---6

[85]

Venkateswarlu MK, Kandasamy A, Chandrasekaran K (2016) An energy-efficient clustering algorithm for edge-based wireless sensor networks. In: Twelfth International Multi-Conference on Information Processing-2016 (IMCIP-2016), Procedia Computer Science, vol 89, pp 7---16

[86]

Wang A, Yang D, Sun D (2012) A clustering algorithm based on energy information and cluster heads expectation for wireless sensor network. Des Anal Wirel Syst Emerg Comput Archit Syst 38:662---671

Digital Library

[87]

Wang K, Abu AS, Little TDC, Basu P (2005) Attribute-based clustering for information dissemination in wireless sensor networks, In: Proceeding of 2nd Annual IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks (SECON 2005), Santa Clara, CA, Sept 2005

[88]

Woungang SMI, Misra SC (2009) Guide to wireless sensor networks. Springer, London

Digital Library

[89]

Yadav S, Kumar V (2017) Optimal clustering in underwater wireless sensor networks: acoustic, EM and FSO Communication compliant technique, IEEE Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission, pp 1---16

[90]

Ye M, Li C, Chen G, Wu J (2006) An energy efficient clustering scheme in wireless sensor networks. Ad Hoc Sensor Wirel Netw 1:1---21

[91]

Young H, Wan Y, Haosong G, Zeng H (2009) A partition based LEACH algorithm. In IEEE Ninth International Conference on Computer and Information Technology, pp 40---45

Digital Library

[92]

Younis O, Fahmy S (2004) HEED: a hybrid, energy-efficient, distributed clustering approach for Ad Hoc sensor networks. IEEE Trans Mob Comput 3(4):366---379

[93]

Yueyang L, Hong J, Guangxin Y (2006) An energy-efficient PEGASIS-based enhanced algorithm in wireless sensor networks. China Communications Technology Forum

[94]

Zhu Q, Qing L, Wang M (2006) Design of a distributed energy-efficient clustering algorithm for heterogeneous wireless sensor networks. Comput Commun 29:2230---2237

Digital Library

Cited By

Siddiq AGhazwani Y(2024)Hybrid Optimized Deep Neural Network-Based Intrusion Node Detection and Modified Energy Efficient Centralized Clustering Routing Protocol for Wireless Sensor NetworkIEEE Transactions on Consumer Electronics10.1109/TCE.2024.343097470:3(6303-6313)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1109/TCE.2024.3430974
S KRao DJain ASharma SPandit SPandey R(2024)Effectual Energy Optimization Stratagems for Wireless Sensor Network Collections Through Fuzzy-Based Inadequate ClusteringSN Computer Science10.1007/s42979-024-03377-05:8Online publication date: 6-Nov-2024
https://dl.acm.org/doi/10.1007/s42979-024-03377-0
Saemi BHalataei FAhmadi RAshkaran AMirkamali SHosseinabadi A(2024)Improving the quality of real-time data transmission service in VANETS by balancing the load on road side unitsCluster Computing10.1007/s10586-024-04317-627:5(6471-6487)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1007/s10586-024-04317-6
Show More Cited By

Survey on clustering in heterogeneous and homogeneous wireless sensor networks
1. General and reference
  1. Cross-computing tools and techniques
2. Networks
  1. Network services
  2. Network types

Recommendations

A Survey on Analytical Modeling and Mitigation Techniques for the Energy Hole Problem in Corona-Based Wireless Sensor Network

Wireless sensor networks (WSNs) have attracted much attention in recent years. In the many-to-one WSNs, the nodes located around the sink relay the data from other sensor nodes, which depletes their energy more quickly, resulting in energy holes and hot ...
Low-Energy Adaptive Unequal Clustering Protocol Using Fuzzy c-Means in Wireless Sensor Networks

Clustering technique in wireless sensor networks incorporate proper utilization of the limited energy resources of the deployed sensor nodes with the highest residual energy that can be used to gather data and send the information. However, the problem ...
Cluster-Head Restricted Energy Efficient Protocol (CREEP) for Routing in Heterogeneous Wireless Sensor Networks

A magnanimous number of collaborative sensor nodes make up a Wireless Sensor Network (WSN). These sensor nodes are outfitted with low-cost and low-power sensors. The routing protocols are responsible for ensuring communications while considering the ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image The Journal of Supercomputing

The Journal of Supercomputing Volume 74, Issue 1

January 2018

525 pages

ISSN:0920-8542

Issue’s Table of Contents

Copyright © Copyright © 2018 Springer Science+Business Media, LLC, part of Springer Nature.

Publisher

Kluwer Academic Publishers

United States

Publication History

Published: 01 January 2018

Author Tags

Qualifiers

Article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

40
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 11 Feb 2025

Other Metrics

View Author Metrics

Citations

Cited By

Siddiq AGhazwani Y(2024)Hybrid Optimized Deep Neural Network-Based Intrusion Node Detection and Modified Energy Efficient Centralized Clustering Routing Protocol for Wireless Sensor NetworkIEEE Transactions on Consumer Electronics10.1109/TCE.2024.343097470:3(6303-6313)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1109/TCE.2024.3430974
S KRao DJain ASharma SPandit SPandey R(2024)Effectual Energy Optimization Stratagems for Wireless Sensor Network Collections Through Fuzzy-Based Inadequate ClusteringSN Computer Science10.1007/s42979-024-03377-05:8Online publication date: 6-Nov-2024
https://dl.acm.org/doi/10.1007/s42979-024-03377-0
Saemi BHalataei FAhmadi RAshkaran AMirkamali SHosseinabadi A(2024)Improving the quality of real-time data transmission service in VANETS by balancing the load on road side unitsCluster Computing10.1007/s10586-024-04317-627:5(6471-6487)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1007/s10586-024-04317-6
Ashok Kumar MSaravanan K(2023)Enhancing energy utilization for high power node multicasting in wireless sensor networksJournal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.3233/JIFS-22353645:3(4753-4766)Online publication date: 1-Jan-2023
https://dl.acm.org/doi/10.3233/JIFS-223536
Mughal FHe JZhu NMallah GQiao ZHaider AHussain SHussain MZardari Z(2022)A new Asymmetric Link Quality Routing protocol (ALQR) for heterogeneous WSNsMicroprocessors & Microsystems10.1016/j.micpro.2022.10461793:COnline publication date: 1-Sep-2022
https://dl.acm.org/doi/10.1016/j.micpro.2022.104617
Al-Sulaifanie AAl-Sulaifanie BBiswas S(2022)Recent trends in clustering algorithms for wireless sensor networksComputer Communications10.1016/j.comcom.2022.05.006191:C(395-424)Online publication date: 1-Jul-2022
https://dl.acm.org/doi/10.1016/j.comcom.2022.05.006
Manoharan J(2022)A Novel Load Balancing Aware Graph Theory Based Node Deployment in Wireless Sensor NetworksWireless Personal Communications: An International Journal10.1007/s11277-022-09994-3128:2(1171-1192)Online publication date: 13-Sep-2022
https://dl.acm.org/doi/10.1007/s11277-022-09994-3
Al-Qamaji AAtakan B(2022)Event Distortion-Based Clustering Algorithm for Energy Harvesting Wireless Sensor NetworksWireless Personal Communications: An International Journal10.1007/s11277-021-09316-z123:4(3823-3843)Online publication date: 1-Apr-2022
https://dl.acm.org/doi/10.1007/s11277-021-09316-z
Javadpour A(2022)An Optimize-Aware Target Tracking Method Combining MAC Layer and Active Nodes in Wireless Sensor NetworksWireless Personal Communications: An International Journal10.1007/s11277-019-06425-8108:2(711-728)Online publication date: 10-Mar-2022
https://dl.acm.org/doi/10.1007/s11277-019-06425-8
Edla DLipare AParne S(2022)Load balanced cluster formation to avoid energy hole problem in WSN using fuzzy rule-based systemWireless Networks10.1007/s11276-022-03200-929:3(1299-1310)Online publication date: 1-Dec-2022
https://dl.acm.org/doi/10.1007/s11276-022-03200-9
Show More Cited By

View Options

View options

Figures

Tables

Media

View Issue’s Table of Contents