Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
Mobile Networks and Applications
Erschienen in: Mobile Networks and Applications 2/2019

05.09.2017

Development of Fuzzy based Energy Efficient Cluster Routing Protocol to Increase the Lifetime of Wireless Sensor Networks

verfasst von: S. Balaji, E. Golden Julie, Y. Harold Robinson

Erschienen in: Mobile Networks and Applications | Ausgabe 2/2019

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

Wireless Sensor Network is a wide area monitoring tools supporting for Scientific Research, Low-power microscopic sensors. WSN uses limited resource memory, computation power, bandwidth, and energy. The Cluster Routing protocol is the best methodologies for energy efficiency in the wireless sensor network. Cluster Routing Protocols are used to form a cluster creation on the selection of cluster head (CH). Then the data packets are sending from one CH to another CH and finally data packets are send to the base station. CHs are selected by using the setup phase. This system proposed a multi hop transmission, where the data packets are send from one hop to another hop. Finally these data packets are transmitted to the base station. To transmit the packets from source sensor to wireless sensor network base station via the cluster head, using the fuzzy logic type 1with three parameters such as trust factor and distance. The fuzzy logic predicts the nodes, which is having high trust factor, and near to the base station CH will be selected as best forwarder by using Type 1 fuzzy logic. It will direct to increase the life time of network plus reduce the overhead of network.
Vorheriger Artikel Fuzzy Trust Approach for Detecting Black Hole Attack in Mobile Adhoc Network
Nächster Artikel Influence of Krylov subspace in Graph Isomorphism for Mobile Networks

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Weitere Produktempfehlungen anzeigen
Literatur
1.
Akyildiz IF, Su W, Sankarasubramaniam Y et al (2002) A survey on sensor networks. IEEE Commun Mag 40(8):102–114CrossRef
2.
S. Lindsey and C. S. Raghavendra, “PEGASIS: Power-efficient Gathering in Sensor Information Systems”, Parallel and Distributed Systems, vol. 9, no. 924, (2002)
3.
Liu X (2012) A survey on clustering routing protocols in wireless sensor networks. Sensors 12(8):11113–11153CrossRef
4.
Ali MS, Dey T, and Biswas R (2008) ALEACH: Advanced LEACH routing protocol for wireless microsensor networks. Int Conf Electr Comput Eng ICECE 909–914
5.
Harold RY, Rajaram M, Golden JE, Balaji S (2016) Dominating set algorithm and trust evaluation scheme for secured cluster formation and data transferring. World Acad Sci Eng Technol Int J Comput Electr Autom Control Inf Eng 10:388–393
6.
Harold Robinson Y, Rajaram M, Golden Julie E, Balaji S (2016) “Tree based data fusion clustering routing algorithm for illimitable network administration in wireless sensor network”, world academy of science, engineering and technology. Int J Comput Electr Autom Control Inf Eng 10(6):1123–1130
7.
8.
Arbab E, Aghazarian V, Hedayati A, Ghazanfari Motlagh N (2012) A LEACH-based clustering algorithm for optimizing energy consumption in wireless sensor networks” 2nd international Conference on computer science and information technology (ICCSIT'2012) Singapore
9.
Manjeshwar DP, Agrawal E (2001) TEEN: A routing protocol for enhanced efficiency in wireless sensor networks, In Proceedings of the 15th International Parallel and Distributed Processing Symposium (IPDPS). San Francisco,CA, USA, pp 2009–2015
10.
Karnik, N. N., & Mendel, J. M. (1998). An introduction to type-2 fuzzy logic systems. In proceeding of IEEE international Conference on fuzzy systems (FUZZ) (Vol. 2, pp. 915–920)
11.
Harold RY, Golden JE, Balaji S (2016) Bandwidth and delay aware routing protocol with scheduling algorithm for multi hop mobile ad hoc networks. World Acad Sci Eng Technol Int J Comput Electr Autom Control Inf Eng 10(8):1512–1521
12.
Kumar SS, Kumar MN, Sheeba VS (2011) Fuzzy logic based energy efficient hierarchical clustering in wireless sensor networks. Int J Res Rev Wirel Sens Netw (IJRRWSN) 1(4):53–57
13.
Liang QL, Mendel JM (2000) Equalization of nonlinear time-varying channels using type-2fuzzy adaptive filters. IEEE Trans Fuzzy Syst 8(5):551–563CrossRef
14.
Kulkarni RV, Forster A, Venayagamoorthy GK (2011) Computational intelligence in wireless sensor networks: a survey. IEEE Commun Surv Tutorials 13(1):68–96CrossRef
15.
16.
Baranidharan B, Srividhya S, Santhi B (2014) Energy efficient hierarchical unequal clustering in wireless sensor networks. Indian J Sci Technol 7(3):301–305
17.
Heizelman W, Chandrakasan A, Balakrishnan H (2000) Energy-efficient communication protocol for wireless microsensor networks. In Proceeding of the 33rd annual Hawaii international Conference on system sciences (HICSS) (pp. 3005–3014). Maui, HI
18.
Ye M, Li C, Chen G, Wu J (2005) EECS: an energy efficient cluster scheme in wireless sensor networks. Proceedings of IEEE international workshop on strategies for energy efficiency in ad hoc and sensor networks. Phoenix, Arizona
19.
Balaji S, Rajaram M (2014) “EUDIS-An Encryption Scheme for User-Data Security in Public Networks”, World Academy of Science, Engineering and Technology. Int J Comput Inf Syst Control Eng 8(11):1825–1830
20.
Shen B, Zhang SY, Zhong YP (2006) Wireless sensor network clustering routing protocol. J Softw 17(7):1588–1600CrossRefMATH
21.
Shurman MM, Alomari ZA, and Mhaidat KM (2014) An Efficient Billing Scheme for Trusted Nodes Using Fuzzy Logic in Wireless Sensor Netw Wireless Eng Technol 5:62-73
22.
Castillo O, Melin P (2008) Type-2 fuzzy logic: theory and applications. Springer, Berlin, HeidelbergMATH
23.
Singh AK, Goutele S, Verma S, Purohit N (2012) An energy efficient approach for clustering in WSN using fuzzy logic. Int J Comput Appl 44(18):8–12
24.
O. Younis and S. Fahmy, “HEED: A Hybrid, Energy-efficient”, Distributed Clustering Approach for Ad Hoc Sensor Networks. Mobile Compu, vol. 3, no. 366, (2004)
25.
ArunSamPaul Thomas G, Karthik Ganesh R, Kandasamy A, Balaji S, Harold Robinson Y (2011) An advanced controlled-flooding routing with Group Organization for Delay Tolerant Networks using A-SMART. Emerging trends in electrical and computer technology (ICETECT), 978-1-4244-7926-9/11, IEEE
26.
Harold Robinson Y, Rajaram M, Golden Julie E, Balaji S (2016) “TBOR: tree based opportunistic routing for mobile ad hoc networks”, World Academy of Science, Engineering and Technology. Int J Comput Electr Autom Control Inf Eng 10(6):1115–1122
27.
28.
29.
30.
Mendel JM (2001) Uncertain rule-based fuzzy logic system: introduction and new directions. Prentice Hall PTR, UpperSaddle RiverMATH
31.
Balaji S, Julie EG, Rajaram M, Robinson YH (2016) Fuzzy based particle swarm optimization routing technique for load balancing in wireless sensor networks, World Academy of Science, Engineering and Technology. Int J Comput Electr Autom Control Inf Eng 10(7):1384–1393
32.
Indranil G, Denis R, Srinivas SS (2005) Cluster-head election using fuzzy logic for wireless sensor networks. In Proceedings of the 3rd annual communication networks and services research Conference (CNSR) (pp. 255–260)
33.
34.
Karnik NN, Mendel JM, Liang QL (1999) Type-2 fuzzy logic systems. IEEE Trans Fuzzy Syst 7(6):643–658CrossRef
35.
Kim JM, Park SH, Han YJ, Chung TM (2008) CHEF: cluster-head election mechanism using fuzzy logic in wireless sensor networks. In proceedings of the international Conference on advanced communication technology (ICACT) (pp. 654–659)
36.
Yang K (2014) Wireless sensor networks." Principles, design and applications (2014).Zhang, Degan, et al. "An energy-balanced routing method based on forward-aware factor for wireless sensor networks. IEEE Trans Ind Inf 10(1):766–773CrossRef
37.
Wang, H, Wang J (2014) An effective image representation method using kernel classification." Tools with Artificial Intelligence (ICTAI), 2014 I.E. 26th international Conference on. IEEE (pp. 853-858)
38.
Tuia D, Camps-Valls G, Matasci G, Kanevski M (2010) Learning relevant image features with multiple-kernel classification. IEEE Trans Geosci Remote Sens 48(10):3780–3791CrossRef
39.
Wang H, Wang J (2014) An effective image representation method using kernel classification. In tools with artificial intelligence (ICTAI), 2014 I.E. 26th international Conference on (pp. 853-858). IEEE
40.
Qi C, Zhou Z, Sun Y, Song H, Hu L, Wang Q (2017) Feature selection and multiple kernel boosting framework based on pso with mutation mechanism for hyperspectral classification. Neurocomputing 220:181–190
41.
Pardo A, Real E, Krishnaswamy V, López-Higuera JM, Pogue BW, Conde OM (2017) Directional kernel density estimation for classification of breast tissue spectra. IEEE Trans Med Imaging 36(1):64–73CrossRef
42.
Zhao F, Guibas L (2004) Wireless sensor networks:an information processing approach. Publishers –San Francisco, Morgan Kaufmann
43.
44.
Chattwejee M, Das SK, Turgut D (2002) WCA: a weighted clustering algorithm for mobile ad hoc networks. Clust Comput 5:193–204CrossRef
45.
Lee C, Jeong T FRCA: A Fuzzy Relevance-Based Cluster Head Selection Algorithm for Wireless Mobile Ad-Hoc Sensor Networks. Division of Electronic Engineering, Chonbuk National University, Jeonbuk, Korea
46.
Aslam M, Rasheed MB, Shah T, Rahim A, Khan ZA, Qasim U, Qasim MW, Hassan A, Khan A, Javaid N Energy optimization and Performance Analysis of Cluster Based Routing Protocols Extended from LEACH for WSNs
47.
Klir G–J, Yuan B (1995) Fuzzy Sets and Fuzzy Logic: Theory and Applications. Prentice Hall, New JerseyMATH
48.
Mahmoud MM, Lin X, Shen X et al (2015) Secure and reliable routing protocols for heterogeneous multihop wireless networks. IEEE Trans Parallel Distrib Syst 26(4):1140–1153CrossRef
49.
Ayyasamy A, Venkatachalapathy K (2012) Increased throughput for load based channel aware routing in MANETs with reusable paths. Int J Comput Appl 40(2):20–23
50.
Ayyasamy A, Venkatachalapathy K (2015) Context aware adaptive fuzzy based QoS routing scheme for streaming services over MANETs. Wirel Netw 21(2):421–430CrossRef
Metadaten
Titel
Development of Fuzzy based Energy Efficient Cluster Routing Protocol to Increase the Lifetime of Wireless Sensor Networks
verfasst von
S. Balaji
E. Golden Julie
Y. Harold Robinson
Publikationsdatum
05.09.2017
Verlag
Springer US
Erschienen in
Mobile Networks and Applications / Ausgabe 2/2019
Print ISSN: 1383-469X
Elektronische ISSN: 1572-8153
DOI
https://doi.org/10.1007/s11036-017-0913-y

Weitere Artikel der Ausgabe 2/2019

Mobile Networks and Applications 2/2019 Zur Ausgabe

OriginalPaper

A Method for Power Saving in Dense WiFi Networks

EditorialNotes

Editorial: Advances in Green Communications and Networking

OriginalPaper

Cost optimization of PV-Diesel Systems in Nanogrid Using L J Cuckoo Search and its Application in Mobile Towers

OriginalPaper

Target Aucourant Data Dissemination by Collaboratory Sensing in IOT Environment

OriginalPaper

Particle Swarm Based Resource Optimized Geographic Routing for Improved Network Lifetime in MANET

OriginalPaper

Cooperative Cognitive Non-Orthgonal Multiple Access Under Unreliable Backhaul Connections

Neuer Inhalt

    Bildnachweise