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
Wireless Personal Communications
Erschienen in: Wireless Personal Communications 1/2020

13.01.2020

A Mathematical Model for Energy Efficient Secured CH Clustering Protocol for Mobile Wireless Sensor Network

verfasst von: D. Rajesh, T. Jaya

Erschienen in: Wireless Personal Communications | Ausgabe 1/2020

Einloggen

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

search-config
loading …

Abstract

Mobile Wireless sensor network encloses several minute sensors with miniature energy transceiver for collecting information in a diverse atmosphere. Network with restricted battery energy in sensor nodes is difficult task to design a proficient routing method to maximize network duration. In this research work a Mathematical Model for Energy Efficient Secured CH Clustering Protocol for Mobile Wireless Sensor Networks to maximize network duration. It includes cluster-head shifting method with in cluster that avoids frequent clustering and regularly scatters load with nodes. ME2SC methodology is evaluated with LEACH-C, E2R2 and DMSR. Simulation consequences demonstrate proposed approach diminishes energy expenditure and amplifies network duration.
Vorheriger Artikel A Compact Frequency Diversity Antenna with DGS and SRR Mode Switching for LTE and WLAN/WiMAX Wireless Systems
Nächster Artikel True Event-Driven and Fault-Tolerant Routing in Wireless Sensor Network

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

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+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 "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
Literatur
1.
Kamimura, J., Wakamiya, N., & Murata, M. (2006). A distributed clustering method for energy-efficient data gathering in sensor networks. International Journal of Mobile Computing,1(2), 113–119.
2.
Akyildiz, I. F., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002). Wireless sensor networks: A survey. Computer Networks,38(4), 393–422.CrossRef
3.
Wang, F., & Liu, J. (2011). Networked wireless sensor data collection: Issues, challenges, and approaches. IEEE Communications Surveys and Tutorials,13(4), 673–687.CrossRef
4.
Mainwaring, A., Polastre, J., Szewczyk, R., Culler, D., & Anderson, J. (2002). Wireless sensor networks for habitat monitoring. In Proceedings of the 1st ACM international workshop on wireless sensor networks and applications (pp. 88–97). Atlanta, Ga, USA.
5.
Zhow, W., Shi, W., Wang, X., & Wang, K. (2012). Adaptive sensor activation algorithm for target tracking in wireless sensor networks. International Journal of Distributed Sensor Networks,2012, 515906.CrossRef
6.
Durmus, Y., Ozgovde, A., & Ersoy, C. (2012). Distributed and online fair resource management in video surveillance sensor networks. IEEE Transactions on Mobile Computing,11(5), 835–848.CrossRef
7.
Modares, H., Salleh, R., & Moravejosharieh, A. (2011). Overview of security issues in wireless sensor networks. In Proceedings of the 2nd international conference on computational intelligence, modelling and simulation (CIMSim’11) (pp. 308–311).
8.
Kim, K. T., Yoo, H. K., Son, B. H., & Youn, H. Y. (2010). An energy efficient clustering scheme for self-organizing distributed wireless sensor networks. In Proceedings of the 10th IEEE international conference on computer and information technology (CIT’10) (pp. 1468–1473). Bradford, UK.
9.
Al-Karaki, J. N., & Kamal, A. E. (2004). Routing techniques in wireless sensor networks: A survey. IEEE Wireless Communications,11(6), 6–28.CrossRef
10.
Anastasi, G., Conti, M., Di Francesco, M., & Passarella, A. (2009). Energy conservation in wireless sensor networks: A survey. Ad Hoc Networks,7(3), 537–568.CrossRef
11.
Bajaber, F., & Awan, I. (2011). Adaptive decentralized re-clustering protocol for wireless sensor networks. Journal of Computer and System Sciences,77(2), 282–292.MathSciNetCrossRef
12.
Kim, K. T., Lyu, C. H., Moon, S. S., & Youn, H. Y. (2010). Tree-based clustering (TBC) for energy efficient wireless sensor networks. In Proceedings of the 24th IEEE international conference on advanced information networking and applications workshops (WAINA’10) (pp. 680–685). Perth, Australia.
13.
Culler, D., Estrin, D., & Srivastava, M. (2004). Overview of sensor networks. Computer,37(8), 41–49.CrossRef
14.
Li, I. -H., Liao, I. -E., & Wu, F. -N. (2011). Tlaeep: A traffic load-aware energy efficient protocol for wireless sensornetworks. Journal of Internet Technology,12(1), 27–34.
15.
Dhivya, M., Potnuru, A. K., & Sundarambal, M. (2011). Energy efficient routing protocol for wireless sensor networks. In Proceedings of the international conference on process automation, control and computing (PACC’11) (pp. 1–5). Coimbatore, India.
16.
Kim, K. T., & Youn, H. Y. (2012). An energy efficient MAC protocol employing dynamic threshold for wireless sensor networks. International Journal of Distributed Sensor Networks,2012, 304329.CrossRef
17.
Lim, S. J., & Park, M. S. (2012). Energy efficient chain formation algorithm for data gathering in wireless sensor networks. International Journal of Distributed Sensor Networks,2012, 843413.CrossRef
18.
Kochhal, M., Schwiebert, L., & Gupta, S. (2006). Self-organizing of wireless sensor networks. In J. Wu (Ed.), Handbook on theoretical and algorithmic aspects of sensor, adhoc wireless, and peer-to-peer networks (pp. 369–392). Boca Raton: Auerbach Publications.
19.
Jiang, Q., & Manivannan, D. (2004). Routing protocols for sensor networks. In Proceedings of the 1st IEEe consumer communications and networking conference (CCNC’04) (pp. 93–98).
20.
Singh, S. K., Singh, M. P., & Singh, D. K. (2010). Routing protocols in wireless sensor networks—a survey. International Journal of Computer Science and Engineering Survey,1(2), 63–83.CrossRef
21.
Wei, D., Jin, Y., Vural, S., Moessner, K., & Tafazolli, R. (2011). An energy-efficient clustering solution for wireless sensor networks. IEEE Transactions on Wireless Communications,10(11), 3973–3983.CrossRef
22.
Heinzelman, W. R., Chandrakasan, A., & Balakrishnan, H. (2000). Energy-efficient communication protocol for wireless microsensor networks. In Proceedings of the 33rd annual hawaii international conference on system sciences (HICSS-33’00) (p. 223). Maui, Hawaii.
23.
Buyanjargal, O., & Kwon, Y. (2010). Adaptive and energy efficient clustering algorithm for event-driven application in wireless sensor networks (AEEC). Journal of Networks,5(8), 904–911.
24.
Kim, K. T., Lee, B. J., Choi, J. H., Jung, B. Y., & Youn, H. Y. (2009) An energy efficient routing protocol in wireless sensor networks. In Proceedings of the international conference on computational science and engineering (CSE’09) (pp. 132–139). Vancouver, Canada.
25.
Noori, M., & Ardakani, M. (2011). Lifetime analysis of random event driven clustered wireless sensor networks. IEEE Transactions on Mobile Computing,10(10), 1448–1458.CrossRef
26.
Kim, K.T., & Youn, H.Y. (2005). Energy-Driven Adaptive Clustering Hierarchy (EDACH) for wireless sensor networks. In Proceedings of the embedded and ubiquitous computing workshops (EUC’05), vol. 3823 of lecture notes in computer science (pp. 1098–1107).
27.
Lindsey, S., & Raghavendra, C.S. (2002). PEGASIS: Power-efficient gathering in sensor information systems. In Proceedings of the IEEE aerospace conference (pp. 1–6).
28.
Heinzelman, W. B., Chandrakasan, A. P., & Balakrishnan, H. (2002). An application-specific protocol architecture for wireless microsensor networks. IEEE Transactions on Wireless Communications,1(4), 660–670.CrossRef
29.
Meng, T.H., & Rodoplu, V. (1998). Distributed network protocols for wireless communication. In Proceedings of the IEEE international symposium on circuits and systems (ISCAS’98) (pp. 600–603).
30.
Foss, S. G., & Zuyev, S. A. (1996). On a voronoi aggregative process related to a bivariate poisson process. Advances in Applied Probability,28(4), 965–981.MathSciNetCrossRef
31.
Chhaya, M. S., & Gupta, S. (1997). Performance modeling of asynchronous data transfer methods of IEEE 802.11 MAC protocol. Wireless Networks,3(3), 217–234.CrossRef
32.
Pahlavan, K., & Levesque, A. (1995). Wireless information networks. New York: Wiley.
33.
Ghelichi, M., Jahanbakhsh, S. K., & Sanaei, E. (2008). RCCT: Robust clustering with cooperative transmission for energy efficient wireless sensor networks. In Proceedings of the international conference on information technology: New generations (ITNG’08) (pp. 761–766). Las Vegas, Nev, USA.
34.
Sarma, H. K. D., Mall, R., & Kar, A. (2015). E2R2: Energy-efficient and reliable routing for mobile wireless sensor networks. In IEEE systems journal.
Metadaten
Titel
A Mathematical Model for Energy Efficient Secured CH Clustering Protocol for Mobile Wireless Sensor Network
verfasst von
D. Rajesh
T. Jaya
Publikationsdatum
13.01.2020
Verlag
Springer US
Erschienen in
Wireless Personal Communications / Ausgabe 1/2020
Print ISSN: 0929-6212
Elektronische ISSN: 1572-834X
DOI
https://doi.org/10.1007/s11277-020-07036-4

Weitere Artikel der Ausgabe 1/2020

Wireless Personal Communications 1/2020 Zur Ausgabe

OriginalPaper

Theoretical Analysis and Design of High-Stable-Gain Antenna with Ultrawide Band Capabilities and Suppressed Back Radiations

OriginalPaper

Technologies Assisting the Paradigm Shift from 4G to 5G

OriginalPaper

A Proposed Efficient Hybrid Precoding Algorithm for Millimeter Wave Massive MIMO 5G Networks

OriginalPaper

Energy Harvesting for Cooperative Cognitive Radio Networks

OriginalPaper

Performance Analysis of Novel Multi-band Monopole Antenna for Various Broadband Wireless Applications

OriginalPaper

Enhancement of the Dynamic Computation-Offloading Service Selection Framework in Mobile Cloud Environment

Neuer Inhalt

    Bildnachweise