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 2/2015

01.03.2015

Energy and Coverage-Aware Routing Algorithm for Wireless Sensor Networks

verfasst von: Tarachand Amgoth, Prasanta K. Jana

Erschienen in: Wireless Personal Communications | Ausgabe 2/2015

Einloggen

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

search-config
loading …

Abstract

One of the objectives of the wireless sensor networks (WSNs) is to preserve the coverage of the target area by the sensor nodes to a maximum possible time. Therefore, designing energy efficient algorithm to maximize the coverage lifetime is a central problem to a large-scale WSN. In this paper, we propose a new distributed, energy and coverage aware routing algorithm called DECAR to achieve this goal. In the proposed algorithm, sensor nodes are grouped into clusters of unequal size to minimize the hot spot problem during the process of data routing towards sink. We devise a simple and elegant method for selecting next hop cluster heads (CHs) to relay the aggregated data by considering the overlapping of their sensing areas. In addition to this, the proposed method tries to balance the relaying load of the CHs in order to equalize their energy consumption. Simulation results show that the proposed DECAR algorithm achieves better coverage lifetime than the existing approaches.
Vorheriger Artikel A New Low-Profile Inverted A-Shaped Patch Antenna for Multi-band Operations
Nächster Artikel Bit-Clusters Trellis Search Based Iterative MIMO Detection Algorithm

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.
Anastasi, G., Conti, M., Francesco, M. D., & Passarella, A. (2009). Energy conservation in wireless sensor networks: A survey. Ad Hoc Networks, 7, 537–568.CrossRef
2.
Abbasi, A. A., & Younis, M. (2007). A survey on clustering algorithms for wireless sensor networks. Computer Communications, 30, 2826–2841.CrossRef
3.
Heinzelman, W. B., Chandrakasan, A., & Balakrishnan, H. (2000). Energy-efficient communication protocols for wireless microsensor networks. In Proceedings of Hawaii international conference on system sciences.
4.
Bandhopadhyay, S., & Coyle, E. (2003). An energy efficient hierarchical clustering algorithm for wireless sensor networks. In Proceedings of IEEE INFOCOM.
5.
Younis, O., & Fahmy, S. (2004). HEED: A hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. IEEE Transactions on Mobile Computing, 3, 366–379.CrossRef
6.
Chan, H., & Perrig, A. (2004). ACE: An emergent algorithm for highly uniform cluster formation. In Proceedings of the First European workshop on sensor networks (pp. 154–171).
7.
Demirbas, M., Arora, A., & Mittal, V. (2004). FLOC: A fast local clustering service for wireless sensor networks. In Workshop on dependently issues in wireless ad hoc networks and sensor networks.
8.
Ye, M., Li, C. F., Chen, G. H., & Wu, J. (2005). An energy-efficient unequal clustering mechanism for wireless sensor networks. In Proceedings of the international conference on mobile ad hoc and sensor systems (p. 8).
9.
Ye, M., Li, C. F., Chen, G. H., & Wu, J. (2005). EECS: An energy efficient clustering scheme in wireless sensor networks. In IEEE international performance computing and communication conference (pp. 535–540).
10.
Kuila, P., Gupta, S. K., & Jana, P. K. (2013). A novel evolutionary approach for load balanced clustering problem for wireless sensor networks. Swarn and Evolutionary Computing, 12, 48–56.CrossRef
11.
12.
Dimokas, N., Katsaros, D., & Manolopoulos, Y. (2010). Energy-efficient distributed clustering in wireless sensor networks. Journal of Parallel Distributed Computing, 70, 371–383.CrossRefMATH
13.
Nauman, A., William, P., William, R., & Shyamala, S. (2011). A multi-criterion optimization technique for energy efficient cluster formation in wireless sensor networks. Information Fusion, 12, 202–212.CrossRef
14.
Navid, A., Alireza, V., Maria, G., & Majid, S. (2012). Cluster size optimization in sensor networks with decentralized cluster-based protocols. Computer Communications, 35, 207–220.CrossRef
15.
Amgoth, T., & Jana, P. K. (2013). BDCP: A backoff-based distributed clustering protocol for wireless sensor networks. In Proceedings of the international conference on advances in computing, communication and informatics (pp. 1012–1016).
16.
Tsai, Y. R. (2007). Coverage-preserving routing protocols for randomly distributed wireless sensor networks. IEEE Transactions on Wireless Communications, 6, 1240–1245.CrossRef
17.
Chamam, A., & Pierre, S. (2009). On the planning of wireless sensor networks: Energy-efficient clustering under the joint routing and coverage constraint. IEEE Transactions on Mobile Computing, 8, 1077–1086.CrossRef
18.
Heinzelman, W. B., & Soro, S. (2009). Cluster head election techniques for coverage preservation in wireless sensor networks. Ad-Hoc Networks, 7, 955–972.CrossRef
19.
Tao, Y., Zhang, Y., & Ji, Y. (2013). Flow-balanced routing for multi-hop clustered wireless sensor networks. Ad-Hoc Networks, 11, 541–554.CrossRef
20.
Perillo, M., Cheng, Z., & Heinzelman, W. (2004). On the problem of unbalanced load distribution in wireless sensor networks. In Proceedings of the IEEE GLOBECOM workshops (pp. 74–79).
21.
Muruganathan, S. D., Ma, D. C. F., Bhasin, R. I., & Fapojuwo, A. O. (2005). A centralized energy-efficient routing protocol for wireless sensor networks. IEEE Communications Magazine, 43, s8–13.CrossRef
22.
Yu, M., Kin, K. L., & Ankit, M. (2007). A dynamic clustering and energy efficient routing techniques for sensor networks. IEEE Transactions on Wireless Communications, 6, 3069–3079.CrossRef
23.
Fariborzi, H., & Moghavvemi, M. (2009). EAMTR: Energy aware multi-tree routing for wireless sensor networks. IET Communications, 3, 733–739.CrossRef
24.
Gagarin, A., Hussain, S., & Yang, L. T. (2010). Distributed hierarchical search for balanced energy consumption routing spanning trees in wireless sensor networks. Journal of Parallel and Distributed Computing, 70, 975–982.CrossRefMATH
25.
Ren, F., Zhang, J., He, T., Lin, C., & Das, S. K. (2011). EBRP: Energy-balanced routing protocol for data gathering in wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems, 22, 2018–2125.
26.
Abdel Salam, H. S., & Olariu, S. (2012). BEES: Bioinspired backbone selection in wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems, 23, 44–51.CrossRef
27.
Liu, Y., & Wang, Z. (2012). Maximizing energy utilization routing scheme in wireless sensor networks based on minimum hops algorithm. Computers and Electrical Engineering, 38, 703–721.CrossRefMATH
28.
Jiguo, Y., Yingying, Q., Guangui, W., & Xin, G. (2012). A cluster-based routing protocol for wireless sensor with non-uniform node distribution. International Journal of Electronics and Communications, 66, 54–61.CrossRef
29.
Abdulla, A. E. A. A., Nishiyama, H., & Kato, N. (2012). Extending the lifetime of the wireless sensor networks: A hybrid routing algorithm. Computer Communications, 35, 1056–1063.CrossRef
30.
Niculescu, D., & Nath, B. (2001). Ad-hoc positioning system. In Proceedings of the global telecommunications conference (pp. 2926–2931).
31.
Liu, Y., Suo, L., Sun, D., & Wang, A. (2013). A virtual square grid-based coverage algorithm of redundant node for wireless sensor network. Journal of Network and Computer Application, 36, 811–817.CrossRef
Metadaten
Titel
Energy and Coverage-Aware Routing Algorithm for Wireless Sensor Networks
verfasst von
Tarachand Amgoth
Prasanta K. Jana
Publikationsdatum
01.03.2015
Verlag
Springer US
Erschienen in
Wireless Personal Communications / Ausgabe 2/2015
Print ISSN: 0929-6212
Elektronische ISSN: 1572-834X
DOI
https://doi.org/10.1007/s11277-014-2143-y

Weitere Artikel der Ausgabe 2/2015

Wireless Personal Communications 2/2015 Zur Ausgabe

OriginalPaper

A Multi-objective Disjoint Set Covers for Reliable Lifetime Maximization of Wireless Sensor Networks

OriginalPaper

Adaptive Joint Semi-blind Estimation of CFO and Channel for OFDM Systems

OriginalPaper

A Energy-Polarization Based Detection for Cognitive Radios

OriginalPaper

Analysis of Optimal Carrier Sensing Range in Wireless Ad Hoc Networks with Order Dependent Capture Capability

OriginalPaper

A Reader Anti-collision Protocol for RFID-Enhanced Wireless Sensor Networks

OriginalPaper

Performance of Cooperative Diversity with Constellation Rearrangement in Multi-hop Wireless Networks

Neuer Inhalt

    Bildnachweise