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 Networks
Erschienen in: Wireless Networks 7/2014

01.10.2014

Prolonging the lifetime of wireless sensor networks by utilizing feedback control

verfasst von: Jing Zhang, Yanheng Liu, Dayang Sun, Bin Li

Erschienen in: Wireless Networks | Ausgabe 7/2014

Einloggen

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

search-config
loading …

Abstract

A new algorithm aiming to prolong the lifetime of wireless sensor networks (WSNs) is proposed to balance energy depletion. Using a feedback control combined with a discrete nonlinear programming method to adjust the transmission radii of sensor nodes located in different locations, makes network load redistribution possible and balances energy consumption, further prolongs the lifetime of the entire network. A data distribution model which specific to WSNs with sensor nodes that can adjust transmission radii is proposed to analyze the load spread of the network. This model contributes to predicting and analyzing energy consumption balance effectively. Compared with two other algorithms, dynamic transmission range adjustment and SP, respectively, the experimental results show that the proposed algorithm can lengthen the lifetime of WSNs by up to 22.7 and 27.2 %.
Vorheriger Artikel Cooperative data transmission framework for IEEE 802.16j mobile multihop relay networks
Nächster Artikel Deploying AL-FEC protection with online algorithms for multicast services over cellular 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
Literatur
1.
Ghataoura, D. S., Mitchell, J. E., & Matich, G. E. (2011). Networking and application interface technology for wireless sensor network surveillance and monitoring. IEEE Communication Magazine, 49(10), 90–97.CrossRef
2.
Zhuiykov, S. (2012). Solid-state sensors monitoring parameters of water quality for the next generation of wireless sensor networks. Sensors and Actuators B: Chemical, 161(1), 1–20.CrossRef
3.
Li, M., & Liu, Y. (2007). Underground structure monitoring with wireless sensor networks. In Proceedings of sixth IEEE/ACM international conference information processing in sensor networks (IPSN’07) (pp. 69–78).
4.
Placzek, B. (2012). Selective data collection in vehicular networks for traffic control applications. Transportation Research Part C: Emerging Technologies, 23, 14–28.CrossRef
5.
Li, J., & Mohapatra, P. (2005). An analytical model for the energy hole problem in many-to-one sensor networks. In IEEE VTS vehicular technology conference proceedings (pp. 2721–2725).
6.
Li, Q.-Q., Gong, H., Liu, M., Yang, M., & Zheng, J. (2011). On prolonging network lifetime through load-similar node deployment in wireless sensor networks. Sensors, 11(4), 3527–3544.CrossRef
7.
Olariu, S., & Stojmenovic, I. (2006). Design guidelines for maximizing lifetime and avoiding energy holes in sensor networks with uniform distribution and uniform reporting. In Proceedings of 25th IEEE INFOCOM conference (pp. 2505–2516).
8.
Bagaa, M., Challal, Y., Ouadjaout, A., Lasla, N., & Badachea, N. (2012). Efficient data aggregation with in-network integrity control for WSN. Journal of Parallel and Distributed Computing, 72, 1157–1170.CrossRef
9.
Larios, D. F., Barbancho, J., Rodríguez, G., Sevillano, J. L., Molina, F. J., & León, C. (2012). Energy efficient wireless sensor network communications based on computational intelligent data fusion for environmental monitoring. IET Communications, 6(14), 2189–2197.CrossRef
10.
Zeydan, E., Kivanc, D., Comaniciu, C., & Tureli, U. (2012). Energy-efficient routing for correlated data in wireless sensor networks. Ad Hoc Networks, 10, 962–975.CrossRef
11.
Heinzelman, W. R., Chandrakasan, A., & Balakrishnan, H. (2000). Energy-efficient communication protocol for wireless microsensor networks. In Proceedings of 33rd Hawaii international conference on system sciences, USA (Vol. 8, p. 8020).
12.
Lindsey, S., Raghavendra C. S. (2002). PEGASIS: Power-efficient gathering in sensor information systems. In Proceedings of the IEEE aerospace conference, Montana, USA (Vol. 3, pp. 1125–1130).
13.
Sinha, K., Sinha, B. P., & Datta, D. (2010). CNS: A new energy efficient transmission scheme for wireless sensor networks. Wireless Network, 16(8), 2087–2104.CrossRef
14.
Mitton, N., Razafindralambo, T., Simplot-Ryl, D., & Stojmenovic, I. (2012). Towards a hybrid energy efficient multi-tree-based optimized routing protocol for wireless networks. Sensors, 12(12), 17295–17319.CrossRef
15.
Cheng, S.-T., & Chang, T.-Y. (2012). An adaptive learning scheme for load balancing with zone partition in multi-sink wireless sensor network. Expert Systems with Applications, 39, 9427–9434.MathSciNetCrossRef
16.
Chang, C.-Y., Lin, C.-Y., & Kuo, C.-H. (2012). EBDC: An energy-balanced data collection mechanism using a mobile data collector in WSNs. Sensors, 12(5), 5850–5871.CrossRef
17.
Keskın, M. E., Altinel, I. K., Aras, N., & Ersoy, C. (2011). Lifetime maximization in wireless sensor networks using a mobile sink with nonzero traveling time. Computer Journal, 54(12), 1987–1999.CrossRef
18.
Zhiewen, Z., Chen, Z. G., & Liu, A. F. (2010). Energy-hole avoidance for WSN based on adjust transmission power. Chinese Journal of Computers, 33(1), 12–22.CrossRef
19.
Wu, X., Chen, G., & Das, S. K. (2008). Avoiding energy holes in wireless sensor networks with nonuniform node distribution. IEEE Transactions on Parallel Distributed Systems, 19(5), 710–720.CrossRef
20.
Bouabdallah, F., Bouabdallah, N., & Boutaba, R. (2009). On balancing energy consumption in WSNs. IEEE Transactions on Vehicular Technology, 58(6), 2909–2924.CrossRef
21.
Ren, F., Zhang, J., He, T., Lin, C., & Ren, S. K. (2011). EBRP: Energy-balanced routing protocol for data gathering in WSNs. IEEE Transactions on Parallel Distributed Systems, 22(12), 2108–2125.CrossRef
22.
Ilyas, M. U., & Radha, H. (2012). A dynamic programming approach to maximizing a statistical measure of the lifetime of sensor networks. ACM Transactions on Sensor Networks, 8(2), 18.CrossRef
23.
Vinh, T.-Q., Huu, P. N., & Miyoshi, T. (2011). A transmission range optimization algorithm to avoid energy holes in wireless sensor networks. IEICE Transactions on Communications E, 94B(11), 3026–3036.
24.
Azad, A. K. M., & Kamruzzaman, J. (2011). Energy-balanced transmission policies for wireless sensor networks. IEEE Transactions on Mobile Computing, 10(7), 927–940.CrossRef
25.
26.
27.
Heinzelman, W. B. (2000). Application-specific protocol architectures for wireless networks. Ph.D. thesis. Massachusetts Institute of Technology.
28.
Sun, H., Wang, Y., & Chai, S. (2005). A universal approach for continuous or discrete nonlinear programmings with multiple variables and constraints. Applied Mathematics and Mechanics, 26(10), 1284–1292.MathSciNetCrossRefMATH
Metadaten
Titel
Prolonging the lifetime of wireless sensor networks by utilizing feedback control
verfasst von
Jing Zhang
Yanheng Liu
Dayang Sun
Bin Li
Publikationsdatum
01.10.2014
Verlag
Springer US
Erschienen in
Wireless Networks / Ausgabe 7/2014
Print ISSN: 1022-0038
Elektronische ISSN: 1572-8196
DOI
https://doi.org/10.1007/s11276-014-0726-x

Weitere Artikel der Ausgabe 7/2014

Wireless Networks 7/2014 Zur Ausgabe

OriginalPaper

Assessing the influence of selfishness on the system performance of gossip based vehicular networks

OriginalPaper

Dynamic power management in Wi-Fi Direct for future wireless serial bus

OriginalPaper

Delay minimization and priority scheduling in wireless mesh networks

OriginalPaper

Rethinking TCP flow control for smartphones and tablets

OriginalPaper

An energy-aware deadline-constrained message delivery in delay-tolerant networks

OriginalPaper

Signal power random fading based interference-aware routing for wireless sensor networks

Neuer Inhalt

    Bildnachweise