Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Cluster Computing
Published in: Cluster Computing 2/2019

12-03-2018

Research on the optimal cluster number of energy efficiency based on the block model of opportunistic signal

Author: Tiancheng Wang

Published in: Cluster Computing | Special Issue 2/2019

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

According to the WiFi, acoustic or visible light opportunity signals in Wireless Sensor Networks (WSNs), we propose a block Compartmental model based on optimal cluster number (Compartmental Modelling). The block model is a fading model, which reflects the attenuation of the opportunity signal with the propagation distance. In order to reduce the overall energy consumption, the optimal number of clusters is calculated by using the different order of the Taylor series expansion of the block model. Finally, a real experimental platform is established by using mobile phone, wireless access point, sound and light signal to analyze the optimal number of clusters. The experimental data showed that compared with the Exponential model and the logarithmic Log model, the energy consumption of CML decreased by about 6 and 8% respectively. In addition, the energy efficiency of the visible light signal is nearly 12% compared to the WiFi harmonic signal.
previous article Mobile robot positioning method based on multi-sensor information fusion laser SLAM
next article Competition and the stepping-stone theory in the broadband access market

Dont have a licence yet? Then find out more about our products and how to get one now:

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!

inform now

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!

inform now

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!

inform now
Literature
1.
Song, G.H., Chao, M.Y., Yang, B.W., et al.: TLR: a traffic light-based intelligent routing strategy for NGEO satellite IP networks. IEEE Trans. Wirel. Commun. 13(6), 3380–3393 (2014)
2.
Nishiyama, H., Tada, Y., Kato, N., et al.: Toward optimized traffic distribution for efficient network capacity utilization in two-layered satellite networks. IEEE Trans. Veh. Technol. 62(3), 1303–1313 (2013)
3.
Zhou, D., Chen, S., Dong, S.: Network traffic prediction based on ARFIMA model. Int. J. Comput. Sci. Issues 9(6), 84–87 (2013)
4.
Ojeda, L.L., Kibangou, A.Y., De Wit, C.C.: Adaptive Kalman filtering for multi-step ahead traffic flow prediction, pp. 4724–4729. In: American Control Conference (2013)
5.
Xiao, H., Sun, H., Ran, B.: Fuzzy-neural network traffic prediction framework with wavelet decomposition. Transp. Res. Rec. J Transp. Res. Board 1836(1), 16–20 (2003)
6.
Hong, W.C.: A hybrid support vector machine regression for exchange rate prediction. Int. J. Inf. Manag. Sci. 17(2), 19–32 (2006)
7.
Quan, T., Liu, X., Liu, Q.: Weighted least squares support vector machine local region method for nonlinear time series prediction. Appl. Soft Comput. 10(2), 562–566 (2010)
8.
Xu, B., Han, D.: LS-SVM combination prediction technique based on prediction correlation and its application. In: Foundations of Intelligent Systems, pp. 559–566. Springer, Berlin (2014)
9.
Lu, Z., Zhou, C., Wu, J., et al.: Integrating granger causality and vector auto-regression for traffic prediction of large-scale WLANs. KSII Trans. Internet Inf. Syst. 10(1), 136–151 (2016)
10.
Romirermaierhofer, P., Schiavone, M., D’Alconzo, A.: Device-specific traffic characterization for root cause analysis in cellular networks, pp. 64–78. In: International Workshop on Traffic Monitoring and Analysis, TMA (2015)
11.
Sakurai, Y., Papadimitriou, S., Faloutsos, C.: BRAID: stream mining through group lag correlations, pp. 599–610. In: ACM SIGMOD International Conference on Management of Data, Baltimore, Maryland, USA, June. DBLP (2005)
12.
Wang, H., Hu, D.: Comparison of SVM and LS-SVM for regression, pp. 279–283. In: International Conference on Neural Networks and Brain, 2005. Icnn&b. IEEE (2005)
13.
Siuly, S., Li, Y.: Improving the separability of motor imagery EEG signals using a cross correlation-based least square support vector machine for brain–computer interface. IEEE Trans. Neural Syst. Rehabil. Eng. 20(4), 526 (2012)
Metadata
Title
Research on the optimal cluster number of energy efficiency based on the block model of opportunistic signal
Author
Tiancheng Wang
Publication date
12-03-2018
Publisher
Springer US
Published in
Cluster Computing / Issue Special Issue 2/2019
Print ISSN: 1386-7857
Electronic ISSN: 1573-7543
DOI
https://doi.org/10.1007/s10586-018-2475-6

Other articles of this Special Issue 2/2019

Cluster Computing 2/2019 Go to the issue

OriginalPaper

An intelligent data aware and energy censoring scheme for wireless sensor networks

OriginalPaper

A modeling and optimization method for heterogeneous objects based on complex networks theory

OriginalPaper

Enhanced perceptual psychopathology correlation mechanism model based on rough set and neural network

OriginalPaper

Construction of employee training program evaluation system of three exponential forecast based on sliding window

OriginalPaper

Modelling the spice parameters of SOI MOSFET using a combinational algorithm

OriginalPaper

Productivity prediction method based on analysis model of principal component neural network

Premium Partner

    Image Credits