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
Wireless Personal Communications
Published in: Wireless Personal Communications 1/2019

18-03-2019

Computation of Mesh Node Placements Using DE Approach to Minimize Deployment Cost with Maximum Connectivity

Authors: G. Merlin Sheeba, Alamelu Nachiappan

Published in: Wireless Personal Communications | Issue 1/2019

Log in

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

search-config
loading …

Abstract

A node placement problem is formulated to ensure maximum connectivity and minimum deployment cost using differential evolution based node placement with traffic weight algorithm. A simulation study is performed to evaluate the performance of the network under four different client distribution patterns (Normal, Uniform, Exponential and Weibull). A maximum throughput of 95.3% and 96.2% of throughput is achieved in normal and weibull distributions than the conventional placement. It is observed from the results that the two distributions have good impact on network performance with minimum deployment cost and maximum connectivity. The packet delivery rate shows a percentage increase of 36.6% compared to the SA based placement scheme in normal distribution. It is also observed that a percentage increase of 28.9% of improvement is achieved when clients are distributed with weibull distribution and minimum end to end delay.
previous article Miniaturized Half-Mode Slow-Wave Substrate-Integrated Waveguide Bandpass Filter
next article Local Contribution (LC) and Trustworthiness Factors to Induce Fairness in P2P Networks

Dont have a licence yet? Then find out more about our products and how to get one 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+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 "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.
Denzinger, J., & Kidney, J. (2006). Evaluating different genetic operators in the testing for unwanted emergent behavior using evolutionary learning of behavior. In IEEE/WIC/ACM international conference on intelligent agent technology, pp. 23–29.
2.
Barolli, Fatos Xhafa Admir, Sánchez, Christian, & Barolli, Leonard. (2011). A simulated annealing algorithm for router nodes placement problem in wireless mesh. Networks Simulation Modelling Practice and Theory, 19, 2276–2284.CrossRef
3.
Xhafa, F., Sánchez, C., Barolli, A., & Takizawa, M. (2015). Solving mesh router nodes placement problem in wireless mesh networks by tabu search algorithm. Journal of Computer and System Sciences, 81, 1417–1428.MathSciNetCrossRefMATH
4.
Garey, M. R., & Johnson, D. S. (1979). Computers and Intractability—a guide to the theory of NP-completeness. San Francisco: Freeman.MATH
5.
Ilonen, J., Kamarainen, J. K., & Lampinen, J. (2003). Differential evolution training algorithm for feed-forward neural networks. Neural Processing Letters, 17(1), 93–105.CrossRef
6.
Lim, A., Rodrigues, B., Wang, F., & Xua, Zh. (2005). k-Center problems with minimum coverage. Theoretical Computer Science, 332, 1–17.MathSciNetCrossRefMATH
7.
Zhou, P., Wang, X., Manoj, B. S., & Rao R. (2010). On optimizing gateway placement for throughput in wireless mesh networks. EURASIP Journal on Wireless Communications and Networking, vol. 1, pp. 1–12.
8.
Price, K., Storn, R., & Lampinen, J. (2005). Differential evolution—A practical approach to global optimization. Berlin: Springer.MATH
9.
Oda, T., Barolli, A., Spaho, E., Barolli, L., Xhafa, F.& Iwashige, J. (2012). Node Placement in WMNs and visualization of evolutionary computation process using WMN-GA system. In 15th international conference on network-based information systems, (pp. 214–220).
10.
Tu, W. (2014). A multi-rate multi-channel multicast algorithm in wireless mesh networks. In 39th annual IEEE conference on local computer networks, (pp. 55–63).
11.
Xu, X., Tang, S., Mao, X., & Li, X. Y. (2010). distributed gateway placement for cost minimization in wireless mesh networks. In IEEE international conference on distributed computing systems, (pp. 507–515).
12.
Sheeba, G. M., Nachiappan, A., & Gokulnath, P. S. L. (2012). Improving link quality using OSPF routing protocol in a stable Wi-Fi mesh network. In communications and signal processing (ICCSP), 2012 international conference on (pp. 23–26). IEEE.
13.
Sheeba, G. M., & Nachiappan, A. (2013). An interworking implementation and performance evaluation in IEEE 802.11 s based campus mesh networks. Indian Journal Of Computer Science And Engineering, 4(1), 29–33.
14.
Sheeba, G. M., & Nachiappan, A. (2015). Fuzzy differential evolution based gateway placements in WMN for cost optimization. Intelligent Systems Technologies and Applications, 385, 137–145.CrossRef
15.
Sheeba, G. M., Nachiappan, A., & Kumar, P. H. (2015). placement of energy aware wireless mesh nodes for e-learning in green campuses. arXiv preprint. arXiv:​1505.​04713.
16.
Sheeba, G. M., & Nachiappan, A. (2015). Gateway placements in wmn with cost minimization and optimization using sa and de techniques. International Journal Of Pharmacy & Technology, 7(1), 8274–8281.
17.
Sheeba, G. M., & Nachiappan, A. (2018). Performance evaluation of fuzzy DE based node placement in WMN. Journal of Engineering Research, 5(4), 106–120.
Metadata
Title
Computation of Mesh Node Placements Using DE Approach to Minimize Deployment Cost with Maximum Connectivity
Authors
G. Merlin Sheeba
Alamelu Nachiappan
Publication date
18-03-2019
Publisher
Springer US
Published in
Wireless Personal Communications / Issue 1/2019
Print ISSN: 0929-6212
Electronic ISSN: 1572-834X
DOI
https://doi.org/10.1007/s11277-019-06255-8

Other articles of this Issue 1/2019

Wireless Personal Communications 1/2019 Go to the issue

OriginalPaper

A Probability-Based Anti-Collision Protocol for RFID Tag Identification

OriginalPaper

Performance Analysis of Low Power Channel Estimator for Multi User MIMO-OFDM System

OriginalPaper

Security Optimization of Two-Hop AF Cooperative Relay Network

OriginalPaper

A Metamaterial Inspired ZOR Antenna Using IDC and Spiral Inductor with Partial Ground Plane for WLAN Application

BriefCommunication

DFT-Based Low-Complexity Channel Estimation Method for Millimeter-Wave MIMO Systems

OriginalPaper

Broadcast Retransmission Algorithm Based on Potential Game in CRNs