Skip to main content

Advertisement

SpringerLink
Log in

Bee System Based Base Station Cooperation Technique for Mobile Cellular Networks

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

Mobility with high degree of network-facility is a mandatory attribute for better QoS in cellular networks, but it leads to a huge increment in energy consumption, a significant fraction of which related to the base stations within the service area. In this paper, we are introducing a base station cooperation technique for energy efficiency in mobile communication networks, and it is based on nature-inspired computing, especially the Bee system. All serving base stations within a given geographical area will work together to provide a better network experience to the mobile subscriber. In order to achieve this, base stations will check for availability of unutilized (or underutilized) bandwidth and if it is over a certain threshold, all base stations perform a re-reunion procedure to provide a uniform distribution of the consumed bandwidth (bandwidth load), thereby providing better service to users. We have formulated the proposed technique to determine the effectiveness, efficiency and scalability of work. Further we create a simulation setup for proposed algorithm using OPNET to implement a real time cellular networks. It has been observed that results of proposed work have sufficient improvement in energy efficiency at the base station with respect to traditional schemes.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20
Fig. 21
Fig. 22

Similar content being viewed by others

References

  1. Biswash, S. K., & Kumar, C. (2010). Multi home agent and pointer-based (MHA–PB) location management scheme in integrated cellular-WLAN networks for frequent moving users. Computer Communications, 33, 2260–2270.

    Article  Google Scholar 

  2. Hasan, Z., Boostanimehr, H., & Bhargava, V. K. (2011). Green cellular networks: A survey some research issues and challenges. IEEE Communications Surveys and Tutorials, 13, 524–540.

    Article  Google Scholar 

  3. Biswash, S. K., & Kumar, C. (2013). An index-based location management scheme for PCS network. Wireless Personal Communication, 69, 1597–1614.

    Article  Google Scholar 

  4. Pujji, L. K., Sowerby, K. W., & Neve, M. J. (2013). Development of a hybrid algorithm for efficient optimisation of base station placement for indoor wireless communication systems. Wireless Personal Communication, 69, 471–486.

    Article  Google Scholar 

  5. Biswash, S. K., & Kumar, C. (2011). An efficient metric-based (EM-B) location management scheme for wireless cellular networks. Journal of Network and Computer Applications, 34, 2011–2026.

    Article  Google Scholar 

  6. Son, K., Nagaraj, S., Sarkar, M., & Dey, S. (2013). QoS-aware dynamic cell reconfiguration for energy conservation in cellular networks. In Wireless Communications and Networking Conference (WCNC) (pp. 2022–2027).

  7. Bolla, R., & Repetto, M. (2014). A comprehensive tutorial for mobility management in data networks. IEEE Communications Surveys and Tutorials, 16, 812–833.

    Article  Google Scholar 

  8. Tuncer, H., Mishra, S., & Shenoy, N. (2012). A survey of identity and handoff management approaches for the future Internet. Computer Communications, 36, 63–79.

    Article  Google Scholar 

  9. Biswash, S.K., Sarkar, M., Nagaraj, S. (2015). Bee system-based energy efficient base station operation in mobile cellular networks. In IEEE ICNC 2015.

  10. Biswash, S. K., & Kumar, C. (2015). The metric and cache-based (MC-B) system for location management in wireless cellular networks. Wireless Personal Communication, 82, 569–593.

    Article  Google Scholar 

  11. Han, F., Safar, Z., & Liu, K. J. R. (2013). Energy-efficient base-station cooperative operation with guaranteed QoS. IEEE Transaction on Communication, 61, 3505–3517.

    Article  Google Scholar 

  12. Oh, E., Son, K., & Krishnamachari, B. (2013). Dynamic base station switching on/off strategies for green cellular networks. IEEE Transactions On Wireless Communications, 12(2013), 2126–2136.

    Article  Google Scholar 

  13. Lorincz, J., & Matijevic, T. (2014). Energy-efficiency analyses of heterogeneous macro and microbase station sites. Computers and Electrical Engineering, 40, 330–349.

    Article  Google Scholar 

  14. Niu, Z., Wu, Y., Gong, J., & Yang, Z. (2010). Cell zooming for cost-efficient green cellular networks. IEEE Communications Magazine, 48, 74–79.

    Article  Google Scholar 

  15. Cao, Dongxu, Zhou, Sheng, & Niu, Zhisheng. (2013). Optimal combination of base station densities for energy-efficient two-tier heterogeneous cellular networks. IEEE Transactions on Wireless Communications, 12, 4350–4362.

    Article  Google Scholar 

  16. http://www.nokiasiemensnetworks.com/environment.

  17. Dressler, F., & Akan, O. B. (2010). A survey on bio-inspired networking. Computer Networks, 54, 881–900.

    Article  MATH  Google Scholar 

  18. Rocha, M., Mendes, R., Rocha, O., Rocha, I., & Ferreira, E. C. (2014). Optimization of fed-batch fermentation processes with bio-inspired Algorithms. Expert Systems with Applications, 41, 2186–2195.

    Article  Google Scholar 

  19. Galán-Jiménez, J., & Gazo-Cervero, A. (2014). Using bio-inspired algorithms for energy levels assessment in energy efficient wired communication networks. Journal of Network and Computer Applications, 37, 171–185.

    Article  Google Scholar 

  20. Huang, S. J., Liu, X. Z., Su, W. F., & Ou, T. C. (2013). Application of enhanced honey-bee mating optimization algorithm to fault section estimation in power systems. IEEE Transactions on Power Delivery, 28(3), 1944–1951.

    Article  Google Scholar 

  21. Haddad, O. B., Afshar, A., & Marino, M. A. (2006). Honey-bees mating optimization (HBMO) algorithm: A new heuristic approach for water resources, optimization. Water Resources Management, 20, 661–680.

    Article  Google Scholar 

  22. Xia, F., Zhao, X., Zhang, J., Ma, J., & Kong, X. (2014). BeeCup: A bio-inspired energy-efficient clustering protocol for mobile learning. Future Generation Computer Systems, 37, 449–460.

    Article  Google Scholar 

  23. Tsai, P. W., Khan, M. K., Pan, J. S., & Liao, B. Y. (2014). Interactive artificial bee colony supported passive continuous authentication system. IEEE Systems Journal, 8(2014), 395–405.

    Article  Google Scholar 

  24. Wedde, H. F., & Senge, S. (2013). BeeJamA: A distributed, self-adaptive vehicle routing guidance approach. IEEE Transactions on Intelligent Transportation Systems, 14, 1882–1895.

    Article  Google Scholar 

  25. Liao, T., Aydın, D., & Stützle, T. (2013). Artificial bee colonies for continuous optimization: Experimental analysis and improvements. Swarm Intelligence, 7, 327–356.

    Article  Google Scholar 

  26. Mukherjee, A., Bhattacherjee, S., Pal, S., & De, D. (2013). Femtocell based green power consumption methods for mobile network. Computer Networks, 57, 162–178.

    Article  Google Scholar 

  27. Takanashi, H., & Rappaport, S. S. (1999). Dynamic base station selection for personal communication systems with distributed control schemes. Wireless Personal Communications, 11, 185–207.

    Article  Google Scholar 

  28. Chang, J. Y., & Lin, Y. S. (2015). An efficient base station and relay station placement scheme for multi-hop relay networks. Wireless Personal Communication, 82, 1907–1929.

    Article  Google Scholar 

  29. Akyildiz, I. F., & Wang, W. (2002). A dynamic location management scheme for next-generation multitier PCS systems. IEEE Transactions on Wireless Communications, 1(1), 178–189.

    Article  Google Scholar 

  30. Wang, Wenye, & Akyildiz, Ian F. (2001). A new signaling protocol for intersystem roaming in next-generation wireless systems. IEEE Journal on Selected Areas in Communications, 19, 2040–2052.

    Article  Google Scholar 

  31. Gorji, A. A., & Anderson, B. D. O. (2013). Emitter localization using received-strength-signal data. Signal Processing, 93, 996–1012.

    Article  Google Scholar 

  32. Lin, L., So, H. C., & Chan, Y. T. (2013). Accurate and simple source localization using differential received signal strength. Digital Signal Processing, 23, 736–743.

    Article  MathSciNet  Google Scholar 

Download references

Acknowledgments

This work has been supported by the National Science Foundation under Award No. 1116874.

Author information

Authors and Affiliations

  1. Department of Electrical and Computer Engineering, San Diego State University, San Diego, CA, 92182, USA

    Sanjay Kumar Biswash, Santosh Nagaraj, Mahasweta Sarkar & Naga Rajesh Narra

Authors
  1. Sanjay Kumar Biswash
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Santosh Nagaraj
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mahasweta Sarkar
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Naga Rajesh Narra
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sanjay Kumar Biswash.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Biswash, S.K., Nagaraj, S., Sarkar, M. et al. Bee System Based Base Station Cooperation Technique for Mobile Cellular Networks. Wireless Pers Commun 92, 1193–1220 (2017). https://doi.org/10.1007/s11277-016-3602-4

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-016-3602-4

Keywords

Search

Navigation