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Optimum bandwidth allocation in wireless networks using differential evolution

  • Zahid Afzal
  • Peer Azmat ShahEmail author
  • Khalid M. AwanEmail author
  • Zahoor-ur-Rehman
Original Research
  • 51 Downloads

Abstract

Wireless networking is experiencing a tremendous growth in new standards of communication and computer applications. Currently, wireless networks exist in various forms, providing different facilities. However, due to some limitations as compared with wired counterparts, wireless networks face several major challenges and one of them is optimum bandwidth allocation. The focus of optimum bandwidth allocation is to reduce the losses and satisfying quality of service (QoS) requirements. In wireless networks, the term bandwidth allocation is attributed as the distribution of bandwidth resources among different users, which affects the serviceability of the entire system. Though many studies related to bandwidth allocation have been reported already, however, only sub-optimal solutions have been provided so far. In this research, we proposed to use the differential evolution (DE) algorithm to allocate bandwidth through a bandwidth reservation scheme in the Cellular IP network, in order to improve the QoS at an acceptable level. DE belongs to a class of evolutionary algorithms (EA), like particle swarm optimization and genetic algorithm. A DE-based method is used which looks for any free bandwidth in the cell or in adjacent cells and provides it to the cell where required. In case, it fails to find the free available bandwidth then it will search the bandwidth which is standby for non real-time users and allocates it to the real-time users that will help in improving the QoS in terms of connection/call dropping probability for real-time users. Simulation results show that the proposed method performs better as compared to previously used EA models for bandwidth allocation.

Keywords

Cellular IP network Evolutionary algorithms differential evolution Quality of service (QoS) 

Notes

References

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Internet, Communication and Networks (ICNet) Research Lab, Department of Computer ScienceCOMSATS UniversityAttockPakistan
  2. 2.Pattern Recognition, Imaging and Data Engineering (PRIDE) Research Lab, Department of Computer ScienceCOMSATS UniversityAttockPakistan

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