Call Admission Control in Mobile Multimedia Network Using Grey Wolf Optimization

Kumar, Sanjeev; Gaur, Madhu Sharma

doi:10.1007/978-981-15-2780-7_27

Cited by 7 publications

(1 citation statement)

References 16 publications

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“…Bandwidth is allocated to calls in proportion to the priority of the calls. Kumar et al [24] modeled the channel allocation scheme for calls as an optimization problem on multiple objectives. Fitness function based on multiple objectives of minimizing call drop, increasing resource utilization, etc., is defined and optimization is done using Grey wolf optimizer.…”

Section: Related Workmentioning

confidence: 99%

Active Learning Assisted Admission and Bandwidth Management in HWN for Facilitating Differential QoS under Multicriteria Factors

Biradar

Shweta

Padmanaban

et al. 2022

Scientific Programming

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Control of call admission and management of bandwidth are the two important functionalities to achieve higher call handling capacity in heterogeneous wireless networks (HWN). This work addresses the problem of supporting differential qualities of services (QoS) with adherence to multicriteria factors in addition to reducing call-dropping probability in HWN. Toward this end, learning-assisted admission and bandwidth management are proposed. The decision to control the call acceptance ratio and bandwidth allocation level is learned continuously based on current network dynamics and the differential QoS requirements of the current calls. This learning reduces the call drop probability and slippage in QoS for calls. The parameters employed for evaluation in the suggested approach for call admission control include call priority, service type, service delivery mode, bandwidth availability for scalable and nonscalable calls, QoS distortion rate, and call ratio.

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Section: Related Workmentioning

confidence: 99%