Improving Adaptive Quality of Service for Multimedia Wireless Networks Using Hierarchical Networks Approach
Multimedia traffic is expected to populate the next generation wireless networks. As in wireline networks, the wireless network must able to provide a guaranteed quality of service (QoS) over the lifetime of mobile connections. Some challenging problems such as user mobility, limited frequency sp...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English English |
| Published: |
2004
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| Subjects: | |
| Online Access: | http://psasir.upm.edu.my/id/eprint/258/1/549513_FK_2004_43.pdf |
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| Summary: | Multimedia traffic is expected to populate the next generation wireless networks. As in
wireline networks, the wireless network must able to provide a guaranteed quality of service
(QoS) over the lifetime of mobile connections. Some challenging problems such as user
mobility, limited frequency spectrum and shortage of bandwidth, influence the QoS
provisioning for the users.
This thesis examines into the issue of delivering a guaranteed quality of service (QoS) for
multimedia services in wireless environment. A PhD candidate, Prihandoko have proposed
an Adaptive QoS (AdQoS) model to guarantee the delivery of multimedia services. That
work have been adopted and extended by means of a hierarchical network approach, calling
it as Improved AdQoS model.The main objective that the Improved AdQoS framework tries to accomplish is to reduce the
New Call Blocking Probability (NCBP) and Handoff Call Dropping Probability (HCDP). The
key feature of this framework is the integration of the hierarchical network together with the
modified Call Admission Control (CAC) algorithm and the bandwidth reallocation scheme.
These schemes are developed to control the bandwidth operation of ongoing connections
when the system is overloaded depending on the movement speed of a particular user
assuming the speed of a mobile user would not be changed throughout the duration of a
connection.
The performance of the system is evaluated through simulations of a cellular
environment under three different scenarios. Scenario A represents an area with
80% slow speed users and 20% fast speed users, Scenario B represents an area with a
population of 40% slow speed users and 60% fast speed users while Scenario C represents an
area with 20% slow speed users and 80% fast speed users.
When compared with the scheme proposed Prihandoko in the literature, the
simulation results show that our proposed scheme reduces the new call
blocking probabilities, the handoff dropping probabilities and reduces
significantly the probability of terminating calls |
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