A new QoS provisioning method for adaptive multimedia in cellular wireless networks

Third generation cellular wireless networks are designed to support adaptive multimedia by controlling individual ongoing flows to increase or decrease their bandwidth in response to changes in traffic load There is growing interest in quality of service (QoS) provisioning under this adaptive multim...

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Vydáno v:2004 IEEE Infocom Ročník 3; s. 2130 - 2141 vol.3
Hlavní autoři: Fei Yu, Wong, V.W.S., Leung, V.C.M.
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: Piscataway, New Jersey IEEE 2004
Témata:
Access methods and protocols, osi model
Adaptive control
Algorithm design and analysis
Applied sciences
Bandwidth
Call admission control
Cellular networks
Equipments and installations
Exact sciences and technology
Learning
Mobile radiocommunication systems
Operation, maintenance, reliability
Programmable control
Quality of service
Radiocommunications
Systems, networks and services of telecommunications
Telecommunication traffic
Telecommunications
Telecommunications and information theory
Teleprocessing networks. Isdn
Transmission and modulation (techniques and equipments)
Wireless networks
Access control
Performance evaluation
Mobile radiocommunication
Wireless telecommunication
Reinforcement learning
Equity
Teletraffic
Cell network
Traffic load
Multimedia communication
Algorithm
Simulation
Telecommunication network
Transition probability
Handover
Service quality
ISBN:0780383559, 9780780383555
ISSN:0743-166X
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Shrnutí:Third generation cellular wireless networks are designed to support adaptive multimedia by controlling individual ongoing flows to increase or decrease their bandwidth in response to changes in traffic load There is growing interest in quality of service (QoS) provisioning under this adaptive multimedia framework, in which a bandwidth adaptation algorithm needs to be used in conjunction with the call admission control algorithm. This paper presents a novel method for QoS provisioning via the use of the average reward reinforcement learning, which can maximize the network revenue subject to several predetermined QoS constraints. By considering handoff dropping probability, average allocated bandwidth and intraclass fairness simultaneously, our algorithm formulation guarantees that these QoS parameters are kept within predetermined constraints. Unlike other model-based algorithms, our scheme does not require explicit state transition probabilities and therefore the assumptions behind the underlying system model are more realistic than those in previous schemes. Moreover, by considering the status of neighboring cells, the proposed scheme can dynamically adapt to changes in traffic condition. Simulation results demonstrate the effectiveness of the proposed approach in adaptive multimedia cellular networks
ISBN:0780383559
9780780383555
ISSN:0743-166X
DOI:10.1109/INFCOM.2004.1354620