Performance evaluation of TCP/RLP protocol stack over CDMA wireless link
Wireless Networks - Special issue on wireless multimedia networking
Flow and stretch metrics for scheduling continuous job streams
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
Jitter control in QoS networks
IEEE/ACM Transactions on Networking (TON)
A Behavioral Model of Web Traffic
ICNP '99 Proceedings of the Seventh Annual International Conference on Network Protocols
Proceedings of the 9th annual international conference on Mobile computing and networking
Radio Resource Management for Cellular CDMA Systems Supporting Heterogeneous Services
IEEE Transactions on Mobile Computing
A novel thread scheduler design for polymorphic embedded systems
CASES '11 Proceedings of the 14th international conference on Compilers, architectures and synthesis for embedded systems
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The success of future generation wireless data services will depend on the parameterized provisioning of quality of service (QoS) for applications whose demands and nature are highly heterogeneous. Also, user satisfaction will play a key role in the economic viability of wireless service deployments. In this paper, we present a QoS framework based on the paradigm of traffic class and user satisfaction. We address the problem of dealing with subjectiveness of user satisfaction or expectation from service providers by defining what we call user irritation factors, using Sigmoid functions. These factors reflect users' sensitivity and tolerance to delay. The proposed class-based QoS framework comprises a radio resource management scheme which considers user satisfaction based on the perceived QoS, and caters to heterogeneous applications that have diverse QoS requirements. Our resource management scheme has two components: the admission control algorithm caters to the long term user satisfaction while the session-based rate and bandwidth allocation scheme manipulates the short term user satisfaction. Soft-reservation schemes are also proposed to cater to the higher paying users. Performance metrics have been specifically defined for each traffic class. Extensive simulations using four types of traffic and three classes of users reveal that the proposed framework offers improved QoS without compromising the utilization of the system.