• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.3C
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• pp.219-227
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• 2006

In this paper, we propose a packet scheduling algorithm to maximize the required total price of the systems that is applied with a different traffic pricing criterion by the mobile service operator according to different kinds of the services. The proposed algorithm adopts a particular estimation method in scheduling using the value of pricing function, which is based on the required services and the value of SIR(signal to interference ratio) that indicate the channel condition of each user. We compare Max C/I, proportional fairness and round robin algorithm with the proposed algorithm on HSDPA in order to analyze the performance. The result shows that the proposed algorithm satisfies higher throughput and provides maximum the mobile service provider's revenue.

• Journal of Communications and Networks
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• v.6 no.1
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• pp.68-77
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• 2004

In the near future packet networks should support applications which can not predict their traffic requirements in advance, but still have tight quality of service requirements, e.g., guaranteed bandwidth, jitter, and packet loss. These dynamic characteristics mean that the sources can be made to modify their data transfer rates according to network conditions. Depending on the customer&; needs, network operator can differentiate incoming connections and handle those in the buffers and the interfaces in different ways. In this paper, dynamic QoS-aware scheduling algorithm is presented and investigated in the single node case. The purpose of the algorithm is in addition to fair resource sharing to different types of traffic classes with different priorities ?to maximize revenue of the service provider. It is derived from the linear type of revenue target function, and closed form globally optimal formula is presented. The method is computationally inexpensive, while still producing maximal revenue. Due to the simplicity of the algorithm, it can operate in the highly nonstationary environments. In addition, it is nonparametric and deterministic in the sense that it uses only the information about the number of users and their traffic classes, not about call density functions or duration distributions. Also, Call Admission Control (CAC) mechanism is used by hypothesis testing.