• 中国精品科技期刊
  • CCF推荐A类中文期刊
  • 计算领域高质量科技期刊T1类
Advanced Search
Chen Ting, Li Jiandong, Zhong Shaobo, Li Changle. A Fair-Oriented Two-Level Scheduling Scheme for QoS Guarantee in WiMAX[J]. Journal of Computer Research and Development, 2009, 46(7): 1094-1101.
Citation: Chen Ting, Li Jiandong, Zhong Shaobo, Li Changle. A Fair-Oriented Two-Level Scheduling Scheme for QoS Guarantee in WiMAX[J]. Journal of Computer Research and Development, 2009, 46(7): 1094-1101.

A Fair-Oriented Two-Level Scheduling Scheme for QoS Guarantee in WiMAX

More Information
  • Published Date: July 14, 2009
  • As the standard of worldwide interoperability for microwave access (WiMAX) technology, IEEE 802.16 defined five classes of traffic services, which are UGS, rtPS, ertPS, nrtPS, and BE, respectively, and introduced a supporting mechanism for quality of services (QoS) into medium access control (MAC) layer. But it did not propose the corresponding scheduling algorithm. In order to provide various multimedia communications with QoS guarantee effectively, a two-level scheduling scheme is proposed based on the orthogonal frequency division multiple access (OFDMA) technology and adaptive modulation and coding (AMC) mechanism. This scheduling scheme employes the cross-layer design methodology and can be used in the point-to-multipoint (PMP) WiMAX downlink. According to the value of QoS priority, the first-level scheduler schedules the head of line (HOL) packets in different service class buffers to satisfy the rtPS maximum delay restriction and nrtPS minimum rate requirement simultaneously. After accomplishing the first-level scheduling, the second-level scheduler schedules the HOL packets in different user buffers according to the AMC information and users’ state message for obtaining the users’ rate fairness. Simulation results show that the proposed two-level scheme can meet various QoS requirements of multimedia services well without sacrificing users’ rate fairness, and meanwhile, get the preferable WiMAX system throughput.
  • Related Articles

    [1]Ren Jiadong, Liu Xinqian, Wang Qian, He Haitao, Zhao Xiaolin. An Multi-Level Intrusion Detection Method Based on KNN Outlier Detection and Random Forests[J]. Journal of Computer Research and Development, 2019, 56(3): 566-575. DOI: 10.7544/issn1000-1239.2019.20180063
    [2]Liu Lu, Zuo Wanli, Peng Tao. Tensor Representation Based Dynamic Outlier Detection Method in Heterogeneous Network[J]. Journal of Computer Research and Development, 2016, 53(8): 1729-1739. DOI: 10.7544/issn1000-1239.2016.20160178
    [3]Zhao Xingwang, Liang Jiye. An Attribute Weighted Clustering Algorithm for Mixed Data Based on Information Entropy[J]. Journal of Computer Research and Development, 2016, 53(5): 1018-1028. DOI: 10.7544/issn1000-1239.2016.20150131
    [4]Huang Tianqiang, Yu Yangqiang, Guo Gongde, Qin Xiaolin. Trajectory Outlier Detection Based on Semi-Supervised Technology[J]. Journal of Computer Research and Development, 2011, 48(11): 2074-2082.
    [5]Zhang Jing, Sun Zhihui, Yang Ming, Ni Weiwei, Yang Yidong. Fast Incremental Outlier Mining Algorithm Based on Grid and Capacity[J]. Journal of Computer Research and Development, 2011, 48(5): 823-830.
    [6]Yu Hao, Wang Bin, Xiao Gang, Yang Xiaochun. Distance-Based Outlier Detection on Uncertain Data[J]. Journal of Computer Research and Development, 2010, 47(3): 474-484.
    [7]Ni Weiwei, Chen Geng, Lu Jieping, Wu Yingjie, Sun Zhihui. Local Entropy Based Weighted Subspace Outlier Mining Algorithm[J]. Journal of Computer Research and Development, 2008, 45(7): 1189-1194.
    [8]Jin Yifu, Zhu Qingsheng, Xing Yongkang. An Algorithm for Clustering of Outliers Based on Key Attribute Subspace[J]. Journal of Computer Research and Development, 2007, 44(4): 651-659.
    [9]Ni Weiwei, Lu Jieping, Chen Geng, and Sun Zhihui. An Efficient Data Stream Outliers Detection Algorithm Based on k-Means Partitioning[J]. Journal of Computer Research and Development, 2006, 43(9): 1639-1643.
    [10]Yang Yidong, Sun Zhihui, Zhang Jing. Finding Outliers in Distributed Data Streams Based on Kernel Density Estimation[J]. Journal of Computer Research and Development, 2005, 42(9): 1498-1504.

Catalog

    Article views (737) PDF downloads (485) Cited by()

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return