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Volume 39 Issue 6
Jun.  2017
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WANG Ruyan, CHI Wenxiang, ZHANG Hong. Adaptive Traffic Shaping Policy Based on Token Bucket Algorithm of Wireless-optical Broadband Access Network[J]. Journal of Electronics & Information Technology, 2017, 39(6): 1401-1408. doi: 10.11999/JEIT160974
Citation: WANG Ruyan, CHI Wenxiang, ZHANG Hong. Adaptive Traffic Shaping Policy Based on Token Bucket Algorithm of Wireless-optical Broadband Access Network[J]. Journal of Electronics & Information Technology, 2017, 39(6): 1401-1408. doi: 10.11999/JEIT160974

Adaptive Traffic Shaping Policy Based on Token Bucket Algorithm of Wireless-optical Broadband Access Network

doi: 10.11999/JEIT160974
Funds:

The National Natural Science Foundation of China (61371097, 61401052, 61271261), Science and Technology Research Project of Chongqing Municipal Education Commission (KJ1400418), Youth Talents Training Project of Chongqing Science Technology Commission (CSTC2014KJRC-QNRC 40001), Chongqing Funded Project of College Young Teachers Scheme (Yu teaches [2014] No. 47) , Program for Innovation Team Building at Institutions of Higher Education in Chongqing (CXTDX201601020)

  • Received Date: 2016-09-28
  • Rev Recd Date: 2017-02-15
  • Publish Date: 2017-06-19
  • There are mismatches of transmission rates and different service classifications between optical domain and wireless domain in Wireless-Optical Broadband Access Network (WOBAN). To improve the QoS of the integration network and make full use of network resources, a new algorithm based on token bucket traffic shaping policy is proposed. According to the service mapping rules and scheduling of EPON and WiMAX, the selection of token bucket parameters B determined based on the relative service priority of the entire network. This paper also combines with more realistic self-similar network traffic to derive the best formula for token bucket parameters and then proposes a shared buffer strategy on the basis of the service priority. Furthermore, an adaptively dynamically adjust traffic shaping policy is obtained through the change of QoS metrics. The simulation results show that the proposed strategy can effectively reduce traffic shaping network equipment pressure while improving the QoS of whole converged networks.
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