Prof. Bin Ma Profile

Prof. Bin Ma

at Chongqing Univ of Posts and Telecommunications

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Proceedings Article | 7 October 2016 Paper

Spectrum handoff algorithm with imperfect spectrum sensing incognitive radio networks

Bin Ma, Xiao-min Bao, Xian-zhong Xie

Proceedings Volume 9902, 99020J (2016) https://doi.org/10.1117/12.2262337

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To guarantee the quality of service of licensed users, the unlicensed users must vacate the occupied channel by spectrum handoff if licensed users appear in the licensed spectrum. However, spectrum sensing with false alarm and missed detection may lead to more inaccuracy problems when unlicensed users perform spectrum handoff. To improve the problems mentioned before, we utilize PRP M/G/1 queuing network model to propose a spectrum handoff algorithm with error data retransmission mechanism and analyze its performance by transmission delay and extended data delivery time. In addition, we discuss the relationship between false alarm probability, extended data delivery time and user traffic load and verify the effectiveness of the proposed algorithm.

Proceedings Article | 19 November 2007 Paper

Using cloud association rule data mining approach in optical networks

Bin Ma

Proceedings Volume 6783, 67833S (2007) https://doi.org/10.1117/12.742814

KEYWORDS: Clouds, Databases, Switching, Data mining, Dense wavelength division multiplexing, Networks, Optical networks, Optical fibers, Statistical analysis, Mining

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In the current DWDM network, one of the critical design issues in the utilization of networks is careful planning to minimize burst dropping resulting from resource contention. The provision of suitable planning before metadata are sent is critical to improve the rate of successful transmission. In this paper, we attempt to adopt a novel data mining approaches to determining a suitable routing path in the OBS network. Instead of using label switching techniques in DWDM, we proposed the hybrid OBS routing planning on the basics of Cloud Association Rules Algorithm, thus reduced the transmission collision rate in OBS routing. This paper searches for the optimal routing path from all the possible routing paths using cloud association rule approach with Apriori-gen algorithm based on the PACNet topology. The heuristic rules discovered by Apriori-gen algorithm are stored in the Knowledge Base (KB) as references for determining the most suitable routing path. The Knowledge Base of the routing path are set up by means of optimal path routing with the highest successful rate which is mined from the database of historical routing paths using cloud association rules. The experiment results show that the successful rates of routing paths obtained by the proposed routing planning approach can effectively improve the successful rates of transmission.

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