面向终端个性化服务的模糊垂直切换算法

马彬; 张文静; 谢显中

doi:10.11999/JEIT160839

面向终端个性化服务的模糊垂直切换算法

doi: 10.11999/JEIT160839

基金项目:

国家自然科学基金(61271259, 61301123, 61471076)，重庆市基础与前沿研究计划(cstc2015jcyjA40047)，重庆邮电大学博士启动基金(A2014-10, A2015-16)

计量
- 文章访问数: 1247
- HTML全文浏览量: 143
- PDF下载量: 450
- 被引次数: 0
出版历程
- 收稿日期: 2016-08-15
- 修回日期: 2017-02-08
- 刊出日期: 2017-06-19

Individualization Service Oriented Fuzzy Vertical Handover Algorithm

Funds:

The National Natural Science Foundation of China (61271259, 61301123, 61471076), The Foundation and Advanced Research Program of Chongqing (cstc2015jcyjA40047), The Doctoral Start-up Fund of Chongqing University of Posts and Telecommunications (A2014-10, A2015-16)

摘要

摘要: 在异构无线网络中，针对终端不同类型的应用在服务质量(QoS)需求上的差异，该文提出一种面向终端个性化服务的模糊垂直切换算法。该算法从以下两个方面提高切换性能：首先在网络发现阶段，通过预测候选网络在切换时刻的负载状态，对候选网络进行筛选；然后在切换判决阶段，根据每类应用对QoS参数的不同需求范围设计不同的隶属度函数。仿真结果表明，该算法能有效降低切换阻塞率，提高系统吞吐量，并能根据终端的应用类型合理地选择切换网络，满足了终端的个性化服务需求。
- 异构无线网络 /
- 垂直切换 /
- 网络负载预测 /
- 隶属度函数
Abstract: Considering the differences in Quality of Service (QoS) requirements of different application classes in heterogeneous wireless networks, this paper proposes an individualization service oriented fuzzy vertical handover algorithm. The handover performance is improved from the following two aspects. Firstly, in the network discovery phase, the candidate networks are sifted by predicting the network loads in handover execution. Secondly, in the handover decision phase, different membership functions are designed according to the different QoS requirements of each application class. The simulation results show that the proposed algorithm can reduce the blocking probability, improve the system throughput, select the target network reasonably, and meet the QoS requirements of terminal individualization service.
- Heterogeneous wireless networks /
- Vertical handover /
- Network loads prediction /
- Membership function

HTML全文

参考文献(19)

FERNANDES S and KARMOUCH A. Management architectures in wireless networks: A comprehensive survey and future directions[J]. IEEE Communications Surveys Tutorials, 2012, 14(1): 45-63. doi: 10.1109/SURV.2011. 082010.00099.

AHMED A, BOULAHIA L M, and GAITI D. Enabling vertical handover decisions in heterogeneous wireless networks: A state-of-the-art and a classification[J]. IEEE Communications Surveys Tutorials, 2013, 16(2): 776-811. doi: 10.1109/SURV.2013.082713.00141.

LEE H, KIM D, CHUNG B, et al. Adaptive hysteresis using mobility correlation for fast handover[J]. IEEE Communications Letters, 2008, 12(2): 152-154. doi: 10.1109/ LCOMM.2008.071316.

SINGH N P and SINGH B. Vertical handoff decision in 4G wireless networks using multi attribute decision making approach[J]. Wireless Networks, 2013, 20(5): 1203-1211. doi: 10.1007/s11276-013-0670-1.

SHEN W and ZENG Q A. Cost-function-based network selection strategy in integrated wireless and mobile networks[J]. IEEE Transactions on Vehicular Technology, 2008, 57(6): 3778-3788. doi: 10.1109/TVT.2008.917257.

马彬, 谢显中, 廖晓峰. 车辆异构网络中预测垂直切换算法[J]. 电子与信息学报, 2015, 37(4): 874-880. doi: 10.11999/ JEIT140845.

MA B, XIE X Z, and LIAO X F. Prediction vertical handoff algorithm in vehicle heterogeneous network[J]. Journal of Electronics Information Technology, 2015, 37(4): 874-880. doi: 10.11999/JEIT140845.

潘甦, 梁宇, 刘胜美. 一种基于移动趋势量化的多属性垂直切换判决算法[J]. 电子与信息学报, 2016, 38(2): 269-275. doi: 10.11999/JEIT150443.

PAN S, LIANG Y, and LIU S M. A multi-attribute vertical handoff decision algorithm based on motion trend quantification[J]. Journal of Electronics Information Technology, 2016, 38(2): 269-275. doi: 10.11999/JEIT150443.

LI L, MA L, XU Y, et al. Motion adaptive vertical handoff in cellular/WLAN heterogeneous wireless network[J]. The Scientific World Journal, 2014, 14(3): 1-7. doi: 10.1155/ 2014/341038.

ALOTAIBI N M and ALWAKEEL S S. A neural network based handover management strategy for heterogeneous networks[C]. 2015 IEEE 14th International Conference on Machine Learning and Applications, Miami, FL, USA, 2015: 1210-1214. doi: 10.1109/ICMLA.2015.65.

NARAYANAN V A, RAJESWARI A, and SURESHKUMAR V. Service-adaptive fuzzy multi criteria based intelligent vertical handover decision algorithm for heterogeneous wireless networks[C]. International Conference on Artificial Intelligence and Evolutionary Algorithms in Engineering Systems, Coimbatore, India, 2015: 297-304. doi: 10.1007/ 978-81-322-2126-5_33.

KUSTIAWAN I and CHI K. Handoff decision using a kalman filter and fuzzy logic in heterogeneous wireless networks[J]. IEEE Communications Letters, 2015, 19(12): 2258-2261. doi: 10.1109/LCOMM.2015.2495212.

KALEEM F, MEHBODNIYA A, ISLAM A, et al. Dynamic target wireless network selection technique using fuzzy linguistic variables[J]. China Communications, 2013, 10(1): 1-16. doi: 10.1109/CC.2013.6457526.

KANTUBUKTA V, MAHESHWARI S, MAHAPATRA S, et al. Energy and quality of service aware FUZZY-technique for order preference by similarity to ideal solution based vertical handover decision algorithm for heterogeneous wireless networks[J]. The Institution of Engineering and Technology Networks, 2013, 2(3): 103-114. doi: 10.1049/iet-net.2012. 0183.

CHAMODRAKAS I and MARTAKOS D. A utility-based fuzzy TOPSIS method for energy efficient network selection in heterogeneous wireless networks[J]. Applied Soft Computing, 2012, 12(7): 1929-1938. doi: 10.1016/j.asoc.2012. 04.016.

杨剑波. 多模智能终端在异构无线网络中的垂直切换技术研究[D]. [博士论文], 解放军信息工程大学, 2013: 19-38.

YANG J B. Research on vertical handover for multi-mode intelligent terminal in heterogeneous wireless networks[D]. [Ph.D. dissertation], PLA Information Engineering University, 2013: 19-38.

TANIUCHI K, CORPORATION T, OHBA Y, et al. IEEE 802.21: Media independent handover: Features, applicability, and realization[J]. IEEE Communications Magazine, 2009, 47(1): 112-120. doi: 10.1109/MCOM.2009.4752687.

施引文献

资源附件(0)

访问统计