Low-cost Optical Network Unit Deployment Strategy with Survivability Aware in Hybrid Optical-wireless Broadband Access Networks

WANG Ruyan; LIU Hui; WU Dapeng; ZHANG Yan; XIANG Luoyong

doi:10.11999/JEIT150872

Volume 38 Issue 6

Jun. 2016

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Article Navigation > Journal of Electronics & Information Technology > 2016 > 38(6): 1354-1361

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Citation:

WANG Ruyan, LIU Hui, WU Dapeng, ZHANG Yan, XIANG Luoyong. Low-cost Optical Network Unit Deployment Strategy with Survivability Aware in Hybrid Optical-wireless Broadband Access Networks[J]. Journal of Electronics & Information Technology, 2016, 38(6): 1354-1361. doi: 10.11999/JEIT150872

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Low-cost Optical Network Unit Deployment Strategy with Survivability Aware in Hybrid Optical-wireless Broadband Access Networks

doi: 10.11999/JEIT150872

Funds:

The National Natural Science Foundation of China (61371097), Chongqing Natural Science Foundation (CSTC2013JJB40006), Youth Talents Training Project of Chongqing Science Technology Commission (CSTC2014KJRC- QNRC40001)

Received Date: 2015-07-21
Rev Recd Date: 2016-02-19
Publish Date: 2016-06-19

Abstract

Abstract

There is a contradiction between the degree of survivability and the cost of deployment in Hybrid Optical-Wireless Broadband Access Networks (HOWBAN). To improve the network resources utilization, a low- cost Optical Network Unit (ONU) deployment strategy is proposed. According to the deployment of wireless functions in the network, the degree of network survivability and the deployment are considered in the optimization process of vector evaluated binary particle swarm optimization. Furthermore, to deploy the network with low cost while at the same time guaranteeing a high degree of survivability, the selecting of optical-network-units can be decided dynamically by the evolution of particle. The results show that low-cost ONU deployment strategy can effectively improve the network survivability, and reduce network cost.
- Hybrid Optical-Wireless Broadband Access Networks (HOWBAN),
- Survivability,
- Low-cost,
- Particle swarm algorithm

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References(20)

References

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