认知无线网具有业务感知功能的新型路由协议

doi:10.3969/j.issn.1001-2400.2012.05.001

Abstract

Abstract:

In existing routing protocols for wireless networks, congestion control schemes are taken into consideration only after congestion has happened, and these reactive manners may result in more packets loss, longer end-to-end delay and more overhead. This paper proposes a traffic-aware routing protocol(TACR) which can be used in cognitive wireless networks. By the use of prediction methods based on wiener processes and local probe information, TACR perceives traffic state changes quickly and accurately, thereby optimizing network routing and effectively balancing the network load. Meanwhile, distributed Q-learning mechanism is introduced into TACR to dynamically adjust the route lifetime according to network conditions, and the routing adaptability for traffic distribution is improved. Under the reasonable definition of network overhead, we analyze the performance of TACR in the typical scene, and prove its superiority. Simulation results show that the TACR routing protocol shortens the average end-to-end delay by 40%, reduces packets loss by 10% and network control overhead by 27% compared with the existing routing protocol in heavy load environments.

Key words: cognitive network, traffic-aware, network overhead

CLC Number:

TP393

References

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Traffic-aware routing protocol for the cognitive wireless network

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