CL-ILD: A Cross Layer Interference-Load and Delay Aware Routing Metric for Multi-Radio Wireless Mesh Network

被引:7
作者
Narayan, D. G. [1 ]
Uma, M. [1 ]
Pavan, G. [1 ]
Suraj, S. [1 ]
机构
[1] BVB Coll Engn & Technol, Hubli 580031, India
来源
2013 SECOND INTERNATIONAL CONFERENCE ON ADVANCED COMPUTING, NETWORKING AND SECURITY (ADCONS 2013) | 2013年
关键词
Wireless Mesh Networks; Routing Metrics; QoS; ETX; CL-ILD; AODV;
D O I
10.1109/ADCONS.2013.54
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, we propose a new cross layer routing metric that estimates the interference, load and delay of a link efficiently for multi-radio Wireless Mesh Networks (WMNs) to improve the performance. WMNs are an emerging technology and are used as a backhaul networks to connect to the internet. These networks employ Multi-Channel Multiple Radio (MCMR) mechanisms to achieve high performance. But, performance of WMNs still depends on the routing protocols and its routing metrics to support QoS of multimedia applications. Also, the presence of MCMR leads to intra-flow and interflow interference. In this context, several routing metrics have been proposed to improve the routing performance by considering interference and other link quality parameters. However, most routing metrics lack the efficient monitoring mechanisms for considering the interference, load and delay together in order to support the routing algorithms. In this paper, a new routing metric called Cross-Layer Interference, Load and Delay aware metric (CL-ILD) is proposed. Our metric finds the optimal path by measuring the intra-flow interference at network layer, inter-flow interference at physical layer, load at MAC layer, and delay by computing Expected Transmission Time at network layer. We have implemented our metric in AODV protocol using NS2 simulator. The performance of our metric is compared with metric of interference and channel diversity (MIND) and iAWARE using QoS parameters throughput and end-to- end delay. The results reveal that the proposed metric performs significantly better than MIND and iAWARE.
引用
收藏
页码:181 / 186
页数:6
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