HybridLQI: Hybrid MultihopLQI for Improving Asymmetric Links in Wireless Sensor Networks

The article proposes HybridLQI to improve the performance of MultihopLQI in the asymmetrical wireless links sensor networks. Every node can maintain the number of messages it sends to each of its neighbours and how many of them are acknowledged, the packet loss percentage over the links can be calculated. Link Quality Indicator (LQI) is used to estimate the downlink channel. Therefore, without adding any extra cost to the network, the bi-directional channel quality can be calculated. Asymmetrical links are created by setting the Base Station transmitting at higher power than the other nodes. This approach in a dense network improves message received percentage by up to 20% for the whole network. For sparse asymmetrical links networks with nodes in straight line and having direct line of sight, this approach improves the packet reception percentage by up to 350% for the node which is 3 hops away from the Base Station. All the results are based on the experiments performed on the real platform.

[1]  W.B. Heinzelman,et al.  Experimental investigation of radio performance in wireless sensor networks , 2006, 2006 2nd IEEE Workshop on Wireless Mesh Networks.

[2]  Philip Levis,et al.  Understanding the causes of packet delivery success and failure in dense wireless sensor networks , 2006, SenSys '06.

[3]  Riadh Dhaou,et al.  Experimental Study: Link Quality and Deployment Issues in Wireless Sensor Networks , 2009, Networking.

[4]  F. Golatowski,et al.  Weighted Centroid Localization in Zigbee-based Sensor Networks , 2007, 2007 IEEE International Symposium on Intelligent Signal Processing.

[5]  Philip Levis,et al.  Collection tree protocol , 2009, SenSys '09.

[6]  Monique Becker,et al.  Effect of Topology on the Performance of Mobile Heterogeneous Sensor Networks , 2007 .

[7]  David E. Culler,et al.  Towards a Sensor Network Architecture: Lowering the Waistline , 2005, HotOS.

[8]  Zhen Song,et al.  Resource-Aware and Link Quality Based Routing Metric for Wireless Sensor and Actor Networks , 2007, 2007 IEEE International Conference on Communications.

[9]  David E. Culler,et al.  Taming the underlying challenges of reliable multihop routing in sensor networks , 2003, SenSys '03.

[10]  Marco Zuniga,et al.  Analyzing the transitional region in low power wireless links , 2004, 2004 First Annual IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks, 2004. IEEE SECON 2004..

[11]  David E. Culler,et al.  Telos: enabling ultra-low power wireless research , 2005, IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005..

[12]  Philip Levis,et al.  Four-Bit Wireless Link Estimation , 2007, HotNets.

[13]  Ramesh Govindan,et al.  Understanding packet delivery performance in dense wireless sensor networks , 2003, SenSys '03.

[14]  A. Gupta,et al.  Understanding topology challenges in the implementation of wireless sensor network for cold chain , 2010, 2010 IEEE Radio and Wireless Symposium (RWS).

[15]  Philippe Jacquet,et al.  Optimized Link State Routing Protocol (OLSR) , 2003, RFC.

[16]  Robert Tappan Morris,et al.  a high-throughput path metric for multi-hop wireless routing , 2005, Wirel. Networks.