Mechanism and Analysis on Fine-Grain Gradient Sinking Model in Wireless Sensor Networks

Data sinking is one of the typical transmission patterns in WSN(wireless sensor network) . There is inherent unbalanced traffic load distribution in such funnel like transmission. A case in hop-based sinking(HBS) model is found more intricate than simple thought that inner nodes burden more forwarding tasks,showing the inverse direction within the same hop level comparing with global trend. With a simple weighted average mechanism,a continuous gradient parameter is introduced,which will be dedicated to instructing how to forward data to sink in place of hop count,namely fine-grain gradient sinking(FGS) . Through traffic analysis and detailed simulation,in FGS model the network turns out to be smoother on traffic load distribution and more efficient on data forwarding than that in HBS model.

[1]  Guillermo A. Francia.  A Wireless Sensor Network , 2003, International Conference on Wireless Networks.

[2]  Anantha P. Chandrakasan,et al.  An application-specific protocol architecture for wireless microsensor networks , 2002, IEEE Trans. Wirel. Commun..

[3]  Songwu Lu,et al.  A scalable solution to minimum cost forwarding in large sensor networks , 2001, Proceedings Tenth International Conference on Computer Communications and Networks (Cat. No.01EX495).

[4]  Jun Luo,et al.  Joint mobility and routing for lifetime elongation in wireless sensor networks , 2005, Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies..

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

[6]  Robert Tappan Morris,et al.  a high-throughput path metric for multi-hop wireless routing , 2003, MobiCom '03.

[7]  Sang Hyuk Son,et al.  Efficiency Centric Communication Model for Wireless Sensor Networks , 2006, Proceedings IEEE INFOCOM 2006. 25TH IEEE International Conference on Computer Communications.

[8]  Han Bing,et al.  Study on Bottleneck Nodes in Wireless Sensor Networks , 2006 .

[9]  Mo Chen,et al.  The Importance of Data Compression for Energy Efficiency in Sensor Networks , 2003 .

[10]  Li Jian-Zhong,et al.  Concepts, Issues and Advance of Sensor Networks and Data Management of Sensor Networks , 2003 .

[11]  Qing Li,et al.  A Distributed Energy-Efficient Clustering Algorithm for Heterogeneous Wireless Sensor Networks , 2006 .

[12]  Bhaskar Krishnamachari,et al.  Impact of energy depletion and reliability on wireless sensor network connectivity , 2004, SPIE Defense + Commercial Sensing.

[13]  Gregory J. Pottie,et al.  Wireless integrated network sensors , 2000, Commun. ACM.

[14]  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..

[15]  Ahmed Helmy,et al.  Energy-efficient forwarding strategies for geographic routing in lossy wireless sensor networks , 2004, SenSys '04.

[16]  Deborah Estrin,et al.  Complex Behavior at Scale: An Experimental Study of Low-Power Wireless Sensor Networks , 2002 .