Network calculus based QoS analysis of network coding in Cluster-tree wireless sensor network

In resource-limited wireless sensor networks(WSNs), network resource will run out soon due to communication of mass redundant data. We employ Network Coding as an effective in-network processing strategy to reduce the data transmission amount. With this concern, a comprehensive Network-Calculus based analytical framework for Cluster-tree WSNs involving network coding is established in this paper. To specify, we firstly derive the service curve for sensor node performing network coding; then some useful performance expressions like input/output arrival curve, buffering requirements and end-to-end delay are calculated; finally, to show the effectiveness and superiority of our proposed analytical framework, we demonstrate how to apply the analytical framework to a special IEEE802.15.4/Zigbee protocol. Indeed, numerical results show that network coding does improve buffer requirement and end-to-end delay compared with classical scheduling strategy.

[1]  Florin Ciucu,et al.  On expressing networks with flow transformations in convolution-form , 2011, 2011 Proceedings IEEE INFOCOM.

[2]  C. Fraboul,et al.  Guaranteed Packet Delays with Network Coding , 2008, 2008 5th IEEE Annual Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks Workshops.

[3]  Yong Liu,et al.  Stochastic Network Calculus , 2008 .

[4]  Carlo Fischione,et al.  Performance Analysis of GTS Allocation in Beacon Enabled IEEE 802.15.4 , 2009, 2009 6th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks.

[5]  Eduardo Tovar,et al.  Real-Time Communications Over Cluster-Tree Sensor Networks with Mobile Sink Behaviour , 2008, 2008 14th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications.

[6]  Rene L. Cruz,et al.  A calculus for network delay, Part II: Network analysis , 1991, IEEE Trans. Inf. Theory.

[7]  Eduardo Tovar,et al.  Modeling and Worst-Case Dimensioning of Cluster-Tree Wireless Sensor Networks , 2006, 2006 27th IEEE International Real-Time Systems Symposium (RTSS'06).

[8]  Weijia Jia,et al.  Performance of Acyclic Stochastic Networks with Network Coding , 2011, IEEE Transactions on Parallel and Distributed Systems.

[9]  Weijia Jia,et al.  Performance modeling of stochastic networks with network coding , 2009, 2009 Workshop on Network Coding, Theory, and Applications.

[10]  Rudolf Ahlswede,et al.  Network information flow , 2000, IEEE Trans. Inf. Theory.

[11]  Eduardo Tovar,et al.  GTS allocation analysis in IEEE 802.15.4 for real-time wireless sensor networks , 2006, Proceedings 20th IEEE International Parallel & Distributed Processing Symposium.

[12]  Markus Fidler,et al.  Survey of deterministic and stochastic service curve models in the network calculus , 2009, IEEE Communications Surveys & Tutorials.

[13]  Xue Liu,et al.  End-to-End Delay Analysis in Wireless Network Coding: A Network Calculus-Based Approach , 2011, 2011 31st International Conference on Distributed Computing Systems.

[14]  Utz Roedig,et al.  Sensor Network Calculus - A Framework for Worst Case Analysis , 2005, DCOSS.