A reliable cooperative and distributed management for wireless industrial monitoring and control

This paper is concerned with the analysis, design and validation of a reliable management strategy for industrial monitoring and control over wireless sensor network (WSN). First, we investigate the interactions between contention resolution and congestion control mechanisms in Wireless Industrial Sensor Network (briefly WISN). An extensive set of simulations are performed in order to quantify the impacts of several network parameters (i.e. buffer, sensors reporting rate) on the overall network performance (i.e. reliability, packet losses). This calls for cross-layer mechanisms for efficient data delivery over WISN. Second, a reliable sink resource allocation strategy based on log-utility fairness criteria is proposed. It is shown that the resource sink manager can plan strategies to better allocate the available resource among competing sensors. Finally, the analysis, design and validation of a reliable sinks cooperative control for WISN are introduced. A sufficient condition for wireless network stability in presence of multiple sinks and heterogeneous sensors with different time delays is given and it is used for network parameters design. The stability condition and the resulting cooperative control performance in terms of fairness, link utilization, packet losses, reliability and latency are validated by Matlab/Simulink-based simulator TrueTime, which facilitates co-simulation of controller task execution in real-time kernels and in the wireless network environment. Copyright © 2009 John Wiley & Sons, Ltd.

[1]  Albert-László Barabási,et al.  Statistical mechanics of complex networks , 2001, ArXiv.

[2]  C. Desoer,et al.  On the generalized Nyquist stability criterion , 1979, 1979 18th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes.

[3]  Xiang Li,et al.  Pinning a complex dynamical network to its equilibrium , 2004, IEEE Trans. Circuits Syst. I Regul. Pap..

[4]  H. Ozbay,et al.  A solution to the robust flow control problem for networks with multiple bottlenecks , 2001, Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228).

[5]  Richard M. Murray,et al.  Consensus problems in networks of agents with switching topology and time-delays , 2004, IEEE Transactions on Automatic Control.

[6]  Amy L. Murphy,et al.  Middleware to support sensor network applications , 2004, IEEE Network.

[7]  Donald F. Towsley,et al.  Analysis and design of controllers for AQM routers supporting TCP flows , 2002, IEEE Trans. Autom. Control..

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

[9]  Karl Henrik Johansson,et al.  On decentralized negotiation of optimal consensus , 2008, Autom..

[10]  Alvise Bonivento,et al.  Rialto: a bridge between description and implementation of control algorithms for wireless sensor networks , 2005, EMSOFT.

[11]  Frank Kelly,et al.  Rate control for communication networks: shadow prices, proportional fairness and stability , 1998, J. Oper. Res. Soc..

[12]  B. Otis,et al.  PicoRadios for wireless sensor networks: the next challenge in ultra-low power design , 2002, 2002 IEEE International Solid-State Circuits Conference. Digest of Technical Papers (Cat. No.02CH37315).

[13]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[14]  Stephen P. Boyd,et al.  Fast linear iterations for distributed averaging , 2003, 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475).