Delay Minimum Data Collection in the low-duty-cycle wireless sensor networks

In low-duty-cycle wireless sensor networks, wireless nodes usually have two states: active state and dormant state. The necessary condition for a successful wireless transmission is that both the sender and the receiver are awake. In this paper, we study the problem: How fast can raw data be collected from all source nodes to a sink in low-duty-cycle WSNs? To address this, we define the Minimum Data Collection Delay (MDCD) problem, and give both the lower and upper tight bounds on the minimum delay for data collection when interfering links are eliminated. Furthermore, a novel concept, Virtual Grid Network (VGN) is introduced to successfully convert the MDCD problem into max-flow problem, and present a MDCD algorithm enlightened by the Ford-fulkerson max-flow method, which is able to find an optimal solution in polynomial time and achieves the lower bound. Extensive simulations are conducted and the results show that the proposed MDCD algorithm significantly outperforms the Shortest Path Routing algorithm (up to 32%) and achieves the lower bound.

[1]  Yuefeng Ji,et al.  Analysis and experimentation of key technologies in service-oriented optical internet , 2011, Science China Information Sciences.

[2]  Bhaskar Krishnamachari,et al.  Enhancing the Data Collection Rate of Tree-Based Aggregation in Wireless Sensor Networks , 2008, 2008 5th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks.

[3]  Bhaskar Krishnamachari,et al.  Scheduling Algorithms for Tree-Based Data Collection in Wireless Sensor Networks , 2011, Theoretical Aspects of Distributed Computing in Sensor Networks.

[4]  Bo Jiang,et al.  Opportunistic Flooding in Low-Duty-Cycle Wireless Sensor Networks with Unreliable Links , 2009, IEEE Transactions on Computers.

[5]  Bhaskar Krishnamachari,et al.  Fast Data Collection in Tree-Based Wireless Sensor Networks , 2012, IEEE Transactions on Mobile Computing.

[6]  Tian He,et al.  Data forwarding in extremely low duty-cycle sensor networks with unreliable communication links , 2007, SenSys '07.

[7]  Andrea J. Goldsmith,et al.  Energy-delay tradeoffs for data collection in TDMA-based sensor networks , 2005, IEEE International Conference on Communications, 2005. ICC 2005. 2005.

[8]  Yunhao Liu,et al.  Multiple task scheduling for low-duty-cycled wireless sensor networks , 2011, 2011 Proceedings IEEE INFOCOM.

[9]  Ying Zhang,et al.  Distributed Minimal Time Convergecast Scheduling in Wireless Sensor Networks , 2006, 26th IEEE International Conference on Distributed Computing Systems (ICDCS'06).

[10]  Viktor K. Prasanna,et al.  Energy-latency tradeoffs for data gathering in wireless sensor networks , 2004, IEEE INFOCOM 2004.

[11]  Do Young Eun,et al.  Smart sleep: Sleep more to reduce delay in duty-cycled wireless sensor networks , 2011, 2011 Proceedings IEEE INFOCOM.

[12]  Bhaskar Krishnamachari,et al.  Delay efficient sleep scheduling in wireless sensor networks , 2005, Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies..

[13]  Hui Song,et al.  Routing in intermittently connected sensor networks , 2008, 2008 IEEE International Conference on Network Protocols.