Lifetime-aware data collection in Wireless Sensor Networks

In WSNs (Wireless Sensor Networks), sensor nodes are typically battery powered. As a result, network lifetime becomes a major optimization objective in the design of a WSN. We investigate the problem of lifetime-aware data collection in a WSN with only one base station. We propose an efficient distributed algorithm for constructing a routing DAG (Directed Acyclic Graph), namely, R-DAG, for data collection. Our algorithm makes use of a shortest path DAG and adds sibling edges to balance the loads of the base station's children, prolonging the network lifetime. The simulation results show that the R-DAG significantly outperforms the shortest path DAG. For the 60 instances of WSNs generated by using Cooja simulator, the average improvement and the maximum improvement in network lifetime achieved by the R-DAG over the shortest path DAG are 42% and 99.5%, respectively.

[1]  Qin Wang,et al.  A Realistic Power Consumption Model for Wireless Sensor Network Devices , 2006, 2006 3rd Annual IEEE Communications Society on Sensor and Ad Hoc Communications and Networks.

[2]  Radha Poovendran,et al.  Maximizing Network Lifetime of Broadcasting Over Wireless Stationary Ad Hoc Networks , 2005, Mob. Networks Appl..

[3]  Ness B. Shroff,et al.  On the Construction of a Maximum-Lifetime Data Gathering Tree in Sensor Networks: NP-Completeness and Approximation Algorithm , 2008, IEEE INFOCOM 2008 - The 27th Conference on Computer Communications.

[4]  Hui Wu,et al.  Lifetime aware deployment of k base stations in WSNs , 2012, MSWiM '12.

[5]  Young-Jin Kim,et al.  Geographic routing made practical , 2005, NSDI.

[6]  Ping-Lang Yen,et al.  A load balancing algorithm based on probabilistic multi-tree for wireless sensor networks , 2011, 2011 Fifth International Conference on Sensing Technology.

[7]  Cheng-Long Chuang,et al.  A Probablistic Load-Balancing Convergecast Tree Algorithm for Heterogeneous Wireless Sensor Networks , 2012, 2012 IEEE 14th International Conference on High Performance Computing and Communication & 2012 IEEE 9th International Conference on Embedded Software and Systems.

[8]  Lynn Choi,et al.  DAG-based multipath routing for mobile sensor networks , 2011, ICTC 2011.

[9]  Yi-Jing Chu,et al.  The first order load-balanced algorithm with static fixing scheme for centralized WSN system in outdoor environmental monitoring , 2009, 2009 IEEE Sensors.

[10]  Jiannong Cao,et al.  An Efficient Algorithm for Constructing Maximum lifetime Tree for Data Gathering Without Aggregation in Wireless Sensor Networks , 2010, 2010 Proceedings IEEE INFOCOM.

[11]  Wendi Heinzelman,et al.  Proceedings of the 33rd Hawaii International Conference on System Sciences- 2000 Energy-Efficient Communication Protocol for Wireless Microsensor Networks , 2022 .

[12]  Guihai Chen,et al.  Maximizing lifetime for the shortest path aggregation tree in wireless sensor networks , 2011, 2011 Proceedings IEEE INFOCOM.

[13]  Weifa Liang,et al.  Online Data Gathering for Maximizing Network Lifetime in Sensor Networks , 2007, IEEE Transactions on Mobile Computing.

[14]  Richard Han,et al.  A node-centric load balancing algorithm for wireless sensor networks , 2003, GLOBECOM '03. IEEE Global Telecommunications Conference (IEEE Cat. No.03CH37489).

[15]  Guihai Chen,et al.  Building Maximum Lifetime Shortest Path Data Aggregation Trees in Wireless Sensor Networks , 2014, TOSN.

[16]  Kenneth A. Berman,et al.  Dynamic state-based routing for load balancing and efficient data gathering in wireless sensor networks , 2010, 2010 International Symposium on Collaborative Technologies and Systems.

[17]  Andreas Willig,et al.  Protocols and Architectures for Wireless Sensor Networks , 2005 .

[18]  Yacine Challal,et al.  A new weighted shortest path tree for convergecast traffic routing in WSN , 2012, 2012 IEEE Symposium on Computers and Communications (ISCC).

[19]  Yi-Jing Chu,et al.  Application of load-balanced tree routing algorithm with dynamic modification to centralized wireless sensor networks , 2009, 2009 IEEE Sensors.