Minimum latency joint scheduling and routing in wireless sensor networks

Wireless sensor networks are expected to be used in a wide range of applications from environment monitoring to event detection. The key challenge is to provide energy efficient communication; however, latency remains an important concern for many applications that require fast response. In this paper, we address the important problem of minimizing average communication latency for the active flows while providing energy-efficiency in wireless sensor networks. As the flows in some wireless sensor network can be long-lived and predictable, it is possible to design schedules for sensor nodes so that nodes can wake up only when it is necessary and asleep during other times. Clearly, the routing layer decision is closely coupled to the wakeup/sleep schedule of the sensor nodes. We formulate a joint scheduling and routing problem with the objective of finding the schedules and routes for current active flows with minimum average latency. By constructing a novel delay graph, the problem can be solved optimally by employing the M node-disjoint paths algorithm under FDMA channel model. We further present extensions of the algorithm to handle dynamic traffic changes and topology changes in wireless sensor networks.

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

[2]  Robert E. Tarjan,et al.  A quick method for finding shortest pairs of disjoint paths , 1984, Networks.

[3]  Deborah Estrin,et al.  Habitat monitoring: application driver for wireless communications technology , 2001, CCRV.

[4]  J. Elson,et al.  Fine-grained network time synchronization using reference broadcasts , 2002, OSDI '02.

[5]  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..

[6]  Weifa Liang,et al.  Constructing minimum-energy broadcast trees in wireless ad hoc networks , 2002, MobiHoc '02.

[7]  Bhaskar Krishnamachari,et al.  An adaptive energy-efficient and low-latency MAC for data gathering in wireless sensor networks , 2004, 18th International Parallel and Distributed Processing Symposium, 2004. Proceedings..

[8]  Randy H. Katz,et al.  Measuring and Reducing Energy Consumption of Network Interfaces in Hand-Held Devices (Special Issue on Mobile Computing) , 1997 .

[9]  Mihail L. Sichitiu,et al.  Cross-layer scheduling for power efficiency in wireless sensor networks , 2004, IEEE INFOCOM 2004.

[10]  Ramesh Govindan,et al.  Understanding packet delivery performance in dense wireless sensor networks , 2003, SenSys '03.

[11]  Charles E. Perkins,et al.  Ad-hoc on-demand distance vector routing , 1999, Proceedings WMCSA'99. Second IEEE Workshop on Mobile Computing Systems and Applications.

[12]  Huang Lee,et al.  Wakeup scheduling in wireless sensor networks , 2006, MobiHoc '06.

[13]  Deborah Estrin,et al.  Medium access control with coordinated adaptive sleeping for wireless sensor networks , 2004, IEEE/ACM Transactions on Networking.

[14]  Cauligi Raghavendra,et al.  An Adaptive Energy-Efficient and Low-Latency MAC for Data Gathering in Sensor Networks , 2003 .

[15]  Satish Kumar,et al.  Next century challenges: scalable coordination in sensor networks , 1999, MobiCom.

[16]  J. W. Suurballe Disjoint paths in a network , 1974, Networks.

[17]  Ramesh Bhandari,et al.  Optimal physical diversity algorithms and survivable networks , 1997, Proceedings Second IEEE Symposium on Computer and Communications.

[18]  Martin Nilsson,et al.  Investigating the energy consumption of a wireless network interface in an ad hoc networking environment , 2001, Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213).

[19]  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..

[20]  Anantha Chandrakasan,et al.  Low-power wireless sensor networks , 2001, VLSI Design 2001. Fourteenth International Conference on VLSI Design.

[21]  Nitin H. Vaidya,et al.  A wakeup scheme for sensor networks: achieving balance between energy saving and end-to-end delay , 2004, Proceedings. RTAS 2004. 10th IEEE Real-Time and Embedded Technology and Applications Symposium, 2004..

[22]  Nitin H. Vaidya,et al.  Minimizing energy consumption in sensor networks using a wakeup radio , 2004, 2004 IEEE Wireless Communications and Networking Conference (IEEE Cat. No.04TH8733).

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

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