Rumor routing algorthim for sensor networks

Advances in micro-sensor and radio technology will enable small but smart sensors to be deployed for a wide range of environmental monitoring applications. In order to constrain communication overhead, dense sensor networks call for new and highly efficient methods for distributing queries to nodes that have observed interesting events in the network. A highly efficient data-centric routing mechanism will offer significant power cost reductions [17], and improve network longevity. Moreover, because of the large amount of system and data redundancy possible, data becomes disassociated from specific node and resides in regions of the network [10][7][8]. This paper describes and evaluates through simulation a scheme we call Rumor Routing, which allows for queries to be delivered to events in the network. Rumor Routing is tunable, and allows for tradeoffs between setup overhead and delivery reliability. It's intended for contexts in which geographic routing criteria are not applicable because a coordinate system is not available or the phenomenon of interest is not geographically correlated.

[1]  Brad Karp,et al.  Greedy Perimeter Stateless Routing for Wireless Networks , 2000 .

[2]  Deborah Estrin,et al.  Geography-informed energy conservation for Ad Hoc routing , 2001, MobiCom '01.

[3]  Deborah Estrin,et al.  ASCENT: Adaptive Self-Configuring sEnsor Networks Topologies , 2002, Proceedings.Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies.

[4]  Deborah Estrin,et al.  Directed diffusion: a scalable and robust communication paradigm for sensor networks , 2000, MobiCom '00.

[5]  Wendi Heinzelman,et al.  Energy-efficient communication protocol for wireless microsensor networks , 2000, Proceedings of the 33rd Annual Hawaii International Conference on System Sciences.

[6]  Deborah Estrin,et al.  Geographical and Energy Aware Routing: a recursive data dissemination protocol for wireless sensor networks , 2002 .

[7]  Deborah Estrin,et al.  Large-scale Network Discovery: Design Tradeoffs in Wireless Sensor Systems , 2001 .

[8]  Devika Subramanian,et al.  Ants and Reinforcement Learning: A Case Study in Routing in Dynamic Networks , 1997, IJCAI.

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

[10]  Keith Marzullo,et al.  Gossip versus Deterministic Flooding: Low Message Overhead and High Reliability for Broadcasting on Small Networks , 1999 .

[11]  Gregory J. Pottie,et al.  Instrumenting the world with wireless sensor networks , 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).

[12]  Marco Dorigo,et al.  Ant system: optimization by a colony of cooperating agents , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[13]  A.A. Abidi,et al.  Power-conscious design of wireless circuits and systems , 2000, Proceedings of the IEEE.

[14]  Deborah Estrin,et al.  GHT: a geographic hash table for data-centric storage , 2002, WSNA '02.

[15]  Brad Karp,et al.  GPSR: greedy perimeter stateless routing for wireless networks , 2000, MobiCom '00.