The Virtual Pheromone Communication Primitive

We propose a generic communication primitive designed for sensor networks. Our primitive hides details of network communication while retaining sufficient programmer control over the communication behavior of an application; it is designed to ease the burden of writing application-specific communication protocols for efficient, long-lived, fault-tolerant, and scalable applications. While classical network communication methods expect high-reliability links, our primitive works well in highly unreliable environments without needing to detect and prune unreliable links. Our primitive resembles the chemical markers used by many biological systems to solve distributed problems (pheromones). We develop and analyze the performance of an implementation of this primitive called Virtual Pheromone (VP). We demonstrate that VP can attain performance comparable to classical methods for applications such as sleep scheduling, routing, flooding, and cluster formation.

[1]  H. Van Dyke Parunak,et al.  Pheromone learning for self-organizing agents , 2005, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[2]  Isao Shimoyama,et al.  Synthesis of pheromone-oriented emergent behavior of a silkworm moth , 1996, Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems. IROS '96.

[3]  Songwu Lu,et al.  PEAS: a robust energy conserving protocol for long-lived sensor networks , 2002, 10th IEEE International Conference on Network Protocols, 2002. Proceedings..

[4]  Jonathan W. Hui,et al.  T 2 : A Second Generation OS For Embedded Sensor Networks , 2005 .

[5]  David A. Maltz,et al.  Dynamic Source Routing in Ad Hoc Wireless Networks , 1994, Mobidata.

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

[7]  David E. Culler,et al.  TOSSIM: accurate and scalable simulation of entire TinyOS applications , 2003, SenSys '03.

[8]  James McLurkin.  Algorithms for Distributed Sensor Networks , 2000 .

[9]  S. Sitharama Iyengar,et al.  Distributed adaptation methods for wireless sensor networks , 2003, GLOBECOM '03. IEEE Global Telecommunications Conference (IEEE Cat. No.03CH37489).

[10]  Ahmed Helmy,et al.  RUGGED: RoUting on finGerprint Gradients in sEnsor Networks , 2004, The IEEE/ACS International Conference on Pervasive Services.

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

[12]  Songwu Lu,et al.  PEAS: a robust energy conserving protocol for long-lived sensor networks , 2003, 23rd International Conference on Distributed Computing Systems, 2003. Proceedings..

[13]  Young-Bae Ko,et al.  A novel gradient approach for efficient data dissemination in wireless sensor networks , 2004, IEEE 60th Vehicular Technology Conference, 2004. VTC2004-Fall. 2004.

[14]  J. Broch,et al.  Dynamic source routing in ad hoc wireless networks , 1998 .

[15]  Deborah Estrin,et al.  Tenet: An Architecture for Tiered Embedded Networks , 2005 .

[16]  Cem Ersoy,et al.  Multiple sink network design problem in large scale wireless sensor networks , 2004, 2004 IEEE International Conference on Communications (IEEE Cat. No.04CH37577).

[17]  Andrea J. Goldsmith,et al.  Design challenges for energy-constrained ad hoc wireless networks , 2002, IEEE Wirel. Commun..

[18]  David E. Culler,et al.  The Emergence of Networking Abstractions and Techniques in TinyOS , 2004, NSDI.

[19]  David W. Payton,et al.  Pheromone Robotics , 2001, Auton. Robots.

[20]  L. Szumel,et al.  Towards a mobile agent framework for sensor networks , 2005, The Second IEEE Workshop on Embedded Networked Sensors, 2005. EmNetS-II..