Exploiting a Prioritized MAC Protocol to Efficiently Compute Min and Max in Multihop Networks

Consider a wireless sensor network (WSN) where a broadcast from a sensor node does not reach all sensor nodes in the network; such networks are often called multihop networks. Sensor nodes take sensor readings but individual sensor readings are not very important. It is important however to compute aggregated quantities of these sensor readings. The minimum and maximum of all sensor readings at an instant are often interesting because they indicate abnormal behavior, for example if the maximum temperature is very high then it may be that a fire has broken out. We propose an algorithm for computing the min or max of sensor reading in a multihop network. This algorithm has the particularly interesting property of having a time complexity that does not depend on the number of sensor nodes; only the network diameter and the range of the value domain of sensor readings matter.

[1]  Rong Zheng,et al.  MAC layer support for group communication in wireless sensor networks , 2005, IEEE International Conference on Mobile Adhoc and Sensor Systems Conference, 2005..

[2]  Y. C. Tay,et al.  Sift: A MAC Protocol for Event-Driven Wireless Sensor Networks , 2006, EWSN.

[3]  Martin P. Clark Appendix 2: ETSI (European Telecommunications Standards Institute) Radio Specifications for Fixed Wireless , 2001 .

[4]  Nuno Pereira,et al.  Disseminating data using broadcast when topology is unknown , 2005, RTSS 2005.

[5]  Björn Andersson,et al.  Static-Priority Scheduling of Sporadic Messages on a Wireless Channel , 2005, OPODIS.

[6]  Haralabos C. Papadopoulos,et al.  Distributed computation of averages over ad hoc networks , 2005, IEEE Journal on Selected Areas in Communications.

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

[8]  Nuno Pereira,et al.  Implementation of a Dominance Protocol for Wireless Medium Access , 2006, 12th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA'06).

[9]  Wei Hong,et al.  Proceedings of the 5th Symposium on Operating Systems Design and Implementation Tag: a Tiny Aggregation Service for Ad-hoc Sensor Networks , 2022 .

[10]  Chen Zhang,et al.  ExScal: elements of an extreme scale wireless sensor network , 2005, 11th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA'05).

[11]  David S. Johnson,et al.  Computers and Intractability: A Guide to the Theory of NP-Completeness , 1978 .

[12]  Tian He,et al.  Feedback control of data aggregation in sensor networks , 2004, 2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601).

[13]  Johannes Gehrke,et al.  Query Processing in Sensor Networks , 2003, CIDR.

[14]  Deborah Estrin,et al.  Impact of network density on data aggregation in wireless sensor networks , 2002, Proceedings 22nd International Conference on Distributed Computing Systems.

[15]  Deborah Estrin,et al.  The impact of data aggregation in wireless sensor networks , 2002, Proceedings 22nd International Conference on Distributed Computing Systems Workshops.

[16]  Aloysius K. Mok,et al.  Distributed Broadcast Channel Access , 1979, Comput. Networks.

[17]  Dawn Xiaodong Song,et al.  SIA: secure information aggregation in sensor networks , 2003, SenSys '03.

[18]  Anthony Rowe,et al.  FireFly: a cross-layer platform for real-time embedded wireless networks , 2007, Real-Time Systems.

[19]  Ramesh Govindan,et al.  Scale Free Aggregation in Sensor Networks , 2004, ALGOSENSORS.