Notice of Violation of IEEE Publication Principles: Latency optimized workload-based Query Routing Tree algorithm in Wireless Sensor Networks

Notice of Violation of IEEE Publication Principles

"Latency Optimized Workload-based Query Routing Tree Algorithm in Wireless Sensor Networks,"
by Yingchi Mao, Xiaofang Li, Yi Liang,
in the Proceedings of the 2nd International Conference on Information Science and Engineering (ICISE), 2010, December 2010, pp.2159-2162

After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE's Publication Principles.

This paper was found to be a near verbatim copy of the paper cited below. The original text was copied without attribution (including appropriate references to the original author(s) and/or paper title) and without permission.

Due to the nature of this violation, reasonable effort should be made to remove all past references to this paper, and future references should be made to the following article:

"ETC: Energy-driven Tree Construction in Woreless Sensor Networks"
by P. Andreou, A. Pamboris, D. Zeinalipour-Yazti, P.K. Chrysanthis, and G. Samaras,
in the Proceedings of the 2009 Tenth International Conference on Mobile Data Management: Systems, Services and Middleware, May 2009, pp. 513-518


Constructing an effective Query Routing Tree is the premise for continuous queries in a Wireless Sensor Networks (WSN). The query routing tree structures can provide sensors with a path to the querying nodes. At present, the data acquisition systems for WSN construct the routing structures in an ad-hoc manner, therefore, there is no guarantee that a given query workload will be distributed equally among all sensors. That leads to data collisions which represent a major source of energy waste. In addition, if the path of query routing is too long, it seriously suffers from the increased data delivery delay. The high end-to-end delay is not acceptable in the delay-constrained applications. We present a data collection timing model for query results acquisition. Based on the timing model, we propose a delay-optimized and workload-based query routing tree construction algorithm, which balances the workload among nodes and optimizes the data delivery delay, thus reducing energy consumption and the data delivery time in the course of data acquisition. The simulation experiments from Intel Research illustrate that the proposed query routing tree algorithm can significantly reduce energy consumption under a variety of conditions and prolong the lifetime of a wireless sensor network.