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Sensor networks are distributed networks made up of small sensing devices equipped with processors, memory, and short-range wireless communication. They differ from the conventional computer networks in that they have severe energy constraints, redundant low-rate data, and a plethora of information flows. Many aspects of sensor networks, such as routing, preservation of battery power, adaptive self-configuration, etc., have already been studied in previous papers, e.g., [(W. Heinzelman, J. Kulik, and H Balakrishnan, 1999), (N. Bulusu, D. Estrin, L. Girod, and J. Heidelann, 20001), (D. Estrin, 2001)]. However, to the best knowledge of the authors, the area of sensor network quality of service (QoS) remains largely open. This is a rich area because sensor deaths and sensor replenishments make it difficult to specify the optimum number of sensors (this being the service quality that we address in this paper) that should be sending information at any given time. In this paper we present an amalgamation of QoS feedback and sensor networks. We use the idea of following the base station to communicate QoS information to each of the sensors using a broadcast channel and we use the mathematical paradigm of the Gur Game to dynamically adjust to the optimum number of sensors. The result is a robust sensor network that allows the base station to dynamically adjust the resolution of the QoS it receives from the sensors, depending on varying circumstances.