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In heterogeneous network environments with performance variations present, complex distributed applications, such as distributed visual tracking applications, are desired to adapt themselves and to adjust their resource demands dynamically, in response to fluctuations in either end system or network resources. By such adaptations, they are able to preserve the user-perceptible critical QoS parameters, and trade off non-critical ones. However, correct decisions on adaptation timing and scale, such as determining data rate transmitted from the server to clients in an application, depend on accurate observations of system states, such as quantities of data in transit or arrived at the destination.
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