In this paper, we have modeled the performance of an scalable proxy virtualization framework to support an appropriate level of Quality of Service (QoS) for delay sensitive applications in cloud-based large scale sensor networks. The proposed model leverages the functionalities of Constrained Application Protocol (CoAP) to expose an standard interface for transparently decoupling of the applications from servers and ensuring the implementation of the custom QoS metrics through virtualization techniques. The model, combined with prediction-based dynamic resource allocation approach, enables the computation of the number of requests that can be supported for a given service rate and required QoS. It also features the evaluation of different performance metrics, particularly, the probability distribution of the response time and the ability to identify the optimal balance between the resource cost and the service performance. The numerical results obtained from the proposed analytical model can be used to help design and optimize industrial cloud-based sensing systems.

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