Request Control of Web Service-Based Sampling System With Multiple Smart Sensors

In a Web service-based sampling system (WSSS) with multiple smart sensors, where the smart sensors request the sampling-commands (SCs) from the Web server with polling mechanism, and the Web server picks up the targeted estimates (TEs) from all the estimates received, higher polling frequency and more estimate-submissions enable the Web server to obtain all TEs (ATE) with larger probability, enjoying less delays, while suffering more network traffic. Therefore, how to minimize the network traffic while satisfying the acceptable delays and probability of the server obtaining ATE arises as an interesting issue. To address this issue, this article first proposes a Markov decision process (MDP) framework to formulate the request process of WSSS, then explores out the optimal polling frequency and probability in the polynomial time for the smart sensors’ requests, and finally proposes a probability threshold-based algorithm to guide the smart sensors to decide the polling frequency and whether to request the SCs. Theoretical results, simulations, and field experiments document and illustrate its performance.