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Missing data occurs when values of variables in a dataset are not stored. Estimating these missing values is a significant step during the data cleansing phase of a big data management approach. The reason of missing data may be due to nonresponse or omitted entries. If these missing data are not handled properly, this may create inaccurate results during data analysis. Although a traditional method such as maximum likelihood method extrapolates missing values, this paper proposes a bioinspired method based on the behavior of birds, specifically the Kestrel bird. This paper describes the behavior and characteristics of the Kestrel bird, a bioinspired approach, in modeling an algorithm to estimate missing values. The proposed algorithm (KSA) was compared with WSAMP, Firefly, and BAT algorithm. The results were evaluated using the mean of absolute error (MAE). A statistical test (Wilcoxon signed-rank test and Friedman test) was conducted to test the performance of the algorithms. The results of Wilcoxon test indicate that time does not have a significant effect on the performance, and the quality of estimation between the paired algorithms was significant; the results of Friedman test ranked KSA as the best evolutionary algorithm.

Choreography-driven microservice composition has provided a better way to integrate components in the Cyber-physical-Social System (CPSS). Choreography is a global contract that specifies interactions among microservices participating in a composite service. After modeling a choreography, a problem arises here is whether the choreography specification at design time can be implemented correctly by generated microservices that interact with each other via exchanging messages. In this paper, we propose a novel approach for choreography analysis. Specifically, a choreography is specified using a Labeled Transition Systems (LTSs); then, the microservices participating in a composite service can be generated from the given choreography via projection and ε-remove; finally, the analysis of the choreography can be checked for both synchronous and asynchronous compositions using refinement checking. Our approach is completely automated under the support of our developed tool and the Process Analysis Toolkit (PAT) tool.