Cluster aware mobility encounter dataset enlargement
Institute of Electrical and Electronics Engineers Inc.
The recent emerging fields in data processing and manipulation has facilitated the need for synthetic data generation. This is also valid for mobility encounter dataset generation. Synthetic data generation might be useful to run research-based simulations and also create mobility encounter models. Our approach in this paper is to generate a larger dataset by using a given dataset which includes the clusters of people. Based on the cluster information, we created a framework. Using this framework, we can generate a similar dataset that is statistically similar to the input dataset. We have compared the statistical results of our approach with the real dataset and an encounter mobility model generation technique in the literature. The results showed that the created datasets have similar statistical structure with the given dataset. © 2019 IEEE.
This conference paper is not available at CUD collection. The version of scholarly record of this conference paper is published in 2019 15th International Wireless Communications & Mobile Computing Conference (IWCMC) (2019), available online at: https://ieeexplore.ieee.org/document/8766720.
Data processing, Dataset, Internet of Things (IoT), Mobility, Synthetic data, Carrier mobility, Data processing, Mobile computing, Statistical structures, Synthetic data generations, Data handling
Haldar, R., Bacanli, S. S., Aloqaily, M., Mnaouer, A. B., & Turgut, D. (2019). Cluster aware mobility encounter dataset enlargement. In 2019 15th International Wireless Communications and Mobile Computing Conference, IWCMC 2019 (pp. 1918–1922). https://doi.org/10.1109/IWCMC.2019.8766720