Welcome to the AI-SCC&BigData Group

Welcome to AI-SCC&BigData group home page. AI-SCC&BigData group conducts research in the areas related to service and cloud computing, and develops artificial intelligent methods to solve the problems. Our mission is to explore and develop innovative AI-driven solutions that enhance the efficiency, scalability, and intelligence of cloud and service computing and big data analysis in popular areas like resource allocation, service composition, workflow scheduling in cloud computing, social network analysis, query processing. The group has been working in the service and cloud computing and big data areas since 2009 and has published their research outputs in top venues in the field.

Selected Papers:

• Y. Yang, A. Chen. H. Ma, S. Hartmann, M. Zhang: Enhancing Generalization in Genetic Programming Hyper-heuristics through Mini-batch Sampling Strategies for Dynamic Workflow Scheduling, Information Sciences, 2024 (accepted) (CORE Tier A)
• Y. Yang, A. Chen. H. Ma, S. Hartmann, M. Zhang: Dual-Tree Genetic Programming with Adaptive Mutation for Dynamic Workflow Scheduling in Cloud Computing, IEEE Transactions on Evolutionary Computation (TEVC), 2024 (accepted) (CORE Tier A*) TEVC_Yang.pdf
• T. Shi, H. Ma, G. Chen and S. Hartmann, "Auto-Scaling Containerized Applications in Geo-Distributed Clouds" in IEEE Transactions on Service Computing (TSC), 2023. (accepted) (CORE Tier A*)
• Sadeghiram, Soheila, Hui Ma, and Gang Chen. "Multi-objective distributed Web service composition—A link-dominance driven evolutionary approach." Future Generation Computer Systems (2023).https://doi.org/10.1016/j.future.2023.01.001
• C. Wang, H. Ma, G. Chen, S. Hartmann, "Using an Estimation of Distribution Algorithm to Achieve Multitasking Semantic Web Service Composition", IEEE Transactions on Evolutionary Computation, 2022 [PDF] (CORE Tier A*)
• Tao Shi, Hui Ma, Gang Chen, and Sven Hartmann, "Cost-Effective Web Application Replication and Deployment in Multi-Cloud Environment," IEEE Transactions on Parallel and Distributed Systems (TPDS), 2021. doi: 10.1109/TPDS.2021.3133884. (CORE Tier A*)
• S. Sadeghiram, H. Ma and G. Chen, Priority-based Selection of Individuals in Memetic Algorithms for Distributed Data-intensive Web Service compositions, in IEEE Transactions on Services Computing, 2021. doi: 10.1109/TSC.2021.3066322. (CORE Tier A*)
• C. Wang, H. Ma, G. Chen, S. Hartmann, Memetic EDA-Based Approaches to QoS-Aware Automated Semantic Web Service Composition, IEEE Transactions on Evolutionary Computation (TEVC), 2021. doi: 10.1109/TEVC.2021.3127633 (CORE Tier A*)
• T. Shi, H. Ma, G. Chen and S. Hartmann, "Location-Aware and Budget-Constrained Service Deployment for Composite Applications in Multi-Cloud Environment," in IEEE Transactions on Parallel and Distributed Systems (TPDS), vol.31, pp. 1954-1969, 2020. (CORE Tier A*)
• B. Tan, H. Ma, Y. Mei, M. Zhang: A Cooperative Coevolution Genetic Programming Hyper-Heuristic Approach for On-line Resource Allocation in Container-based Clouds, IEEE Transactions on Cloud Computing (TCC), 2020, doi: 10.1109/TCC.2020.3026338
• T. Shi, H. Ma, G. Chen, S. Hartmann: Location-Aware and Budget-Constrained Application Replication and Deployment in Multi-Cloud Environment, IEEE International Conference on Web Services (ICWS), 2020 (ARC/ERA Tier A).
• B. Tan, H. Ma, Y. Mei, M. Zhang, Evolutionary Multi-Objective Optimization for Web Service Location Allocation Problem, IEEE Transactions on Services Computing (TSC), Volume: PP Issue: 99, 2018. (CORE Tier A*)

A complete list of publications from the group, together with source code and datasets can be found at here