• Sterling Abrahams (graduate student)
• Shinola Agbede (graduate student)
• Yeswanth Polu (graduate student)
• Christopher Gonzalez (BS, graduated in 2020)
• Hung Ngo (MS, graduated in 2020, Senior Software Engineer at Illumina)
• Phillip Aguilera (BS, graduated in 2020)
• Jennifer Ly (BS, graduated in 2020)
• Vincent Tran (BS, graduated in 2020, Ph.D. Student, Computer Science Department, UC Riverside)
• Hugo Flores (MS, graduated in 2019, Software Engineer at Google)
• Yuning Yu (MS, graduated in 2020)
• Shangli Hsu (MS, graduated in 2020)
• Jeff Lutz (MS, graduated in 2019, Senior Software Engineer at Telcoin)
• Alex Ing (MS, graduated in 2018)
• Manar Alqarni (MS, graduated in 2017)
• Janani Janardhanan (MS, Sr. Web Developer at Esri Inc., graduated in 2017)
• Muhannad Alghamdi (MS, graduated in 2017)
• Payman Khani (MS, graduated in 2015, IT Coordinator and Part Time Faculty at CSUDH)

The goal of this project is to integrate compute, data, and middleboxes (MBs), three building blocks of PDDCs, into one framework to achieve optimal cloud resource management. A variety of important problems in PDDCs, including virtual machine (VM) migration and placement, load balancing, flow priority and fault tolerance can all be solved using network flow techniques that provide optimal and efficient resource allocation solutions. In particular, the project identifies a series of new policy-preserving problems that adaptively coordinate compute, data, and MBs, and invents a suite of policy-preserving algorithms that satisfy diverse cloud policies while consuming cloud resources efficiently. The proposed techniques include placing, migrating, replicating, and traffic engineering compute, data, and MBs in the PDDC. The project will compare results with integer linear programming (ILP)-based solutions and extend the approach to multi-objective optimization problems. Expected outcomes are fundamental theories, architectures, algorithms, and protocols for the PDDCs, and prototypes that provide long term policy-preserving cloud services.

Publications:

1. AggVNF: Aggregate VNF Allocation and Migration in Dynamic Cloud Data Centers, Christopher Gonzalez and Bin Tang. Submitted.
2. SAM: Maximizing Service Function Chain Availability in Cloud Data Centers, Abraham Sterling, Bin Tang, and Deng Pan, Proceedings of the IEEE Global Communications Conference (GLOBECOM 2023).
3. Achieving High End-to-End Availability in VNF Networks, Enrique Rodicio, Deng Pan, Jason Liu, Bin Tang, Proceedings of the International Conference on Computer Communications and Networks (ICCCN 2022).
4. Traffic-Optimal Virtual Network Function Placement and Migration in Dynamic Cloud Data Centers, Vincent Tran, Jingsong Sun, Bin Tang, Deng Pan, Proceedings of the 36th IEEE International Parallel & Distributed Processing Symposium (IPDPS 2022).
5. FMDV: Dynamic Flow Migration in Virtual Network Function-Enabled Cloud Data Centers, Phillip Aguilera, Christopher Gonzalez, Bin Tang, Proceedings of the IEEE International Conference on Communications (ICC 2022).
6. Service Function Chain Placement in Cloud Data Center Networks: a Cooperative Multi-Agent Reinforcement Learning Approach, Lynn Gao, Yutian Chen, Bin Tang , Proceedings of the 11th EAI International Conference on Game Theory for Networks (GameNets 2021).
7. Throughput Maximization of Virtual Machine Communications in Bandwidth-Constrained Data Centers, Jeff Lutz, Bin Tang, Christopher Gonzalez, Proceedings of the IEEE Global Communications Conference (GLOBECOM 2021).
8. chieving Virtual Network Function Load-Balanced Flow Migration in Dynamic Cloud Data Centers, Phillip Aguilera, Christopher Gonzalez and Bin Tang, Proceedings of the First Computer Science Conference for CSU Undergraduates (CSCSU 2021).
9. Performance Comparison of Fault-Tolerant Virtual Machine Placement Algorithms in Cloud Data Centers, Christopher Gonzalez and Bin Tang, Proceedings of the First Computer Science Conference for CSU Undergraduates (CSCSU 2021).
10. FT-VMP: Fault-Tolerant Virtual Machine Placement in Cloud Data Centers, Christopher Gonzalez and Bin Tang, Proceedings of the International Conference on Computer Communications and Networks (ICCCN 2020).
11. PAM & PAL: Policy-Aware Virtual Machine Migration and Placement in Dynamic Cloud Data Centers, Hugo Flores, Vincent Tran, and Bin Tang, Proceedings of the IEEE International Conference on Computer Communications (Infocom 2020).
12. LB-MAP: Load-Balanced Middlebox Assignment in Policy Driven Data Centers, Manar Alqarni, Alexander Ing, and Bin Tang, Proceedings of the International Conference on Computer Communications and Networks (ICCCN 2017).
13. Profit-Based File Replication in Data Intensive Cloud Data Centers, Muhannad Alghamdi, Bin Tang, and Yutian Chen, Proceedings of the IEEE International Conference on Communications (ICC 2017).
14. Power-Efficient Virtual Machine Replication in Data Centers, Payman Khani, Bin Tang, Jianchao Han, and Mohsen Beheshti, Proceedings of the IEEE International Conference on Communications (ICC 2016).

This work was supported by the National Science Foundation under Grant No. 1911191.