The National Science Foundation (NSF) awarded a 5-year, $111,723 Project Grant under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070) to Stony Brook University. The grant supports research and development of structured learning and optimization solutions to efficiently manage concurrent graph-based computing workloads in wireless edge cloud networks. Key objectives include:
- Designing structured reinforcement learning algorithms to schedule and optimize graph-based computing jobs in the wireless edge cloud and minimize service latency.
- Studying methods to maximize the output of individual graph-based computing jobs given allocated network resources.
- Developing adaptive resource provisioning strategies to make the edge cloud infrastructure cost-effective for supporting graph-based workloads.
The project aims to bridge the gap between advanced distributed computing platforms and wireless network constraints by leveraging structured learning and optimization approaches. It also includes educational and outreach activities to engage students, particularly from underrepresented groups, in this interdisciplinary research area.
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