NSF Org:	CNS Division Of Computer and Network Systems
Recipient:	TRUSTEES OF BOSTON UNIVERSITY
Initial Amendment Date:	March 20, 2025
Latest Amendment Date:	March 20, 2025
Award Number:	2440334
Award Instrument:	Continuing Grant
Program Manager:	Daniel Andresen dandrese@nsf.gov  (703)292-2177 CNS  Division Of Computer and Network Systems CSE  Directorate for Computer and Information Science and Engineering
Start Date:	April 1, 2025
End Date:	March 31, 2030 (Estimated)
Total Intended Award Amount:	$676,807.00
Total Awarded Amount to Date:	$252,604.00
Funds Obligated to Date:	FY 2025 = $252,604.00
History of Investigator:	Vasiliki Kalavri (Principal Investigator) vkalavri@bu.edu
Recipient Sponsored Research Office:	Trustees of Boston University 1 SILBER WAY BOSTON MA  US  02215-1703 (617)353-4365
Sponsor Congressional District:	07
Primary Place of Performance:	Trustees of Boston University 1 SILBER WAY BOSTON MA  US  02215-1703
Primary Place of Performance Congressional District:	07
Unique Entity Identifier (UEI):	THL6A6JLE1S7
Parent UEI:
NSF Program(s):	CSR-Computer Systems Research
Primary Program Source:	01002526DB NSF RESEARCH & RELATED ACTIVIT 01002728DB NSF RESEARCH & RELATED ACTIVIT 01002829DB NSF RESEARCH & RELATED ACTIVIT 01002930DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s):	1045, 9102
Program Element Code(s):	735400
Award Agency Code:	4900
Fund Agency Code:	4900
Assistance Listing Number(s):	47.070

ABSTRACT

This project introduces HoloStream, a novel system that enables the efficient analysis of large data streams on different types of computing platforms. The project?s novelties include (i) a customizable design that can be tailored to various deployment settings, (ii) mechanisms to tune system configuration according to workload changes, and (iii) techniques to manage resources automatically. The project's broader significance and importance are the potential to make data streaming tools more accessible to everyday users, enabling new applications in areas like smart cities, healthcare, personalized recommendations, and tracking disease outbreaks.

The project involves three sets of tasks that address challenges in adaptive resource management and efficient reconfiguration of streaming applications on dataflow systems. First, the investigator designs an adaptive distributed runtime system that can be tailored to the diverse workload characteristics of streaming applications and achieve practical performance on heterogeneous deployments. Second, she introduces online adaptation mechanisms to achieve consistent and correct reconfiguration of streaming applications without downtime. Third, the investigator develops a heterogeneity-aware optimization framework to enable self-management of streaming applications. Project results have the potential to lower the deployment costs of streaming technology for users and providers alike, and inform future research on self-management policies for long-running applications, beyond streaming analytics.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Please report errors in award information by writing to: awardsearch@nsf.gov.