Award Abstract # 0534531
Algorithms and Metrics for New Generation Data Stream Management Systems

NSF Org: IIS
Division of Information & Intelligent Systems
Recipient: UNIVERSITY OF PITTSBURGH - OF THE COMMONWEALTH SYSTEM OF HIGHER EDUCATION
Initial Amendment Date: February 28, 2006
Latest Amendment Date: February 26, 2010
Award Number: 0534531
Award Instrument: Continuing Grant
Program Manager: Gia-Loi Le Gruenwald
IIS
 Division of Information & Intelligent Systems
CSE
 Directorate for Computer and Information Science and Engineering
Start Date: March 1, 2006
End Date: February 28, 2011 (Estimated)
Total Intended Award Amount: $0.00
Total Awarded Amount to Date: $516,000.00
Funds Obligated to Date: FY 2006 = $500,000.00
FY 2009 = $16,000.00
History of Investigator:
  • Panos Chrysanthis (Principal Investigator)
    panos@cs.pitt.edu
  • Kirk Pruhs (Co-Principal Investigator)
  • Alexandros Labrinidis (Co-Principal Investigator)
Recipient Sponsored Research Office: University of Pittsburgh
4200 FIFTH AVENUE
PITTSBURGH
PA  US  15260-0001
(412)624-7400
Sponsor Congressional District: 12
Primary Place of Performance: University of Pittsburgh
4200 FIFTH AVENUE
PITTSBURGH
PA  US  15260-0001
Primary Place of Performance
Congressional District:
12
Unique Entity Identifier (UEI): MKAGLD59JRL1
Parent UEI:
NSF Program(s): Info Integration & Informatics,
DATA MANAGEMENT SYSTEMS
Primary Program Source: app-0106 
01000910DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 7496, 9216, 9218, 9251, HPCC
Program Element Code(s): 736400, 748500
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.070

ABSTRACT

IIS-0534531
Panos K. Chrysanthis
University of Pittsburgh

Algorithms and Metrics for New Generation Data Stream Management Systems

The goal of this project is to design a new generation of data stream management systems (DSMSs), with equal emphasis on optimizing performance and enhancing functionality. New generation DSMSs simplify the development of a wide range of monitoring applications, with diverse requirements. Monitoring applications are core components in scientific exploration, health alerting, environmental monitoring, and business support systems. This project reexamines all four critical components of a DSMS: query scheduler, load shedder, query processor, and data dissemination modules. The two key innovations of this project are: (1) it looks at how these four modules can be integrated to work in combination, instead of making in isolation decisions that have a significant impact on the overall performance; and (2) this project formalizes QoS/QoD metrics for DSMSs
and develops algorithms designed to optimize these metrics. In addition, the project plans include the analytical and experimental evaluation of the proposed algorithms and also the implementation and evaluation of a prototype system. This project provides opportunities for both graduate and undergraduate students to participate in the development of cutting edge technology. Results of this research, including software, data, and publications, will be disseminated via the project Web site at http://db.cs.pitt.edu/streams

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

Note:  When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).

Some links on this page may take you to non-federal websites. Their policies may differ from this site.

(Showing: 1 - 10 of 15)
A. Bonifati, P. K. Chrysanthis, A. M. Ouksel and K.U. Sattler. "Distributed Databases and Peer-to-Peer Databases: Past and Present" ACM Sigmod Record , v.37(1) , 2008 , p.5 http://doi.acm.org/10.1145/1374780.1374781
Kirk Pruhs "Competitive online scheduling for server systems" ACM Sigmetrics Performance Evaluation Review , 2007
Kirk Pruhs, Patchrawat Uthaisombut, Gerhard J. Woeginger "Getting the best response for your erg" ACM Transactions on Algorithms , v.4 , 2008
Kirk Pruhs, Rob van Stee, Patchrawat Uthaisombut "Speed Scaling of Tasks with Precedence Constraints" Theory of Computing Systems , v.1 , 2008 , p.67
Mohamed A. Sharaf, Panos K. Chrysanthis, Alexandros Labrinidis, and Kirk Pruhs "Algorithms and Metrics for Processing Multiple Heterogeneous Continuous Queries" ACM Transactions on Database Systems , v.33(1) , 2008 , p.5.1 http://doi.acm.org/10.1145/1331904.1331909
N. Bansal, T. Kimbrel, and K. Pruhs "Speed scaling to manage energy and temperature" Journal of the ACM , 2007
Nikhil Bansal, David P. Bunde, Ho-Leung Chan, Kirk Pruhs "Average Rate Speed Scaling" Algorithmica , v.60 , 2011 , p.877
Nikhil Bansal, Ho-Leung Chan, Kirk Pruhs "Competitive Algorithms for Due Date Scheduling" Algorithmica , v.59 , 2011 , p.569
Nikhil Bansal, Ho-Leung Chan, Kirk Pruhs "Speed scaling with a solar cell" Theoretical Computer Science , v.410 , 2009 , p.4580
Nikhil Bansal, Kirk Pruhs, Clifford Stein "Speed Scaling for Weighted Flow Time" SIAM Journal of Computing , v.39 , 2009 , p.1294
Nikhil Bansal, Tracy Kimbrel, Kirk Pruhs "Speed Scaling to manage energy and temperature" Journal of the ACM , v.1 , 2007
(Showing: 1 - 10 of 15)

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

Print this page

Back to Top of page