Energy-Efficient Transaction Processing

Overview  |  Funding  |  People  |  Links  |  Publications  |  Related Publications


Compared to early Transaction Processing (TP) systems, today’s TP systems have seen dramatic changes in both application requirements and underlying hardware support. As such, existing algorithms and design decisions hardly reflect reality and require revisiting them. However, more importantly, future generation TP systems must also necessarily evolve because of the emergence of energy efficiency as a first order design consideration.

This project pursues This project is an early venture into a very new area, seeking to identify the most appropriate metrics for energy efficiency (QoE) in TP environments, the most appropriate ways to combine these energy efficiency metrics with existing quality of service (QoS) metrics and the most appropriate ways to specify any trade-off between QoE and QoS. Project plans also include the development of new scheduling algorithms and new TP system components that optimize a particular metric under different hardware configurations, as well as the experimental evaluation of the developed algorithms on simulation platforms and on real, state-of-the-art hardware.

This exploration has the potential to have a great impact in the development of new data management technologies. It is expected to advance the knowledge and understanding of the interplay among modern hardware components and facilitate the development of next generation TP systems that exploit new hardware features with the potential to achieve significant energy savings. This understanding could help formulate the foundations of the important area of energy-efficient data management, and thus contribute to the societal goal of energy conservation and sustainability.



NSF IIS-1050301 (PI: Panos K. Chrysanthis; Co-PIs: Alexandros Labrinidis) NSF Abstract



Faculty: Collaborators
  • Shimin Chen CSD CMU (previously @ Intel Labs Pittsburgh)
Graduate students:
  • Sean Snyder
Undergraduate students
  • Katlyn Daniluk (Summer Intern 2010)

Additional Links


Project papers


    [ 2019 | 2016 | 2013 | 2011 ]


  1. Daniel Petrov, Rakan Alseghayer, Panos K. Chrysanthis, Mitigating Congestion Using Environment Protective Dynamic Traffic Orchestration, IEEE International Workshop on Mobility Data Analytics for Smart Cities Joint with Mobile Data Management 2019 (MDACS '19), 593-598, Hong Kong, SAR, China, June 2019, Co-located with IEEE MDM 2019.

  2. Donald Kline, Jr., Nikolas Parshook, Xiaoyu Ge, Erik Brunvand, Rami Melhem, Panos K. Chrysanthis, Alex K. Jones, GreenChip: A tool for evaluating holistic sustainability of modern computing systems, Sustainable Computing: Informatics and Systems (SUCIS), 22:322-332, June 2019, (Accepted and published on-line on 10/10/2017).

  3. 2016

  4. Donald Kline, Jr., Nikolas Parshook, Xiaoyu Ge, Erik Brunvand, Rami Melhem, Panos K. Chrysanthis, Alex K. Jones, Holistically Evaluating the Environmental Impacts in Modern Computing Systems, The Seventh International Green and Sustainable Computing Conference (IGSC'16), 1-8, November 2016.

  5. 2013

  6. Guy Gadola, Panos K. Chrysanthis, Harnessing off-grid renewable energy, 2013 International Conference on Renewable Energy Research and Applications (ICRERA'13), 927 - 931, Madrid, Spain, October 2013.

  7. 2011

  8. Sean M. Snyder, Shimin Chen, Panos K. Chrysanthis, Alexandros Labrinidis, QMD: Exploiting Flash for Energy Efficient Disk Arrays, Proc. of Seventh International Workshop on Data Management on New Hardware (DaMoN'11), pp. 41-49, Athens, Greece, June 2011, held in conjunction with the 2011 ACM SIGMOD/PODS Conference, DOI:10.1145/1995441.1995447.

  9. Shimin Chen, Panos K. Chrysanthis, Alexandros Labrinidis, Exploiting Flash for Energy Efficient Disk Arrays, NSF Workshop on Sustainable Energy-Efficient Data Management (SEEDM'11), pp. 1-3, Arlington, Virginia, May 2011.


Related publications


    [ 2014 | 2012 | 2011 ]


  1. Marian K. Iskander, Tucker Trainor, Dave W. Wilkinson, Adam J. Lee, Panos K. Chrysanthis, Balancing Performance, Accuracy, and Precision for Secure Cloud Transactions, IEEE Transactions on Parallel & Distributed Systems (IEEE TPDS), 25(2):417-426, February 2014, Date of on-line publication: 02 July 2013.

  2. 2012

  3. Lory Al Moakar, Panos K. Chrysanthis, Christine Chung, Shenoda Guirguis, Alexandros Labrinidis, Panayiotis Neophytou, Kirk Pruhs, Auction-based Admission Control for Continuous Queries in a Multi-Tenant DSMS, International Journal of Next-Generation Computing (IJNGC), 3(3):247-273, November 2012.

  4. 2011

  5. Panayiotis Neophytou, Jesse Szwedko, Mohamed A. Sharaf, Panos K. Chrysanthis, Alexandros Labrinidis, Optimizing the Energy Consumption of Continuous Query Processing with Mobile Clients, Proc. of the 12th International IEEE Conference on Mobile Data Management (MDM'11), (1):98-103, Lulea, Sweden, June 2011, DOI:10.1109/MDM.2011.71.

  6. Marian K. Iskander, Dave W. Wilkinson, Adam J. Lee, Panos K. Chrysanthis, Enforcing Policy and Data Consistency of Cloud Transactions, Proc. of the 2nd ICDCS International Workshop on Security and Privacy on the Cloud (ICDCS-SPCC'11), pp. 253-262, Minneapolis, Minnesota, June 2011, DOI:10.1109/ICDCSW.2011.42.