Dependable Computing Systems Laboratory

The Dependable Computing Systems Laboratory (DCSL) at Purdue University investigates the question of how to build dependable, heterogeneous, large-scale distributed systems.

“Dependability meets Data Analytics, and at Large Scales”

The above sums up our current research direction. We work on software systems to enable them to perform their functionality in the face of natural and malicious failures. We apply and adapt data analytic techniques to work with the noise of computer systems and at large system scales. Current application domains come from distributed software systems, embedded systems, cellular systems, and bioinformatics.


Latest News

  1. November 2020: Our project to use Bluetooth proximity estimation to keep social distancing in manufacturing facilities and campus labs hits prime time. We presented this work as a poster paper at Sensys. Kudos to undergraduate DCSL-ers Kyle and Kavit!
  2. October 2020: The work on our NSF SaTC project on how behavioral biases of humans affect how we protect interconnected computing systems gets a paper into AsiaCCS. The work is led by Mustafa and joint work with Shreyas Sundaram (ECE) and Daniel Woods and Tim Cason (Econ), plus Ohio State, IIT Kharagpur, and QCRI.
  3. September 2020: Our project on security in distributed autonomous systems with the Army Research Lab (ARL) kicks off. This is a 5-year project and involves 5 faculty members: Saurabh Bagchi (PI), Somali Chaterji, Mung Chiang, David Inouye, and from Princeton, Prateek Mittal. With this, we join the Army’s AI Innovation Institute (A2I2) program. We are actively hiring graduate researchers and Research Scientists to join us as part of this project. [ Post ]
  4. September 2020: Papers are accepted to Sensys (approximate computer vision on embedded and mobile platforms), ACM Computing Surveys (survey on firmware emulation for security testing), and NeurIPS (security anomaly detection among sensor data). [ WWW ]
  5. August 2020: Our project on a public repository of computer system usage and failure data from production clusters (at Purdue, Illinois, and Texas) gets funded by NSF. We are hiring a Graduate RA and a Software Engineer/Research Scientist for this three-year project. [ Post ]
  6. March-May 2020: The largest repository on computer system usage and failure data, called Fresco, with logs from Purdue, UIUC, and UT Austin, now has a paper — at DSN 2020. [ WWW ] [ NSF news story ] [ Purdue news story ] [ Talk video ]

Research Theme at DCSL

Since many business and life critical functions are being performed by distributed systems, they need to be dependable while meeting their performance goals. Thus, there is need for smart error detection, diagnosis, and recovery protocols. Since many of these systems operate on vast amounts of data and the patterns of errors or normal operation are approximate and noisy, we have to adapt leading-edge machine learning tools to these systems problems. There is also need for architectures that can combine dependability and security aspects without significantly degrading performance and do this in an adaptive manner, adapting to different user requirements and different runtime environments. This is our mission at DCSL.

Our application contexts come from various domains, many from our industrial colleagues. These include: security-critical enterprise (with Missile Defense Agency, Northrop Grumman and Lockheed Martin), mobile and cloud platforms (in collaboration with AT&T and IBM), large-scale scientific clusters and applications (in collaboration with Lawrence Livermore National Lab and Argonne National Lab), and cyber physical systems (in collaboration with GE Global Research Center and Sandia).

DCSL is the founding lab within the Purdue College of Engineering Center for Resilient Infrastructures, Systems, and Processes (CRISP). DCSL is the co-lead in the WHIN consortium, leading the thrust on “IoT Systems and Networking”.

Last modified: December 11, 2020