The Caltech Rigorous Systems Research Group
The Rigorous Systems Research Group (RSRG, pronounced "resurge") studies the design of computer systems, but it's not your ordinary systems group. RSRG is distinguished by its rigorous/analytic approach to design. The group develops new theory, uses theoretical results to provide new design tools and methodologies, puts these new design tools and methodologies into practice, and develops new theory motivated by practice, thus closing the loop.
The research process of RSRG is centered around three principles, the combination of which distinguish RSRG from most other CS systems groups:
- Theory is the foundation. Everybody in the group develops new theoretical results that inform system design and performance analysis.
- Get your hands dirty. Everybody in the group builds, or uses measurements from, systems and prototypes.
- Be truly interdisciplinary. Everybody in the group uses ideas from disciplines outside computer science (such as operations research, economics, and control theory) or develops systems that are used in varied disciplines (such as space exploration or control of power grids).
This word cloud was generated via wordle using the RSRG web site as an input.
Research in RSRG
Research in RSRG combines development of theory about system design with development of new tools and techniques to apply to system design and implementation. The research areas studied in the group emphasize an integrated approach to practical applications and fundamental theory.
Application Domains
- Network protocols
- Network coding
- Sensor networks
- The Web
- Wireless networks
- Distributed systems
- Power management
- Server farms
- Software reliability
- Rapid data mining
- Mobile agents
- Sponsored search
Analytic Techniques
- Stochastic modeling
- Optimization
- Game theory
- Machine learning
- Probabilistic reasoning
- Information theory
- Queueing theory
- Control theory
- Temporal logics
- Model checking
- Automatic theorem proving
RSRG is unique because of the interplay between these two sets of interests. Every member of the group works in at least one area from both columns.
All members of RSRG work with each other. For convenience, RSRG also has sub-groups/labs that work on more focused problems. Each project includes a 5-10 RSRG faculty/students. We highlight a few of these projects here. To find out about other ongoing projects, please look at the personal pages for the group members.
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Adaptive systems that learn and reason under uncertainty
Headed by Prof. Andreas Krause, the lab focuses on active information acquisition, learning and decision making in large, distributed and uncertain domains, such as sensor networks and the Web. The lab uses and develops new techniques in machine learning, Bayesian inference, graphical models, decision theory and optimization. Example applications include robotic environmental exploration, securing water distribution networks, information gathering on the web, activity recognition and intelligent building automation. -
Infospheres
Headed by Prof. Mani Chandy, Infospheres The Infospheres lab carries out research on theory, design methodology, and prototype development of sense and respond (S&R) systems. Sensing the environment and responding appropriately to opportunities and threats is a matter of survival for organizations and organisms. A zebra survives when it senses and flees a stalking lion and conserves energy by not fleeing from imagined threats. Similarly, an organization thrives when it senses and responds to its environment in a suitable timely fashion. -
NetLab
Headed by Prof. Steven Low, NetLab pursues an integrated approach where theory, algorithm, implementation, experimentation, and infrastructure influence and inform each other intimately. Research in NetLab has focused on the control and optimization of communications networks and protocols, and has recently spawned a startup called FastSoft. -
PerfLab
Headed by Prof. Adam Wierman, PerfLab focuses on providing better system design through measurement and modeling. The group works on a variety of topics including wireless networks, server farm architectures, and energy efficient computing. The goal is to combine system measurement with analytic modeling to develop new design insights in these applications.
