Kien T. Le

I am a graduate student in the Department Computer Science at Rutgers University. My advisors are Ricardo Bianchini and Thu D. Nguyen. I am a member of Panic Lab and Dark Lab. My research focuses on building cost-aware load distribution framework to reduce energy consumption and promote renewable energy.

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Publications:

• GreenHadoop: Leveraging Green Energy in Data-Processing Frameworks
  Inigo Goiri, Kien Le, Thu D. Nguyen, Jordi Guitart, Jordi Torres and Ricardo Bianchini
  To appear In Proceedings of Eurosys 2012.
• GreenSlot: Scheduling Energy Consumption in Green Datacenters
  Inigo Goiri, Kien Le, Md. E. Haque, Ryan Beauchea, Thu D. Nguyen, Jordi Guitart, Jordi Torres and Ricardo Bianchini
  In Proceedings of Super Computing (SC11), November 2011.
• Reducing Electricity Cost Through Virtual Machine Placement in High Performance Computing Clouds
  Kien Le, Jingru Zhang, Jiandong Meng, Ricardo Bianchini, Thu D. Nguyen and Yogesh Jaluria
  In Proceedings of Super Computing (SC11), November 2011.
• Intelligent Placement of Datacenters for Internet Services [Demo]
  Inigo Goiri, Kien Le, Jordi Guitart, Jordi Torres, and Ricardo Bianchini
  In Proceedings of the 31st Int'l Conference on Distributed Computing Systems (ICDCS 2011), June 2011.
• Capping the Brown Energy Consumption of Internet Services at Low Cost [Presentation]
  Kien Le, Ozlem Bilgir, Ricardo Bianchini, Margaret Martonosi, Thu D. Nguyen
  In Proceedings of the First International Green Computing Conference (IGCC'10), August 2010.

  Winner of the Best Paper Award.
• Managing the Cost, Energy Consumption, and Carbon Footprint of Internet Services [Poster]
  Kien Le, Ozlem Bilgir, Ricardo Bianchini, Margaret Martonosi, Thu D. Nguyen
  Poster abstract, In Proceeding of the ACM SIGMETRICS, June 2010.
• Cost- and Energy-Aware Load Distribution Across Data Centers [Presentation]
  Kien Le, Ricardo Bianchini, Margaret Martonosi, Thu D. Nguyen
  In Proceeding of the Workshop on Power Aware Computing and Systems (HotPower), October 2009.
• Managing the Cost, Energy Consumption, and Carbon Footprint of Internet Services
  Kien Le, Ozlem Bilgir, Ricardo Bianchini, Margaret Martonosi, Thu D. Nguyen
  Technical Report DCS--TR--639, Dept. of Computer Science, Rutgers University, July 2008.
• A Cost-Effective Distributed File Service with QoS Guarantees [Presentation]
  Kien Le, Ricardo Bianchini, Thu D. Nguyen
  In Proceedings of the 8th International Middleware Conference (Middleware 2007), November 2007.

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Projects:

• Rutgers Mini Green Datacenter with Ricardo Bianchini and Thu Nguyen
  Exploring scheduling and energy management infrastructure in a green datacenter.
  • Building a free-air cooled datacenter comprising a cluster powered by solar and wind energy.
  • Designing models for predicting the varying availability of green energy.
  • Exploring scheduling paradigms (e.g., pre-computation) to maximize usage of green energy.

• Multi-Datacenter Internet Services with Ricardo Bianchini, Thu Nguyen, and Margaret Martonosi
  Built a framework to distribute load across geographically distributed data centers that minimizes energy costs while satisfying service level agreements.
  • Accounted for server and cooling energy usage and datacenter peak power demand.
  • Leveraged differences in energy costs arising from different timezones, variable electricity prices, and outside temperatures.
  • Explored several optimization and heuristic-based approaches.
  • Explored the implications of caps on brown energy consumption.

• WanStore with Ricardo Bianchini and Thu Nguyen
  Built a framework to distribute requests across multiple back-end services that minimizes cost while satisfying service level agreements.
  • Considered back-end services with distinct performance vs. cost characteristics.
  • Explored two optimization approaches and showed that a hybrid strategy was the best.
  • Built a file system that optimizes over multiple third-party block storage Web services.

• Wayfinder Federated File System with Thu Nguyen and Richard Martin
  Built semantic directories, which are searches persistently embedded in a file system namespace.
  • Explored machine learning techniques for improving relevancy of matches.
  • Participated in evaluation of different distributed search algorithms.
  • Built general content parsing infrastructure.

• Resource profiling in JikesRvm with Thu Nguyen and Barbara Ryder
  Built a fine-grain profiling framework that uses the processor hardware counters.
  • Ported the JikesRvm hardware monitoring package to the Intel platform.
  • Improved the package API to allow finer grain measurements.
  • Officially contributed package back to the project (http://jikesrvm.org/Acknowledgments).