Summer 2006
Summer 2007
Summer 2008

Summer 2006


Name Home Institution Year Mentor
Luis Atencio Florida International University Junior Dr. S Masoud Sadjadi
Sam Burnett Carnegie Mellon University Sophomore Dr. Raju Rangaswami
Igor Hernandez Florida International University Sophomore Dr. Raju Rangaswami
Jason Liptak Syracuse University Sophomore Dr. Raju Rangaswami
Joseph A. Marrero Florida International University Junior Dr. Raju Rangaswami
Brittany Parsons Capital University Sophomore Dr. Peter J. Clarke
Javier Ocasio Perez University of Puerto Rico at Mayaguez Junior Dr. S Masoud Sadjadi and Dr. Tao Li
Tatitana Soldo Florida International University Junior Dr. S Masoud Sadjadi
Ronald Stevens Florida A &M University Junior Dr. Peter J. Clarke
Brenton Williams Florida Memorial College Junior Dr. Chi Zhang


Summer 2006
Summer 2006 Summer 2006

Research and Education:

Dates Activities Coordinator(s)
May 15 - May 19
  • Welcome
  • Tour of School and University Facilities
  • Presentation - Introduction to Autonomic Computing
  • Assignment of Projects
Dr. Milani and Dr. Li
May 22 Start of Research Activities Mentors
June 2 Time Management Workshop FIU Counseling and Psychology Service Center
June 9 Study Strategies FIU Counseling and Psychology Service Center
June 15 Progress Presentation 1 Dr. Milani
July 6 Progress Presentation 2 Dr. Milani
July 7 Managing Test Anxiety FIU Counseling and Psychology Service Center
July 27 Final Project Presentation Dr. Milani

Other Activities:

Dates Activities Coordinator(s)
Regularly Visit to South Beach  
  Visit to Coconut Grove Dr. Milani
  Scuba Diving Trip Dr. Milani and Rangaswami


  1. Title: Self-Optimizing File Systems

  2. Participants: Sam Burnett, Jason Liptak, Medha Bhadkamkar (Ph.D. student) and Raju Rangaswami (mentor)

    Project Description: Efficient file systems hold one of the keys to high-performance I/O systems. Today's file systems perform a static layout of file data, aiming to preserve the directory structure of the file system and optimizing for sequential access to entire files. In this project, we re-examined the existing state-of-the-art in file system design and find it severely lacking in an important aspect, application awareness. We argued that for optimal performance, file systems must self-optimize by adapting data layout to accommodate the dynamism in application access patterns. We developed the design and implementation of an automated data layout reconfigurator which is at the heart of such a self-optimizing file system. Preliminary studies using file system traces indicated significant I/O performance gains when compared to a state-of-the-art ext3 file syst

    Presentations: SOFS-Final-Presentation

    Publications: Feasibility, Efficiency, and Effectiveness of Self-Optimizing Storage Systems Medha Bhadkamkar, Sam Burnett, Jason Liptak, Raju Rangaswami, and Vagelis Hristidis, Florida International University Technical Report TR-2007-01-01, January 2007.

  3. Title: Transparent Adaptation in Existing .NET Applications

  4. Participants: Javier Ocasio Perez, Dr. S. Masoud Sadjadi (mentor)

    Project Description: We define adaptability as the capacity of software in adjusting its behavior in response to changing conditions. To list just a few examples, adaptability is important in pervasive computing, where software in mobile devices need to adapt to dynamic changes in wireless networks; autonomic computing, where software in critical systems are required to be self-manageable; and grid computing, where software for long running scientific applications need to be resilient to hardware crashes and network out-ages. In this project, we investigate a realization of the transparent shaping programming model, called TRAP.NET, which enables transparent adaptation in existing .NET applications as a response to the changes in the application requirements and/or to the changes in their execution environment. Using TRAP.NET, we can adapt an application dynamically, at run time, or statically, at load time, without the need to manually modify the application original functionality-hence transparent.


    Publications: S. Masoud Sadjadi and Fernando Trigoso. Trap.net: A realization of transparent shaping in .net. In Proceedings of The Nineteenth International Conference on Software Engineering and Knowledge Engineering (SEKE'2007), pages 19-24, Boston, USA, July 2007. Note: In the this paper, Javier Ocasio’s help is acknowledged.

  5. Title: Survey of Validation Methods in Autonomic Computing Systems

  6. Participants: Brittany Parsons, Ronal Stevens, Tariq King (PhD student) and Dr. Peter J. Clarke (mentor)

    Project Description: This project involved the survey of several autonomic computing systems focusing on the validation methods used during self-management. The systems surveyed included Impala (Princeton University), OceanStore (UC Berkeley), Model Driven Autonomic Manager (Indiana University), and The Bison Project (University of Bologna). The results of the survey showed that there were no approaches used to validate the changes made to the systems during self-management. As a result the team decided to develop a self-testing framework for autonomic computing systems.



    • Ronald Stevens, Brittany Parsons, and Tariq M. King, "A Self-Testing Autonomic Container", Proceedings of the 45th ACM Southeast Conference, ACMSE '07, p. 1-6, (2007).

    • Tariq King, Djuradj Babich, Jonatan Alava, Ronald Stevens and Peter J. Clarke, "Towards Self-Testing in Autonomic Computing Systems", International Symposium on Autonomic and Decentralized Systems 2007 (ISADS 2007), p. 51-58 (2007).

  7. Title: Self-Protecting Systems

  8. Participants: Joseph Marrero, Igor Hernandez, and Raju Rangaswami (mentor)

    Project Description: This project developed Rootsense, a holistic and real-time intrusion prevention system that combines the merits of misbehavior-based and anomaly-based detection. Four principles govern the design and implementation of Rootsense. First, Rootsense audits events within different subsystems of the host operating system and correlates them to comprehensively capture the global system state. Second, Rootsense restricts the detection domain to root compromises only; doing so reduces run-time overhead and increases detection accuracy (root behavior is more easily modeled than user behavior). Third, Rootsense adopts a dual approach to intrusion detection -- a root penetration detector detects activities that exploit system vulnerabilities to penetrate the security perimeter, and a root misbehavior detector tracks misbehavior by root processes. Fourth, Rootsense is designed to be configurable for overhead management allowing the system administrator to tune the overhead characteristics of the intrusion prevention system that affect foreground task performance. A Linux implementation of Rootsense is analyzed for both accuracy and performance, using several real-world exploits and a range of end-host and server benchmarks.

    Presentations: Rootsense-Final-Presentation

    Publications: Anatomy of a Real-time Intrusion Prevention System, Ricardo Koller, Raju Rangaswami, Joseph Marrero, Igor Hernandez, Geoffrey Smith, Mandy Barsilai, , Florida International University Technical Report TR-2007-01-01, January 2007.

  9. Title: Transparent Grid Enablement in Existing Java Applications using TRAP/J

    Participants: Tatiana Soldo, Luis Atencio and Dr. S. Masoud Sadjadi (mentor)

    Project Description: High performance computing (HPC) is gaining popularity in solving scientific applications. Using the current programming standards, however, it takes an HPC expert to efficiently take advantage of HPC facilities; a skill that a scientist does not necessarily have. This lack of separation of concerns has resulted in scientific applications with rigid code, which entangles non-functional concerns (i.e., the parallel code) into functional concerns (i.e., the core busi-ness logic). Effectively, this tangled code hinders the maintenance and evolution of these applications. In this project, we investigate the design and implementation of a software tool, called Transparent Grid Enabler (TGE), that enables separation of the task of developing the business logic of a scientific application from the task of improving its performance. TGE achieves this goal by integrating two existing software tools, namely, TRAP/J and GRID superscalar. A simple matrix multiplication program is used as a case study to demonstrate the current use and capabilities of TGE.