I am a Ph.D. candidate in the Department of Computer Science at Indiana University Bloomington. My research advisor is Prof. Geoffrey Fox and I work in the Community Grids Lab as a research assistant. In my Ph.D. research, I focus on MapReduce and cloud technologies such Hadoop, Dryad and DryadLINQ. Specifically, I am trying to identify extensions to the MapReduce programming model so that it can be applied to more classes of applications. I have developed i-MapReduce (Iterative MapReduce Runtime) a streaming based MapReduce runtime that supports iterative MapReduce computations efficiently.

i-MapReduce supports long running (cacheable) map/reduce tasks and uses a pub-sub messaging infrastructure for all the communication and data transfer requirements.  In my latest research, I am trying to add fault tolerance support for the i-MapReduce runtime. Apart from the above I have performed extensive analyses on the performance of cloud technologies comparing them with i-MapReduce and the traditional parallel programming techniques such as MPI, and also evaluated the performance implications of virtualization for these runtimes.

I am also a committer for Apache Sandesha and Apache Axis2 projects and the PMC for the Apache Sandesha project. You can find the latest information of my research in my CGL-reports blog.

Education

Ph.D. Computer Science (Candidate) Indiana University Bloomington
M.Sc. Computer Science 2007 Indiana University Bloomington
B.Sc. Engineering 2004 Department of Computer Science and Engineering University of Moratuwa Sri Lanka

Research Interests

Cloud Computing, Data Intensive Scalable Computing, or High Performance Computing

Research

i-MapReduce - a light weight streaming based map reduce runtime with the efficient support for iterative MapReduce computations and faster intermediate data transfers. i-MapReduce incorporates the concept of long running processes available in parallel runtimes such as MPI to the MapReduce model and it uses NaradaBrokering's publish/subscribe messaging infrastructure for  all its communication requirements and the intermediate data transfers.  More detailed description of i-MapReduce can be found here.

Implemented a series of scientific data processing applications such as High Energy Physics data analysis, Cap3 Analysis, Kmeans Clustering, Matrix Multiplication, and Multi-Dimensional Scaling using different parallel runtimes such as Hadoop, Dryad, CGL-MapReduce, and MPI and compared their performance to understand the various benefits and limitations of different parallel runtimes. More detailed description of these solutions and their performance results can be found here.
Researched on the performance implications of virtualization for High Performance Computing (HPC) applications, using a private cloud infrastructure based on Xen and Eucalyptus. This paper contains the  findings of this research.
Integration of Clarens Server, ROOT Analysis Framework and Naradabrokering to provide a collaborative framework for analysing distributed data, especially the data from particle physics experiments. The project is still in working progress. However, a proof of concept implementation/integration is completed.
Developed a C++ Client for Naradabrokering to facilitate the integration of Clarens Server from Caltech with Naradabrokering. This eliminates the dependency to have a JVM installed at client machines as in the JNI implementation. 
Developed a C++ Client for Naradabrokering using JNI technology allowing C++ clients to utilize the publish/subscribe messaging capabilities of Naradabrokering. Software is available for download here.
Developed a transport-independent scheme for tracking the availability of entities in distributed systems using Naradabrokering messaging substrate. The scheme enforces the authorized generation and consumption of traces (encapsulating entity availability).
Y790  - Performance testing on Multi-core chips (Results).
Implemented the message bridge to connect IBM Websphere and Naradabrokering. (The Architecture).
Y790 - Common Architecture for Functional Extensions on Top of Apache Axis2 (This was based on the work I did in axis2 project.)

Publications

Jaliya Ekanayake, Atilla Soner Balkir, Thilina Gunarathne, Geoffrey Fox, Christophe Poulain, Nelson Araujo, Roger Barga DryadLINQ for Scientific Analyses 5th IEEE International Conference on e-Science Oxford UK, December 9-11 2009
Jaliya Ekanayake, (Advisor: Geoffrey Fox) Architecture and Performance of Runtime Environments for Data Intensive Scalable Computing, Doctoral Showcase, SuperComputing2009.
Xiaohong Qiu, Jaliya Ekanayake, Scott Beason, Thilina Gunarathne, Geoffrey Fox, Roger Barga, Dennis Gannon, Cloud Technologies for Bioinformatics Applications, 2nd ACM Workshop on Many-Task Computing on Grids and Supercomputers, SuperComputing2009.
Jaliya Ekanayake, Geoffrey Fox, High Performance Parallel Computing with Clouds and Cloud Technologies, First International Conference on Cloud Computing (CloudComp09) Munich, Germany, 2009.
Eran Chinthaka, Jaliya Ekanayake, David Leake, CBR Based Workflow Composition Assistant, IEEE 2009 Third International Workshop on Scientific Workflows (SWF 2009).
Geoffrey Fox, Seung-Hee Bae, Jaliya Ekanayake, Xiaohong Qiu, and Huapeng Yuan, Parallel Data Mining from Multicore to Cloudy Grids, High Performance Computing and Grids workshop, 2008.
Shrideep Pallickara, Jaliya Ekanayake, Geoffrey Fox, An Overview of the Granules Runtime for Cloud Computing, Fourth IEEE International Conference on eScience, 2008, pp.412-413.
Jaliya Ekanayake and Shrideep Pallickara, MapReduce for Data Intensive Scientific Analysis, Fourth IEEE International Conference on eScience, 2008, pp.277-284.
Jaliya Ekanayake, Shrideep Pallickara,  and Geoffrey Fox, A collaborative framework for scientific data analysis and visualization, Collaborative Technologies and Systems(CTS), 2008,pp. 339-346.
Shrideep Pallickara, Jaliya Ekanayake and Geoffrey Fox, A Scalable Approach for the Secure and Authorized Tracking of the Availability of Entities in Distributed Systems in the proceedings of Proceedings of the 21st IEEE International Parallel & Distributed Processing Symposium (IPDPS 2007). Long Beach, California.
Srinath Perera, Chathura Herath, Jaliya Ekanayake, Eran Chinthaka, Ajith Ranabahu, Deepal Jayasinghe, Sanjiva Weerawarana,Glen Daniels Axis, Middleware for Next Generation Web Services on IEEE International Conference on Web Services (ICWS'06)
Ajay Smitha and Jaliya Ekanayake, Analysis of the Usage Statistics of Robots Exclusion Standard. In proceedings of the IADIS WWW/Internet 2006 Murcia, Spain 5-8 October 2006.
Developerworks Article on Apache Sandesha: Use Apache Sandesha to support Web services implementation.

Presentations

Architecture and Performance of Runtime Environments for Data Intensive Scalable Computing, Doctoral Showcase, SuperComputing2009.
High Performance Parallel Computing with Clouds and Cloud Technologies -CloudComp 2009, Munich, Germany
MapReduce for Data Intensive Scientific Analysis - IEEE e-Science, 2008
A collaborative framework for scientific data analysis and visualization - CTS 2008
Asynchronous Web Services
Expose an Stateless Session Bean as a Web Service
Apache Sandesha and Axis2

Posters

CTS2009 Poster

eScience08 Posters

CTS2008 Posters