• Data analytics
    • Driver profiling
    • Fuel prediction
    • Vehicle health monitoring
    • Multi-factor schedule optimization
    • Local and global content popularity aware synthetic workload generator
  • Internet of Things (IoT)
    • Smartphone-based road condition monitoring
    • Software Defined Radio (SDN) for vitual sensor networks
    • Robust water flow meter
    • Weather data integration and assimilation system
    • An automated framework for weather-related decision making
  • Cloud computing
    • Performance, resource, and workload aware VM scheduling
    • PaaS Aggregation in multi-cloud librities
    • Container-based workflows for weather and flood monitoring and forecasting
  • Complex Event Processing (CEP)
    • Automatic query generation
    • Scaling CEP
    • Event reordering in CEP
    • Consumer-to-consumer social message matching
    • Analyzing illegal call patterns
  • Security
    • Food tracability beyond proof of existance in blockchain
    • Wireless spetrum management for cognitive and citizens broadband radio services
    • Complexity analysis of data anonymization and de-anonymization and statistical techniques
    • Cognitive platform for detection of anomalies and cases of interests in IoT environments
  • Software engineering
    • Robotic process management and agile metrics
Cloud Computing

Work on workload, resource, and cost aware VM allocation in IaaS and PaaS clouds have resulted in several publications. Our key contributions include the following:

  • A proactive, workload, resource, and cost-aware auto-scaling solution for PaaS cloud that combines a predictive model, cost model, and smart killing. An ensemble workload prediction mechanism is introduced based on time series and machine learning techniques for making accurate predictions on drastically different workload patterns.
  • Given that cloud operator exposes a small, dynamic fraction of its infrastructure (corresponding resource specifications and constraints), we propose a dynamic and computationally efficient VM reconfiguration scheme which comprises an Application Performance Model, a Cost Model, and a Reconfiguration algorithm. This enables cloud hosted user applications to dynamically scale while consuming just the adequate amount of resources along different types of resource dimensions, more than just CPU and memory.
  • A resource and policy aware VM scheduling solution for medium-scale IaaS clouds that enables the deployment of VMs based on a predefined set of policies and user priorities, while being aware of the resource utilization of the cloud.
Collaborative Peer-to-Peer Systems

Resource-rich computing devices, decreasing communication costs, and Web 2.0 technologies are fundamentally changing the way distributed applications communicate and collaborate. With these changes, we envision Peer-to-Peer (P2P) systems that will allow for the integration and collaboration of peers with diverse capabilities to a virtual community thereby empowering it to engage in greater tasks beyond what can be accomplished by individual peers, yet are beneficial to all the peers. Collaborative P2P systems are applicable in a wide variety of contexts such as:

  • Distributed Collaborative Adaptive Sensing (DCAS) systems such as Collaborative Adaptive Sensing of the Atmosphere (CASA)
  • Grid and cloud computing
  • P2P clouds, i.e., community-based cloud computing
  • Mobile and social P2P networks
  • Global Environment for Network Innovations (GENI)

Collaborations involving application-specific resources and dynamic quality of service goals will stress current P2P architectures that are designed for best-effort environments with pair-wise interactions among nodes with similar resources. These systems will share a variety of resources such as processor cycles, storage capacity, network bandwidth, sensors/actuators, services, middleware, scientific algorithms, and data. Goal of this project is to address all related challenges of key phases of resource collaboration such as resource advertising, selection, matching, and binding as well issues related to incentives, trust, security, and privacy. Initial work started while I was at CNRL. Some of the sub-projects include:

  • ResQue — A multi-attribute resource and range query generator. Generates random computing nodes with multiple static and dynamic attributes over a given time period and multi-attribute range queries.
  • BitTorrent Search Engine/Site Survey – A survey conducted to understand whether users access multiple BitTorrent search engines and how frequently.
  • Secure patch dissemination over P2P
Complex Event Processing

Work related to Complex Event Processing (CEP) span across both the architectural aspects of CEP engines and use of CEP for multidisciplinary applications. Some of the examples include:

  • Porting WSO2 Siddhi CEP engine to GPU
  • Automated CEP query generation
  • CEP and machine learning for weather detection
  • CEP engine for IoT devices
  • Information Extraction System To Sense Web-Based Information Leakage
  • Secure P2P patch dissemination
  • An Efficient and Scalable Graph-based Access Review Evaluation Model for XACML
  • Crime data analytics platform
  • Biometric enabled third-party authentication system
  • Secure pre-key distribution in Wireless Sensor Networks
Virtual Sensor Networks

A resource efficient approach for concurrent wireless sensor network applications. Initial work started while I was at CNRL.

Other Projects
  • Indexing scientific data
  • PCI DSS Compliance Management Framework
  • Software Metrics for Agile
  • Critical Success Factors for Tech Startups in Sri Lanka
  • Impact of Performance Appraisals on Performance of Software Engineers in Sri Lanka
  • Employee Retention Strategies: A Comparative Study of Sri Lanka Offshore Industry
  • Analysis of Software Quality Assurance Profession in Sri Lankan IT Industry
  • Enhancing Service Quality at Srilankan Airlines: A Critical Analysis of IT Factors And Recommendations
  • Factors Affecting Online Printing Adoption by the Sri Lankan Printing Industry