RESEARCH RECORD
Stream processing, sensor networks, cloud systems, and the timing of continuous queries.
Science of Computer Programming, 105, pp. 124–144
A model and algorithm for calculating the time taken for data to move through a stream query. The work uses causal relationships between data tokens and periodic execution schedules, with experiments evaluating the approach.
IEEE 30th International Conference on Data Engineering Workshops (ICDEW), CloudDB 2014, pp. 207–214
A system for continuous data processing within cloud-hosted clusters. It describes processing pipelines algebraically and automatically places computation across available resources, allowing data sources and processing to share a cluster.
Software: Practice and Experience, 44(2), pp. 175–199
A programming environment that expresses sensor-network applications as connected stream operators. An extensible operator library supports different applications, while placement algorithms reduce energy use on sensor nodes.
15th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM ’12), pp. 125–134
Studies how stream-processing operators can move between sensor nodes as queries and network conditions change, with energy consumption as the optimisation objective.
University of Sydney
Doctoral research on stream programming for distributed systems. The associated body of work covers sensor networks, operator placement, cloud processing, and query timing.
IBM developerWorks
A case study of North Carolina State University’s Virtual Computing Lab, covering cloud service models, provisioning architecture, and shared computing resources for university teaching and research.