Grant: Discovery Grants Program - Individual

A key challenge in the Internet is that of providing efficient content delivery, such as of web pages, video files, and software packages for example, to large numbers of heterogeneous clients.  A converse problem is found in the context of wireless sensor networks, in which potentially large numbers of interconnected, power-limited computing devices are embedded in the physical environment.  Here a key challenge is that of efficiently collecting and extracting from the network the data that is captured at these devices.  The proposed research concerns the design and performance evaluation of protocols for content delivery and for data collection in large-scale systems, and can be divided into three main projects.      The first project concerns content delivery in the Internet, specifically on-demand delivery of large, highly popular files that many clients concurrently request.  Of particular interest are scalable protocols that make use of file replication at multiple servers,  retrieval of data from other clients that have (all or a portion of) the requested file, and parallelism in the form of concurrent delivery of file data to a client from multiple sources.      The second project concerns data collection in large-scale sensor networks, specifically protocols for in-network aggregation of data as it is being forwarded across the network to the collection point(s).  Of particular interest are asynchronous protocols that determine when to form aggregates at each node adaptively rather than with fixed periodicity.  Issues include how to best construct aggregation trees, packet loss recovery, adapting to node failure, and rate control.      Finally, the third project concerns the advancement of performance evaluation methodologies, including both measurement studies and the development of new analytic modelling techniques, with particular emphasis on the application domains of content delivery and sensor networks.           Contributions from these three projects should significantly improve our understanding of, and ability to quantitatively assess, techniques for content delivery and data collection/aggregation in large-scale systems.