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Sequoia: Supporting Network-Aware Distributed Applications

Sequoia aims to make distributed applications network-aware. That is, enable applications to take advantage of the characteristics of the underlying network such as proximity, bandwidth capacity, and topology. It intends to achieve this through the key concept of prediction trees, a virtual topology of the network, where virtual nodes representing routers connect real end hosts, and carefully computed edge weights model path properties such as latency, loss rate, and bandwidth.

The following are some of the network-aware functionalities that Sequoia seeks to provide:

  • Path Property Prediction: Two hosts in the system can estimate path properties (latency, loss rate, available bandwidth) between them through computation without requiring a direct measurement.
  • Server Selection: An external client outside the system can select the closest or best-provisioned server in the system.
  • Hierarchical Partitioning: Hosts can organize into hierarchical clusters based on their position in the network.

Publications
  • The Internet Grows on Trees! (poster)
    Dahlia Malkhi and Venugopalan Ramasubramanian.
    Microsoft TechFest, Redmond, WA, March 2008.

  • Reconstructing Approximate Tree Metrics
    Ittai Abraham, Mahesh Balakrishnan, Fabian Kuhn, Dahlia Malkhi, Venugopalan Ramasubramanian and Kunal Talwar.
    ACM Symposium on Principles of Distributed Computing (PODC), Portland OR, August 2007.

  • Internet Path Quality Prediction Using Trees (poster)
    Ittai Abraham, Mahesh Balakrishnan, Archit Gupta, Fabian Kuhn, Dahlia Malkhi, Venugopalan Ramasubramanian and Kunal Talwar.
    Summer Intern Research Series, Microsoft Research Silicon Valley, July 2007.

Demo

A demo of geographical partitioning and closest-node discovery in Sequoia for PlanetLab nodes.

Talks
People

Internal Contributors:

External Collaborators:


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