Title: Oriented Overlays For Clustering Client Requests To Data-Centric Network Services


(NYU-CS-TR877)

Authors:  Congchun He and Vijay Karamcheti

Abstract:

Many of the data-centric network services deployed today hold massive volumes of data at their origin websites, accessing the data to dynamically generate responses. Such dynamic responses are poorly supported by traditional caching infrastructures and result in poor performance and scalability for such services. One way of remedying this situation is to develop alternative caching infrastructures, which can dynamically detect the often large degree of service usage locality and leverage such information to on-demand replicate and redirect requests to service portions at appropriate network locations. Key to building such infrastructures is the ability to cluster and inspect client requests, at various points across a wide-area network.
This paper presents a zone-based scheme for constructing oriented overlays, which provide such an ability. Oriented overlays differ from previously proposed unstructured overlays in supporting network traffic flows from many sources towards one (or a small number) of destinations, and vice-versa. A good oriented overlay would offer sufficient clustering ability without adversely affecting path latencies. Our overlay construction scheme organizes participating nodes into different zones according to their latencies from the origin server(s), and has each node associate with one or more parents in another zone closer to the origin. Extensive experiments with a PlanetLab-based implementation of our scheme shows that it produces overlays that are (1) robust to network dynamics; (2) offer good clustering ability; and (3) minimally impact end-to-end network latencies seen by clients.