1. Overlay Infrastructure
Hari Balakrishnan
Overlay Infrastructure
Hari Balakrishnan
MIT Laboratory for Computer Science

2. 4 Interesting Areas
Data sharing / resource discovery / data management apps
Build on DHTs
Location: PCs in homes, labs, …
Driver: cooperative, secure archiving (e.g., CVS) and backup service for all our data
New routing & forwarding models
Content routing, RON, OverQoS (QoS overlays)
Location: network “edges”; key is AS diversity
Driver: Predictable network performance, e.g., for previous set of apps
Measurement research
Set up a large-scale overlay for monitoring network performance
Location: “Deep in the network”, at colo’s, etc.
Driver: How well is our prediction doing; how could we do better?
Internet-wide ASPs
Serving software (e.g., “HTTP-based virtual memory”)
Location: Edges / datacenters
Driver: Managing and upgrading software on all our handhelds, desktops, laptops
1 line research goal: let’s design predictable systems

3. Challenges Research Logistics Getting predictability
Design for “flux”: system will have no steady state
Logistics
The 4 (and more) areas have pretty diverse requirements
Management (cf. RON/Chord experience)

4. RON Deployment (19 sites)
To vu.nl lulea.se ucl.uk
To kaist.kr, .ve
.com (ca), .com (ca), dsl (or), cci (ut), aros (ut), utah.edu, .com (tx)
cmu (pa), dsl (nc), nyu , cornell, cable (ma), cisco (ma), mit,
vu.nl, lulea.se, ucl.uk, kaist.kr