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#1 2017-04-04 2:53:27 pm

Registered: 2017-01-25
Posts: 3

PERISCOPE: Standardizing and Orchestrating Looking Glass Querying

The Periscope Looking Glass API, developed by Vasileios Giotsas,
sets out to unify the heterogenous thousands of autonomously operated
Looking Glass (LG) servers into a single unified standardized API
for querying and executing experiments across the collective resource
as a whole. From the beginning, we understood that while the hosting
networks make these services public, usage policies varied and many
LG services request clients rate limit their queries or impose rate
limits and some forbid automated queries entirely. We do our best
with Periscope administration to respect LG resources and implement
conservative client rate limiting enforcing a per-user and per-LG
rate limits. We identify our clients to provide transparency and

We believe the Periscope architecture brings several primary benefits.
The LG data complements our current trace data and extends the
topology coverage. It allows us to implement intelligent load design
across all LG servers, uses caching to reduce the number of redundant
queries, and makes more efficient use of the LG resources as a
whole. Finally, Periscope improves troubleshooting capabilities
(often the reason for supporting these services in the first place).

For more detail regarding the Periscope Looking Glass API see

A webcast of the NANOG68 Periscope presentation is available here:  as well as the accompanying slideset presented at NANOG68 here:

Full paper: V. Giotsas, A. Dhamdhere, and k. claffy, “Periscope:
Unifying Looking Glass Querying“, in Passive and Active Network
Measurement Workshop (PAM), Mar 2016.

This work was supported in part by the National Science Foundation,
the DHS Science and Technology Directorate, Cyber Security Division
(DHS S&T/CSD) and by Defence R&D Canada (DRDC).


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