Wide-Area Traffic Management for Cloud Services

Abstract:

Cloud service providers (CSPs) need effective ways to distribute
content across wide area networks. Providing large-scale,
geographically-replicated online services presents new opportunities
for coordination between server selection (to match subscribers with
servers), traffic engineering (to select efficient paths for the
traffic), and content placement (to store content on specific
servers). Traditional designs isolate these problems, which degrades
performance, scalability, reliability and responsiveness. We leverage
the theory of distributed optimization, cooperative game theory and
approximation algorithms to provide solutions that jointly optimize
these design decisions that are usually controlled by different
institutions of a CSP.

This dissertation proposes a set of wide-area traffic management
solutions, which consists of the following three thrusts:
(i) Sharing information: We develop three cooperation models with an
increasing amount of information exchange between the ISP?s (Internet
Service Provider) traffic engineering and the CDN?s (Content
Distribution Network) server selection. We show that straightforward
ways of sharing information can be quite sub-optimal, and propose a
Nash bargaining solution to reduce the efficiency loss. This work
sheds light on ways that different groups of a CSP can communicate to
improve their performance.

(ii) Joint control: We propose a content distribution architecture by
federating geographically or administratively separate groups of
last-mile CDN servers (e.g., nano data centers) located near end
users. We design a set of mechanisms to solve a joint content
placement and request routing problem under this architecture,
achieving both scalability and cost optimality. This work demonstrates
how to jointly control multiple traffic management decisions that may
have different resolutions (e.g., inter vs. intra ISP), and may happen
at different timescales (e.g., minutes vs. several times a day).

(iii) Distributed implementation: Today?s cloud services are offered
to a large number of geo- graphically distributed clients, leading to
the need for a decentralized traffic control. We present DONAR, a
distributed mapping service that outsources replica selection, while
providing a sufficiently expressive service interface for specifying
mapping policies based on performance, load, and cost. Our solution
runs on a set of distributed mapping nodes for directing local client
requests, which only requires a lightweight exchange of summary
statistics for coordination between mapping nodes. This work
exemplifies a decentralized design that is simultaneously scalable,
reliable, and accurate.

Collectively, these solutions are combined to provide a synergistic
traffic management system for CSPs who wish to offer better
performance to their clients at a lower cost. The main contribution of
this dissertation is to develop new design techniques to make this
process more systematic, automated and effective.