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).

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 2012
Accession Number
ADA571274

Entities

People

  • Joe W. Jiang

Organizations

  • Princeton University

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Cloud Computing
  • Computer Networks
  • Computer Programming
  • Computers
  • Data Centers
  • Engineering
  • Game Theory
  • Information Exchange
  • Infrastructure
  • Internet
  • Network Protocols
  • Network Topology
  • Optimization
  • Reliability
  • Routing Protocols
  • Social Media

Fields of Study

  • Computer science

Readers

  • Computer Networking
  • Distributed Systems and Data Platform Development