Repository logo

Infoscience

  • English
  • French
Log In
Logo EPFL, École polytechnique fédérale de Lausanne

Infoscience

  • English
  • French
Log In
  1. Home
  2. Academic and Research Output
  3. Conferences, Workshops, Symposiums, and Seminars
  4. Heterogeneous Gossip
 
conference paper

Heterogeneous Gossip

Frey, Davide
•
Guerraoui, Rachid  
•
Kermarrec, Anne-Marie  
Show more
2009
Middleware 2009
ACM/IFIP/USENIX, 10th International Middleware Conference

Gossip-based information dissemination protocols are considered easy to deploy, scalable and resilient to network dynamics. Load-balancing is inherent in these protocols as the dissemination work is evenly spread among all nodes. Yet, large-scale distributed systems are usually heterogeneous with respect to network capabilities such as bandwidth. In practice, a blind load-balancing strategy might significantly hamper the performance of the gossip dissemination. This paper presents HEAP, HEterogeneity-Aware gossip Protocol, where nodes dynamically adapt their contribution to the gossip dissemination according to their bandwidth capabilities. Using a continuous, itself gossip-based, approximation of relative bandwidth capabilities, HEAP dynamically leverages the most capable nodes by increasing their fanout, while decreasing by the same proportion that of less capable nodes. HEAP preserves the simple and proactive (churn adaptation) nature of gossip, while significantly improving its effectiveness. We extensively evaluate HEAP in the context of a video streaming application on a testbed of 270 PlanetLab nodes. Our results show that HEAP significantly improves the quality of the streaming over standard homogeneous gossip protocols, especially when the stream rate is close to the average available bandwidth.

  • Files
  • Details
  • Metrics
Loading...
Thumbnail Image
Name

middleware-monod.pdf

Access type

openaccess

Size

293.95 KB

Format

Adobe PDF

Checksum (MD5)

c0058dd8b2f25cd6944bcc9a8f1610d3

Logo EPFL, École polytechnique fédérale de Lausanne
  • Contact
  • infoscience@epfl.ch

  • Follow us on Facebook
  • Follow us on Instagram
  • Follow us on LinkedIn
  • Follow us on X
  • Follow us on Youtube
AccessibilityLegal noticePrivacy policyCookie settingsEnd User AgreementGet helpFeedback

Infoscience is a service managed and provided by the Library and IT Services of EPFL. © EPFL, tous droits réservés