WAN optimization

WAN optimization is a collection of techniques for improving data transfer across wide area networks (WANs). In 2008, the WAN optimization market was estimated to be $1 billion,[1] and was to grow to $4.4 billion by 2014 according to Gartner,[2] a technology research firm. In 2015 Gartner estimated the WAN optimization market to be a $1.1 billion market.[3]

The most common measures of TCP data-transfer efficiencies (i.e., optimization) are throughput, bandwidth requirements, latency, protocol optimization, and congestion, as manifested in dropped packets.[4] In addition, the WAN itself can be classified with regards to the distance between endpoints and the amounts of data transferred. Two common business WAN topologies are Branch to Headquarters and Data Center to Data Center (DC2DC). In general, "Branch" WAN links are closer, use less bandwidth, support more simultaneous connections, support smaller connections and more short-lived connections, and handle a greater variety of protocols. They are used for business applications such as email, content management systems, database application, and Web delivery. In comparison, "DC2DC" WAN links tend to require more bandwidth, are more distant, and involve fewer connections, but those connections are bigger (100 Mbit/s to 1 Gbit/s flows) and of longer duration. Traffic on a "DC2DC" WAN may include replication, back up, data migration, virtualization, and other Business Continuity/Disaster Recovery (BC/DR) flows.

WAN optimization has been the subject of extensive academic research almost since the advent of the WAN.[5] In the early 2000s, research in both the private and public sectors turned to improving the end-to-end throughput of TCP,[6] and the target of the first proprietary WAN optimization solutions was the Branch WAN. In recent years, however, the rapid growth of digital data, and the concomitant needs to store and protect it, has presented a need for DC2DC WAN optimization. For example, such optimizations can be performed to increase overall network capacity utilization,[7][8] meet inter-datacenter transfer deadlines,[9][10][11] or minimize average completion times of data transfers.[11][12] As another example, private inter-datacenter WANs can benefit optimizations for fast and efficient geo-replication of data and content, such as newly computed machine learning models or multimedia content.[13][14]

Component techniques of Branch WAN Optimization include deduplication, wide area file services (WAFS), SMB proxy, HTTPS Proxy, media multicasting, web caching, and bandwidth management. Requirements for DC2DC WAN Optimization also center around deduplication and TCP acceleration, however these must occur in the context of multi-gigabit data transfer rates.

  1. ^ Machowinski, Matthias. "WAN optimization market passes $1 billion in 2008, up 29%; enterprise router market down". Enterprise Routers and WAN Optimization Appliances. Infonetics Research. Retrieved 19 July 2011.
  2. ^ Skorupa, Joe; Severine Real (2010). "Forecast: Application Acceleration Equipment, Worldwide, 2006–2014, 2Q10 Update". Gartner, Inc. Retrieved 19 July 2011.[dead link]
  3. ^ Munch, Bjarne; Neil Rickard (2015). "Magic Quadrant for WAN Optimization, 17 March 2015". Gartner, Inc. Retrieved 26 March 2015.
  4. ^ Cardwell, N.; Savage, S.; Anderson, T. (2000). "Modeling TCP latency". Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064). Vol. 3. Dept. of Comput. Sci. & Eng., Washington Univ., Seattle, WA: IEEE.org. pp. 1742–1751. doi:10.1109/INFCOM.2000.832574. ISBN 0-7803-5880-5. S2CID 6581992.
  5. ^ Jacobson, Van (October 1988). "TCP Extensions for Long-Delay Paths". Request for Comments: 1072. Internet Engineering Task Force (IETF). Retrieved 19 July 2011.
  6. ^ Floyd, Sally. "HighSpeed TCP for Large Congestion Windows". Request for Comments: 3649. Internet Engineering Task Force (IETF). Retrieved 19 July 2011.
  7. ^ S. Jain; et al. (2013). "B4: Experience with a Globally-Deployed Software Defined WAN" (PDF). Retrieved April 4, 2018.
  8. ^ C. Hong; et al. (2013). "Achieving High Utilization with Software-Driven WAN". Microsoft. Retrieved April 4, 2018.
  9. ^ S. Kandula; et al. (2014). "Calendaring for Wide Area Networks" (PDF). Microsoft. Retrieved April 4, 2018.
  10. ^ M. Noormohammadpour; et al. (2016). "DCRoute: Speeding up Inter-Datacenter Traffic Allocation while Guaranteeing Deadlines". Retrieved April 4, 2018.
  11. ^ a b X. Jin; et al. (2016). "Optimizing Bulk Transfers with Software-Defined Optical WAN" (PDF). Retrieved April 4, 2018.
  12. ^ M. Noormohammadpour; et al. (2018). "Minimizing Flow Completion Times using Adaptive Routing over Inter-Datacenter Wide Area Networks". Retrieved April 4, 2018.
  13. ^ M. Noormohammadpour; et al. (July 10, 2017). "DCCast: Efficient Point to Multipoint Transfers Across Datacenters". USENIX. Retrieved July 26, 2017.
  14. ^ M. Noormohammadpour; et al. (2018). "QuickCast: Fast and Efficient Inter-Datacenter Transfers using Forwarding Tree Cohorts". Retrieved January 23, 2018.