Reduce Remote Application Response Time With Wan Optimization Controllers

Wikipedia defines WAN Optimization Controllers as ""a collection of techniques for increasing data-transfer efficiencies across wide-area networks."" The different optimization techniques include compression, latency optimization, forward error correction, caching / proxy, deduplication, traffic shaping, application acceleration, network acceleration equalizing, protocol spoofing, network optimization, connection limits, and simple rate limits. Let's look at some of these techniques to fully understand WAN optimization.

 Compression : It refers to compression techniques similar to ZIP, RAR, ARJ etc. These are applied on the fly to data passing through hardware (or virtual machine) based WAN acceleration appliances.

 Protocol Optimization : It refers to the use of in-depth protocol knowledge to accelerate user response time.

 Network Optimization : This technique helps to keep a network operating at peak efficiency by identifying and resolving data flow barriers.

 Caching : A technique that speeds up certain computer operations by temporarily placing data, or a copy of it, in a location where it can be accessed more rapidly than normal.

 Traffic Shaping : This technique helps to control data flow for specific applications so that important applications can be given precedence over the WAN.

 Deduplication : It eliminates the transfer of redundant data across the WAN by sending references instead of the actual data.

 Latency Optimization : It includes TCP refinements such as window-size scaling, selective acknowledgements, Layer 3 congestion control algorithms, and even co-location strategies in which the application is placed in near proximity to the endpoint to reduce latency.

 Hence, enterprises must invest in a good WAN optimization appliance that accelerates any type of WAN traffic and excels at maximizing the performance of business-critical enterprise applications.

 Thus with WAN optimization controllers, enterprises can maximize their inherent scalability and performance without disrupting the customer experience or exposing mission-critical data.