Salesforce Com, Inc.

Twin Prime, Inc.

Salesforce, Inc.

Kartikeya Chandrayana

Satish Raghunath

Shauli Gal

Tejaswini Ganapathi

Gabriel Tavridis

Kevin Wang

Maria Garcia Cerdeno

Russell Larsen

Radha Krishna Pagadala

Wojciech A Koszek

Xu Che

Andrey Karapetov

Network request data is collected over a time window. The network request data is filtered to generate bypass network traffic records. Network performance categories are generated from the bypass network traffic records. Sufficient statistics of network optimization parameters are calculated for the network performance categories. The sufficient statistics of the network optimization parameters are used to generate network optimization parameters to determine data download performances of web applications.

Estimation of network quality metrics from network request data

A data-driven approach to network performance diagnosis and root-cause analysis is presented. By collecting and aggregating data attribute values across multiple components of a content delivery system and comparing against baselines for points of inspection, network performance diagnosis and root-cause analysis may be prioritized based on impact on content delivery. Recommended courses of action may be determined and provided based on the tracked network performance analysis at diagnosis points.

Inspecting network performance at diagnosis points

Network traffic data associated with data requests to computer applications based on static policies is collected. An optimization order is established among network parameters. A first network parameter of a higher rank in the optimization order is estimated based on the collected network traffic data before one or more other network parameters of lower ranks are estimated. Optimal values for the other network parameters are estimated based at least in part on the estimated first optimal value for the first network parameter. The estimated first optimal value of the first network parameter and the estimated optimal values for the other network parameters are propagated to be used by user devices to make new data requests to the computer applications.

Simultaneous optimization of multiple TCP parameters to improve download outcomes for network-based mobile applications

A CDN traffic is optimized by a client-side system that maps the servers in the CDN system. Content requests from client devices for domain names are forwarded to servers in the CDN system that may be selected from the map to prevent a cache miss in the a server for a particular request for content.

Content delivery network optimization system

A data-driven approach to network performance diagnosis and root-cause analysis is presented. By collecting and aggregating data attribute values across multiple components of a content delivery system and comparing against baselines for points of inspection, network performance diagnosis and root-cause analysis may be prioritized based on impact on content delivery. Alerts may be generated to present recommended courses of action based on the tracked performance analysis.

Network performance root-cause analysis

Network requests are made to download a data object for a display page with different time delays. Page load outcomes of the display page are determined. A criticality of downloading the data object with respect to the display page is determined using page load outcomes. Criticalities of data objects of the display page are used to generate a specific data object download order that prioritizes critical and/or blocking objects of the display page.

Critical path estimation for accelerated and optimal loading of web pages

Network performance data, such as routing trip time between autonomous systems and data centers, is gathered and aggregated to determine optimal mappings of autonomous systems and data centers. Autonomous system based DNS steering may be automated by repeating a life cycle of determining the optimal mappings. Data delivery strategies are applied to a portion of a network to deliver content using the optimal mappings.

Automated autonomous system based DNS steering

Network requests are made to download a data object with different settings of network parameters. Download outcomes of the data object as requested by the network requests are determined. An elasticity of downloading the data object is determined with respect to a specific network parameter in the network parameters. The elasticity is used to generate a network optimization policy that identifies an optimal value for the specific network parameter to be implemented by user devices and/or other devices/elements for downloading the data object.

Network request and file transfer prioritization based on traffic elasticity

Data analysis is performed through a series of commands that apply functions to an initial scope of data. In a client-server architecture, a data analyst may interact with and view a scope of data through a series of commands. Query formation may be performed at a server to generate reports of data to be presented at the client.

Interactive command-line data analysis

A system for improving network data communications performance between end-user devices and content origin servers. A plurality of accelerators are distributed across a network and communicate with end-user devices and content origin servers. Software development kits installed on end-user devices monitor control channel data traffic between the end-user devices and accelerators. Various data traffic efficiency approaches are implemented by the software development kits on the end-user devices and the plurality of accelerators resulting in improved data communications links between the end-user devices and the content origin servers.

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San Francisco, CA, United States of America

Kartikeya Chandrayana