An automatic approach for creating faster websites using HTTP/2, machine learning, and AI

Informations projet

AI for a faster web

N° de convention de subvention: 868576

DOI

10.3030/868576

Projet clôturé

Date de signature de la CE 11 Mai 2019

Date de début 1 Juin 2019

Date de fin 30 Novembre 2019

Financé au titre de

• INDUSTRIAL LEADERSHIP - Innovation In SMEs

Coût total

€ 71 429,00

Contribution de l’UE

€ 50 000,00

Coordonné par

SHIMMERCAT AB
Sweden

Periodic Reporting for period 1 - AI for a faster web (An automatic approach for creating faster websites using HTTP/2, machine learning, and AI)

Période du rapport: 2019-06-01 au 2019-11-30

Résumé du contexte et des objectifs généraux du projet

Website speed is the key to success for e-commerce websites. A fast website creates a better user experience, improves Google ranking, and increases conversion. Optimizing slow websites is therefore a pressing problem on a growing market that calls for efficient solutions.

As web usage and online commerce has exploded, we have moved from simple static websites to fully interactive and complex websites, introducing new challenges for creating fast websites. To address these new challenges, the web protocol HTTP/2 was released in 2015. The new protocol introduces new features that software can use to substantially increase website speed.

However, most of the HTTP/2 features are not straightforward to apply and need to be actively configured. Since the features can lead to substantial speed improvements, the overall objective of this project was to develop a software product that can utilize the features of HTTP/2 to help online businesses create faster websites.

The project outcome shows that the automatic approach with ShimmerCat for creating faster loading times, that uses machine learning and HTTP/2, has the potential to significantly improve the performance of e-commerce websites.

Travail effectué depuis le début du projet jusqu’à la fin de la période considérée dans le rapport et principaux résultats atteints jusqu’à présent

The work performed during the project has focused on exploring and assessing the technical feasibility and commercial viability of the software product ShimmerCat, a web server that handles requests for things which are part of a website. During the project ShimmerCat has been developed to send we traffic data to a cloud infrastructure that analyzes the data, and sends back directives about how to manage the traffic to improve website speed.

During the project the technical viability of the product has been validated in an online operational e-commerce environment that takes live web traffic. The project has also resulted in a validation of the products commercial viability, thanks to the help of an ecommerce platform that has implemented the product in order to resell it.

Progrès au-delà de l’état des connaissances et impact potentiel prévu (y compris l’impact socio-économique et les conséquences sociétales plus larges du projet jusqu’à présent)

ShimmerCat goes beyond the state of the art as it can collect, analyze, and optimize performance with data from HTTP headers and other metadata (timestamp, TCP details, TLS and protocol fingerprints, etc). This data is analyzed to automatically build rules for HTTP/2 Push and resource preloading, rules for redirecting automatic traffic, above-the-fold image prioritization data, and next-gen optimized image formats. The potential impact of the project is to be able to create websites that load 30-60% faster.

Data collection overview