Saving Bandwidth for RSS Feeds by using ASN.1 in e-Learning Applications

R. De Sutter and R. Van de Walle (Belgium)

Keywords

Elearning, RSS feeds, XML compression, ASN.1

Abstract

RSS feeds are gaining popularity as an alternative way to inform subscribers of new events. More and more teachers use it as an alternative to the traditional bulletin board to inform their students on upcoming events. As such, students can receive the latest information about their courses in a centralized way. However, the RSS feeds consume a lot of bandwidth because they are written in the verbose XML language. Bandwidth is wasted in two ways: an RSS feed has no compact representation because of the plain text XML representation and already known information by the RSS viewer about the feed is discarded every time the viewer retrieves the feed. An alternative serialization of the XML data can help to eliminate this overhead. In this paper, we use the Abstract Syntax Notation One (ASN.1) technology with the packed encoding rules to address the overhead of the RSS feeds. We validate its usability for optimizing a real-life RSS feed that distributes translation exercises. We calculate the byte size reduction of the data and compare the processing speed to create and to parse ASN.1 encoded RSS feeds to plain text RSS feeds.

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