Improving network efficiency in real-time groupware with general message compression

Abstract

Groupware communicates by sending messages across the network, and groupware programmers use a variety of formats for these messages, such as XML, plain text, or serialized objects. Although these formats have many advantages, they are often so verbose that they overload the system's network resources. Groupware programmers could improve efficiency by using more compact formats, but this efficiency comes at the cost of increased complexity, reduced convenience, and reduced readability. In this paper we propose an alternate approach for improving efficiencyan automatic compression system that transparently minimizes verbose formats. Our general message compressor -GMCautomatically finds and removes redundancy in message streams, without any knowledge of the contents or structure of the message, and without any need for the programmer to change the way they work. In tests with realistic message traces, GMC reduced text messages to 20% of their original size, XML messages to 8% of the original, and serialized objects to 9%. Although not as compact as a hand-coded representation, GMC provides most of the compression benefits with almost none of the work -it allows groupware programmers to use convenient message formats without compromising transport efficiency.

Timelines: simplifying the programming of lag compensation for the next generation of networked games

“…Janus currently truncates history to limit storage requirements. We plan to adapt algorithms for compacting history developed for solving the groupware latecomer problem [6], and mechanisms for compressing messages [17].…”

An Enhanced Dead Reckoning Model for Physics-Aware Multiplayer Computer Games

“…Consequently, most real-time MCGs employ an Information Management algorithm to maintain a controlled level of inconsistency [3,[6][7][8][9][10]. Such algorithms attempt to optimize the streams of data transmitted by a MCG, and thus reduce the inconsistency caused by overloaded network hardware.…”

Improving TCP Goodput over Wireless Networks Using Kernel-Level Data Compression

“…The user space is the easiest place to implement the data compression [5] [20]. Since the application knows the characteristics of data transmitting over the network it can decide proper policy for the compression.…”

“…Jeannot [5] has suggested a set of user-level functions for network data compression. GMC [20] is another user-level data compressor. Since these approaches are sort of user-level solutions, the modification of the user application is inevitable.…”