Drifting (2026) is an experimental networked music composition and performance for two performers in separate locations. The work explores how network latency, normally considered a technical limitation of remote musical collaboration, can become an active element of the compositional and performance process.

Rather than attempting to eliminate or conceal network delay, Drifting incorporates changing network conditions into its musical structure. Through a custom system integrating Python, Open Sound Control (OSC), Max for Live and Ableton Live, network-delay estimates are translated into musical control data, influencing tempo, audio processing and the behaviour of prepared musical materials.

The result is a performance environment in which composition, human interaction and network conditions continuously shape the unfolding music.

Two custom TouchOSC interfaces were developed to provide each performer with direct control over their musical materials and processing systems.

The interfaces include clip triggers, track controls and sound-processing parameters, allowing performers to select, combine, transform and stop musical material in real time.

Performer A controls melodic, harmonic, bass and textural material, while the network-derived delay determines the session’s tempo state.

Performer B controls percussion, drums and vocal material, with additional control over tempo and audio-processing parameters.

The composition uses a collection of pre-composed musical excerpts rather than a fixed timeline. Both performers construct the musical arrangement during performance, making decisions about sequencing, layering, density and transformation in response to one another and the evolving network conditions.

The system connects two performers through a network, enabling bidirectional audio transmission, real-time data exchange and independent musical control.

Each performer works within a dedicated Ableton Live and Max for Live environment, connected through Tailscale VPN. Python scripts monitor network delay using a repeated ping/pong process, generating estimated one-way delay values that are transmitted through OSC and mapped to musical parameters.

The two performers interact with these values differently.

For Performer A, network delay influences the tempo of the composition. Changes in the estimated delay shift the performance between three predefined tempo states, affecting the pacing and rhythmic character of the musical material.

For Performer B, network delay influences audio processing, including granular synthesis, delay, reverb, pitch shifting and textural transformation. Performer B also retains independent manual control of tempo.

Live audio is exchanged through SonoBus, allowing both performers to hear and respond to each other’s musical decisions throughout the performance.

System architecture

Performer ATouchOSC · Ableton · Max for LiveNetwork delay → tempo

Bidirectional communication

OSC data

SonoBus audio exchange

Tailscale

Performer BTouchOSC · Ableton · Max for LiveNetwork delay → processing

Estimated delayEstimated delay

Python network measurement

1. Ping/pong RTT
2. Estimated one-way delay
3. Max for Live mapping

How network delay is mapped

Layer	Performer A	Performer B
Network input	Estimated one-way delay	Estimated one-way delay
Automated response	Three tempo states: 120 / 89 / 50 BPM	Granular, delay, reverb, pitch and textural processing
Human control	Clip selection, layering, processing	Clip selection, layering, processing and manual tempo

The Python ping/pong system estimates network delay from round-trip measurements. It does not measure the complete end-to-end SonoBus audio latency.

Drifting forms part of Chen Wang’s doctoral research at the University of the Arts London, investigating openness and creative decision-making in technologically mediated music composition and performance.

The work explores how prepared musical structures can remain responsive to changing conditions beyond the direct control of either performer. Network delay becomes one influence within a wider musical relationship shaped by composed materials, performer decisions and technological processes.

Rather than allowing the network to determine the entire composition, the system establishes specific relationships between network conditions and musical parameters, creating opportunities for different musical realisations to emerge.

Technologies

Python · Open Sound Control (OSC) · Max/MSP · Max for Live · Ableton Live · TouchOSC · Tailscale VPN · SonoBus · Real-Time Network Communication

Research & Teaching ↗