Asymptotically Optimal Status Update Compression in Multi-Source System: Age-Distortion Tradeoff

Area of Science:

• Information Theory
• Communication Systems
• Signal Processing

Background:

• Status-updating systems are crucial for real-time information dissemination.
• Efficient compression is vital for managing data in shared communication channels.
• Minimizing age of information (AoI) is key for timely data delivery.

Purpose of the Study:

• To investigate compression schemes for multi-source status-updating systems.
• To minimize the sum of average AoI under symbol distortion constraints.
• To develop optimal quantizer-encoder designs for two distinct compression approaches.

Main Methods:

• Formulation of optimization problems for quantizer-encoder design.
• Analysis of a two-source system with heterogeneous Poisson processes.
• Development of multi-quantizer and single-quantizer compression schemes.

Main Results:

• Asymptotic optimality achieved with uniform quantizers in the multi-quantizer scheme.
• Asymptotic optimality achieved with a piecewise uniform w-quantizer in the single-quantizer scheme.
• Average AoI scales linearly with log distortion for both schemes, with slope dependent on source arrival rates.

Conclusions:

• The proposed compression schemes offer asymptotically optimal solutions for minimizing AoI.
• The design of quantizer-encoder pairs significantly impacts system performance.
• Understanding the relationship between distortion and AoI is crucial for system design.