Real-time control of sensor networks under communication constraints has broad applications, including target tracking and mobile robotics. Traditional centralized methods face congestion and delay issues as system size grows, motivating a shift toward decentralized multi-agent approaches. This paper studies a nonstationary mean-risk optimization model for distributed sensor networks with distance-only noisy measurements and unknown-but-bounded disturbances. An accelerated consensus-based simult