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which matches the empirical 48 ms p95 latency observed in Section 5. Juq-988-javhd.today02-50-06 Min
. The specific string you provided appears to be a formatted filename or a timestamped entry from a video hosting site like JAVHD.today , indicating a video duration of approximately 2 hours, 50 minutes, and 06 seconds Content Overview : which matches the empirical 48 ms p95
The ablation confirms that each component contributes significantly to latency reduction. Experimental results demonstrate a 30 %–45 % reduction
The relentless growth of real‑time data sources—ranging from high‑frequency trading platforms to large‑scale sensor networks—demands processing pipelines capable of sub‑second latency while preserving strong consistency guarantees. In this paper we introduce , a modular, end‑to‑end framework that combines adaptive event‑driven scheduling, just‑in‑time (JIT) compiled data operators, and a hierarchical time‑windowing model to achieve ≤ 50 ms end‑to‑end latency for streams with aggregate rates up to 1 M events · s⁻¹ . We present the architectural design, formalize the latency model, and evaluate the system on three representative benchmarks: financial tick data, smart‑city IoT telemetry, and live video analytics. Experimental results demonstrate a 30 %–45 % reduction in tail latency compared with state‑of‑the‑art platforms (Apache Flink, Spark Structured Streaming, and Hazelcast Jet) while maintaining comparable throughput and fault‑tolerance. The paper concludes with a discussion of scalability limits, security considerations, and avenues for future research.
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