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    "abstract": "This paper proposes a distributed stream transformation architecture that integrates processing capabilities directly into IP-based media transport networks. As media distribution has transitioned from satellite to IP, solutions have been split between dedicated hardware and cloud platforms, each with scalability limitations. Our approach introduces a hardware-agnostic transformation framework supporting graphics processing unit (GPU), vision processing unit (VPU) (field-programmable gate array/application-specific integrated circuit (FPGA/ASIC)), and central processing unit (CPU) accelerators through unified Ku-bernetes orchestration, employing automatic repeat request (ARQ)-based protocols—Reliable Internet Stream Transport (RIST) and Secure Reliable Transport (SRT)—for reliable delivery over unmanaged networks. The architecture features a failure-tolerant control plane separated from the transport layer and a unified transformation engine running across high-performance core nodes and resource-constrained edge devices. Composable transformation pipelines eliminate duplicate processing by collocating multiple output requirements on optimal nodes. Cost analysis demonstrates that distributed commercial off-the-shelf (COTS) edge processing reduces per-stream costs from approximately ${\\$}$ 281/month to ${\\$}$ 97/month compared to managed cloud services over 36 months, supporting a hybrid deployment model.",
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    "docLabel": "MIJ 2026, Volume 135, Number 2 (pp. 42 to 49)",
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    "docTitle": "Integrating a Stream Transformation Engine in the Distribution Pipeline for Next-Gen Streaming Efficiency",
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