End-to-End Orchestration of NextG Media Services over the Distributed Compute Continuum
<|reference_start|>End-to-End Orchestration of NextG Media Services over the Distributed Compute Continuum: NextG (5G and beyond) networks, through the increasing integration of cloud/edge computing technologies, are becoming highly distributed compute platforms ideally suited to host emerging resource-intensive and latency-sensitive applications (e.g., industrial automation, extended reality, distributed AI). The end-to-end orchestration of such demanding applications, which involves function/data placement, flow routing, and joint communication/computation/storage resource allocation, requires new models and algorithms able to capture: (i) their disaggregated microservice-based architecture, (ii) their complex processing graph structures, including multiple-input multiple-output processing stages, and (iii) the opportunities for efficiently sharing and replicating data streams that may be useful for multiple functions and/or end users. To this end, we first identify the technical gaps in existing literature that prevent efficiently addressing the optimal orchestration of emerging applications described by information-aware directed acyclic graphs (DAGs). We then leverage the recently proposed Cloud Network Flow optimization framework and a novel functionally-equivalent DAG-to-Forest graph transformation procedure to design IDAGO (Information-Aware DAG Orchestration), a polynomial-time multi-criteria approximation algorithm for the optimal orchestration of NextG media services over NextG compute-integrated networks.<|reference_end|>
@article{mauro2024end-to-end,
    title={End-to-End Orchestration of NextG Media Services over the Distributed
  Compute Continuum},
    author={Alessandro Mauro, Antonia Maria Tulino, Jaime Llorca},
    journal={arXiv preprint arXiv:2407.08710},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.08710},
    primaryClass={cs.NI}
}