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Fair and Scalable Orchestration of Network and Compute Resources for Virtual Edge Services

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dc.contributor.author Tripathi, Sharda
dc.date.accessioned 2023-04-05T10:17:00Z
dc.date.available 2023-04-05T10:17:00Z
dc.date.issued 2023-03
dc.identifier.uri https://ieeexplore.ieee.org/abstract/document/10065522/keywords#keywords
dc.identifier.uri http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/10183
dc.description.abstract The combination of service virtualization and edge computing allows for low latency services, while keeping data storage and processing local. However, given the limited resources available at the edge, a conflict in resource usage arises when both virtualized user applications and network functions need to be supported. Further, the concurrent resource request by user applications and network functions is often entangled, since the data generated by the former has to be transferred by the latter, and vice versa. In this paper, we first show through experimental tests the correlation between a video-based application and a vRAN. Then, owing to the complex involved dynamics, we develop a scalable reinforcement learning framework for resource orchestration at the edge, which leverages a Pareto analysis for provable fair and efficient decisions. We validate our framework, named VERA, through a real-time proof-of-concept implementation, which we also use to obtain datasets reporting real-world operational conditions and performance. Using such experimental datasets, we demonstrate that VERA meets the KPI targets for over 96% of the observation period and performs similarly when executed in our real-time implementation, with KPI differences below 12.4%. Further, its scaling cost is 54% lower than a centralized framework based on deep-Q networks en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.subject EEE en_US
dc.subject Virtual RAN en_US
dc.subject Virtualized services en_US
dc.subject Resource orchestration en_US
dc.subject Machine Learning en_US
dc.subject Experimental testbed en_US
dc.title Fair and Scalable Orchestration of Network and Compute Resources for Virtual Edge Services en_US
dc.type Article en_US


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