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Maycon Peixoto

Publications and source records attributed to Maycon Peixoto.

2 recordsLinked to original sources

AGORA: Agentic Green Orchestration Architecture for Beyond 5G Networks

Effective management and operational decision-making for complex mobile network systems present significant challenges, particularly when addressing conflicting requirements such as efficiency, user satisfaction, and energy-efficient traffic steering. The literature presents various approaches aimed at enhancing network management, including the Zero-Touch Network (ZTN) and Self-Organizing Network (SON); however, these approaches often lack a practical and scalable mechanism to consider human sustainability goals as input, translate them into energy-aware operational policies, and enforce them at runtime. In this study, we address this gap by proposing the AGORA: Agentic Green Orchestration Architecture for Beyond 5G Networks. AGORA embeds a local tool-augmented Large Language Model (LLM) agent in the mobile network control loop to translate natural-language sustainability goals into telemetry-grounded actions, actuating the User Plane Function (UPF) to perform energy-aware traffic steering. The findings indicate a strong latency-energy coupling in tool-driven control loops and demonstrate that compact models can achieve a low energy footprint while still facilitating correct policy execution, including non-zero migration behavior under stressed Multi-access Edge Computing (MEC) conditions. Our approach paves the way for sustainability-first, intent-driven network operations that align human objectives with executable orchestration in Beyond-5G infrastructures.

cs.NI

Tetris: An SLA-aware Application Placement Strategy in the Edge-Cloud Continuum

An Edge-Cloud Continuum integrates edge and cloud resources to provide a flexible and scalable infrastructure. This paradigm can minimize latency by processing data closer to the source at the edge while leveraging the vast computational power of the cloud for more intensive tasks. In this context, module application placement requires strategic allocation plans that align user demands with infrastructure constraints, aiming for efficient resource use. Therefore, we propose Tetris, an application placement strategy that utilizes a heuristic algorithm to distribute computational services across edge and cloud resources efficiently. Tetris prioritizes services based on SLA urgencies and resource efficiency to avoid system overloading. Our results demonstrate that Tetris reduces SLA violations by approximately 76% compared to the baseline method, which serves as a reference point for benchmarking performance in this scenario. Therefore, Tetris offers an effective placement approach for managing latency-sensitive applications in Edge-Cloud Continuum environments, enhancing Quality of Service (QoS) for users.

cs.DC