PNap: Lifecycle-aware Edge Multi-state sleep for Energy Efficient MEC

2026-03-24

AI Summary

This work addresses the high energy consumption in Multi-access Edge Computing (MEC) systems, where numerous servers remain active even under low workload conditions, and existing energy-saving mechanisms fail to adequately coordinate service lifecycle management with server sleep states. To tackle this issue, the authors propose PowerNap (PNap), a novel framework that jointly optimizes multi-level server sleep modes with service deployment, migration, and other lifecycle operations for the first time. By incorporating traffic prediction to enable dynamic scheduling, PNap significantly reduces energy consumption while preserving service availability. Experimental results demonstrate that the proposed approach achieves up to 14.9% greater energy savings compared to the state-of-the-art solutions.

Technology Category

• Machine Learning: Learning on the Edge & Model Compression
• Multiagent Systems: Mechanism Design
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

Multi-access Edge Computings (MECs) enables low-latency services by executing applications at the network edge. To fulfill low-latency requirements of mobile users, providers have to keep multiple edge servers running at multiple locations, even when, in low-load phases, their capacity is not needed. This significantly increases energy consumption. Multi-state sleep mechanisms mitigate this issue by allowing servers to enter progressively deeper sleep states, trading energy savings for longer wake-up delays. At the same time, service execution depends on non-instantaneous lifecycle operations that cannot be performed while servers are asleep, tightly coupling energy management with service continuity. This paper introduces PowerNap (PNap), a lifecycle-aware orchestration framework that jointly manages server sleep states and service lifecycle states. By leveraging traffic forecasting, PNap jointly minimizes the number of active edge servers and service disruptions. We compare PNap against baselines approaches and a state-of-the-art approach. Results validate PNap, showing how it can reduce energy consumption by up to 14.9% with respect to a state-of-the-art solution while matching its service availability results.

Problem

• Multi-access Edge Computing
• energy efficiency
• multi-state sleep
• service lifecycle
• server orchestration

Innovation

• multi-state sleep
• lifecycle-aware orchestration
• energy-efficient MEC
• traffic forecasting
• edge server management