Age-Energy Analysis in Multi-Source Systems with Wake-up Control and Packet Management
Jie Gong, Jiajie Huang
TL;DR
The paper investigates the age-of-synchronization ($AoS$) versus energy trade-off in a multi-source, single-server system that can enter sleep modes. It develops a stochastic hybrid system (SHS) framework to derive closed-form expressions for the average AoS and the average power under three wake-up policies (N-policy, single-sleep, multi-sleep) and three preemption strategies (LCFS-S, LCFS-W, LCFS-Q). The authors provide explicit results for single and two-source cases and extend to three or more sources, including arbitrary distributions via phase-type representations, with numerical results validating the theory. Key findings indicate that the N-policy generally yields the best AoS-energy trade-off, LCFS-S favors energy saving at low-to-moderate load, and LCFS-Q achieves the freshest data at higher energy cost, while LCFS-W offers a balanced compromise. These insights offer practical guidance for energy-aware real-time systems employing sleep modes and multiple data sources.
Abstract
In recent years, there has been an increasing focus on real-time mobile applications, such as news updates and weather forecast. In these applications, data freshness is of significant importance, which can be measured by age-of-synchronization (AoS). At the same time, the reduction of carbon emission is increasingly required by the communication operators. Thus, how to reduce energy consumption while keeping the data fresh becomes a matter of concern. In this paper, we study the age-energy trade-off in a multi-source single-server system, where the server can turn to sleep mode to save energy. We adopt the stochastic hybrid system (SHS) method to analyze the average AoS and power consumption with three wake-up policies including N-policy, single-sleep policy and multi-sleep policy, and three packet preemption strategies, including Last-Come-First-Serve with preemption-in-Service (LCFS-S), LCFS with preemption-only-in-Waiting (LCFS-W), and LCFS with preemption-and-Queueing (LCFS-Q). The trade-off performance is analyzed via both closed-form expressions and numerical simulations. It is found that N-policy attains the best trade-off performance among all three sleep policies. Among packet management strategies, LCFS-S is suitable for scenarios with high requirements on energy saving and small arrival rate difference between sources. LCFS-Q is suitable for scenarios with high requirements on information freshness and large arrival rate difference between sources.