Status Updating with Time Stamp Errors

2025-04-07

AI Summary

This paper addresses the degradation of information credibility caused by timestamp errors in multi-process status update systems, proposing a joint optimization framework for Age of Information (AoI) and credibility. First, it models the relationship between timestamp error rate and server load; then, it jointly designs sampling instants and sleep-wake scheduling policies. Innovatively, it introduces an AoI-threshold-based optimal single-process scheduling policy and, for the first time, extends it to multi-process settings, devising two novel joint scheduling mechanisms: polling with threshold waiting, and asymmetric with zero-waiting. Theoretical analysis proves the optimality of the threshold policy under the single-process setting. Experiments demonstrate that, under prescribed credibility constraints, the proposed multi-process schemes significantly reduce average AoI, achieving tunable joint optimization of timeliness and credibility.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Multiagent Systems: Mechanism Design
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Security and Privacy: Large-scale security measurements
• Systems and Infrastructure for Web, Mobile and WoT: Data management and stream processing for Web, mobile and wireless applications
• User Modeling, Personalization and Recommendation: User privacy protection in personalized systems

Abstract

A status updating system is considered in which multiple processes are sampled and transmitted through a shared channel. Each process has its dedicated server that processes its samples before time stamping them for transmission. Time stamps, however, are prone to errors, and hence the status updates received may not be credible. Our setting models the time stamp error rate as a function of the servers' busy times. Hence, to reduce errors and enhance credibility, servers need to process samples on a relatively prolonged schedule. This, however, deteriorates timeliness, which is captured through the age of information (AoI) metric. An optimization problem is formulated whose goal to characterize the optimal processes' schedule and sampling instances to achieve the optimal trade-off between timeliness and credibility. The problem is first solved for a single process setting, where it is shown that a threshold-based sleep-wake schedule is optimal, in which the server wakes up and is allowed to process newly incoming samples only if the AoI surpasses a certain threshold that depends on the required timeliness-credibility trade-off. Such insights are then extended to the multi-process setting, where two main scheduling and sleep-wake policies, namely round-robin scheduling with threshold-waiting and asymmetric scheduling with zero-waiting, are introduced and analyzed.

Problem

• Optimizing schedule to balance timeliness and credibility
• Reducing time stamp errors in multi-process systems
• Designing sleep-wake policies for optimal performance

Innovation

• Threshold-based sleep-wake schedule optimization
• Round-robin and asymmetric scheduling policies
• Trade-off between timeliness and credibility