The Age-of-Information (AoI) is a new performance metric recently proposed for measuring the freshness of information in information-update systems. In this work, we conduct a systematic and comparative study to investigate the impact of scheduling policies on the AoI performance in single-server queues and provide useful guidelines for the design of AoI-efficient scheduling policies. Specifically, we first perform extensive simulations to demonstrate that the update-size information can be leveraged for achieving a substantially improved AoI compared to non-size-based (or arrival-time-based) policies. Then, by utilizing both the update-size and arrival-time information, we propose three AoI-based policies. Observing improved AoI performance of policies that allow service preemption and that prioritize informative updates, we further propose preemptive, informative, AoI-based scheduling policies. Our simulation results show that such policies empirically achieve the best AoI performance among all the considered policies. Interestingly, we also prove sample-path equivalence between some size-based policies and AoI-based policies. This provides an intuitive explanation for why some size-based policies, such as Shortest-Remaining-Processing-Time (SRPT), achieve a very good AoI performance. 
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                            Transform Analysis of Preemption Overhead in the M/G/1
                        
                    
    
            Preemptive scheduling policies, which allow pausing jobs mid-service, are ubiquitous because they allow important jobs to receive service ahead of unimportant jobs that would otherwise delay their completion. The canonical example is Shortest Remaining Processing Time (SRPT), which preemptively serves the job with least remaining work at every moment in time [9]. There is a robust literature analyzing response time (elapsed time between a job's arrival and completion) in the M/G/1 queue under many preemptive policies [6, 10, 11], shedding light on questions such as how preemption affects the mean and tail of response time, and whether preemption is unfair towards low-priority jobs. 
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                            - Award ID(s):
- 2307008
- PAR ID:
- 10623912
- Publisher / Repository:
- ACM
- Date Published:
- Journal Name:
- ACM SIGMETRICS Performance Evaluation Review
- Volume:
- 52
- Issue:
- 2
- ISSN:
- 0163-5999
- Page Range / eLocation ID:
- 18 to 20
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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