Age-Delay Tradeoffs in Single Server Systems

Talak, Rajat; Modiano, Eytan

doi:10.1109/isit.2019.8849670

Cited by 29 publications

(7 citation statements)

References 34 publications

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“…Recent research effort has also been exerted to understanding the relation between the AoI and the delay. In [20], the authors analyze the tradeoff between the AoI and the delay in a singleserver M/G/1 system under a specific scheduling policy without knowing the service time of each individual update. In [21], the violation probability of the delay and the PAoI is investigated under an additive white Gaussian noise (AWGN) channel, but the update size is assumed to be identical.…”

Section: Related Workmentioning

confidence: 99%

Anti-aging scheduling in single-server queues: A systematic and comparative study

Liu

Huang

et al. 2021

J. Commun. Netw.

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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. However, compared to the best delay-efficient policies (such as shortest remaining processing time (SRPT)), the AoI improvement is rather marginal in the settings with exogenous arrivals. 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 SRPT) achieve a very good AoI performance.

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Section: Related Workmentioning

confidence: 99%

Anti-aging scheduling in single-server queues: A systematic and comparative study

Liu

Huang

et al. 2021

J. Commun. Netw.

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“…In contrast to AoI, the delay is a traditional timeliness metric that measures the latency of an packet and is considered an packet-centric metric. On the other hand, the update (or packet) generation rate at the source does not affect the delay [27].…”

Section: A the Age Of Information Metricmentioning

confidence: 99%

Age of Information Based URLLC-enabled UAV Wireless Communications System

Basnayaka¹

2021

SSRN Journal

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This paper considers an unmanned aerial vehicles (UAV) communication network, where UAV operate as an aerial mobile relay between a source and a destination of the network. To capture the "timeliness" of the received information at the destination node, a new performance metric named age of information (AoI) is considered. In addition, a short packet communication scheme maintains low latency in the proposed UAV wireless communication system. The finite block-length theory investigates the performances of short packet communications scheme in the UAV-assisted wireless communications system. In this paper, the Average Age of Information (AAoI) is estimated by applying the Stochastic Hybrid Systems (SHS) model. The SHS model comprises discrete states represents events that reset the AoI process and continuously dynamics that represent linearly growing age processes. Finally, a closed-form expression for the AAoI of the proposed UAV wireless communication system is derived and it can be used to estimate the optimal altitude, block length and other parameters.

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“…The proofs of Part A, B, and C are given in Appendix F. Since the virtual queues are mean rate stable, by Part B, ( 25) and ( 26) are true. From ( 23) and ( 26) we get the result in (22).…”

Section: Proofmentioning

confidence: 99%

“…In [4], a simulation study considered AoI in a network of vehicles exchanging status updates. Motivated by [4], AoI was analyzed for several queueing models [5]- [22]. The advantage The authors are with the Laboratory for Information and Decision Systems (LIDS) at the Massachusetts Institute of Technology (MIT), Cambridge, MA.…”

Section: Introductionmentioning

confidence: 99%

Improving Age of Information in Wireless Networks With Perfect Channel State Information

Talak

Karaman

Modiano

2020

IEEE/ACM Trans. Networking

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Age of information (AoI), defined as the time that elapsed since the last received update was generated, is a newly proposed metric to measure the timeliness of information updates in a network. We consider AoI minimization problem for a network with general interference constraints, and time varying channels. We propose two policies, namely, virtual-queue based policy and age-based policy when the channel state is available to the network scheduler at each time step. We prove that the virtual-queue based policy is nearly optimal, up to a constant additive factor, and the age-based policy is at-most a factor of 4 away from optimality. Comparison with previous work, which derived age optimal policies when channel state information is not available to the scheduler, demonstrates significant improvement in age due to the availability of channel state information. Our analysis relies on the age conservation law and age-square conservation law developed in this paper, which hold more generally and may be of independent interest.

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Age-Delay Tradeoffs in Single Server Systems

Cited by 29 publications

References 34 publications

Anti-aging scheduling in single-server queues: A systematic and comparative study

Anti-aging scheduling in single-server queues: A systematic and comparative study

Age of Information Based URLLC-enabled UAV Wireless Communications System

Improving Age of Information in Wireless Networks With Perfect Channel State Information

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