Age of information: The gamma awakening

In this paper, we explore the potential of server waiting before packet transmission in improving the Age of Information (AoI) in status update systems. We consider a non-preemptive queue with Poisson arrivals and independent general service distribution and we incorporate waiting before serving in two packet management schemes: M/GI/1/1 and M/GI/1/2 * . In M/GI/1/1 scheme, the server waits for a deterministic time immediately after a packet enters the server. In M/GI/1/2 * scheme, depending on idle or busy system state, the server waits for a deterministic time before starting service of the packet. In both cases, if a potential newer arrival is captured existing packet is discarded. Different from most existing works, we analyze AoI evolution by indexing the incoming packets, which is enabled by an alternative method of partitioning the area under the evolution of instantaneous AoI to calculate its time average. We obtain expressions for average and average peak AoI for both queueing disciplines with waiting.Our numerical results demonstrate that waiting before service can bring significant improvement in average age, particularly, for heavy-tailed service distributions. This improvement comes at the expense of an increase in average peak AoI. We highlight the trade-off between average and average peak AoI generated by waiting before serving.The authors are with the

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“…Cases of X i (6). We denote S i−1 , S i as independent random variables representing the service times of packets i − 1 and i.…”

Section: A Average Aoimentioning

confidence: 99%

“…are as in (6). Note that for an arbitrary arriving packet i − 1, the next packet index i may or may not be the minimum index in the ensuing service period and the indicator function ½ i=i * accounts for distinguishing it.…”

Section: B Average Peak Aoimentioning

confidence: 99%

Waiting Before Serving: A Companion to Packet Management in Status Update Systems

Zou

Özel

Subramaniam

2020

IEEE Trans. Inform. Theory

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“…Consider a relay network with multiple wireless hops between a transmitter and the receiver. If the service time of each hop follows an exponential distribution, the end-to-end service time in the system follows a gamma distribution [15]. distribution with parameter κ and β can be interpreted as the summation of κ independent exponential random variables with parameter β.…”

Section: B Multi-source M/g/1 Queueing Model -Gamma Distributionmentioning

confidence: 99%

Closed-Form Expression for the Average Age of Information in a Multi-Source M/G/1 Queueing Model

Moltafet

Leinonen

Codreanu

2019

2019 IEEE Information Theory Workshop (ITW)

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Freshness of status update packets is essential for enabling services where a destination needs the most recent measurements of various sensors. In this paper, we study the information freshness of single-server multi-source queueing models under a first-come first-served (FCFS) serving policy.In the considered model, each source independently generates status update packets according to a Poisson process. The information freshness of the status updates of each source is evaluated by the average age of information (AoI). We derive an exact expression for the average AoI for the case with exponentially distributed service time, i.e., for a multi-source M/M/1 queueing model. Moreover, we derive an approximate expression for the average AoI for a multi-source M/G/1 queueing model having a general service time distribution. Simulation results are provided to validate the derived exact average AoI expression, to assess the tightness of the proposed approximation, and to demonstrate the AoI behavior for different system parameters.Index Terms-Information freshness, age of information (AoI), multi-source M/G/1 queueing model.

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“…In [3], it shows that for an M/M/1 system with a buffer, the last-come-first-served (LCFS) with preemption discipline achieves lower time-average age than LCFS without preemption. In [36], it indicates that when the service time follows a Gamma distribution, last-generatedfirst-served (LGFS) with preemption may not outperform LGFS without preemption. If the service times are i.i.d.…”

Section: Introductionmentioning

confidence: 99%

When to preempt? Age of information minimization under link capacity constraint

2019

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In this paper, we consider a scenario where a source continuously monitors an object and sends time-stamped status updates to a destination through a rate-limited link. We assume updates arrive randomly at the source according to a Bernoulli process. Due to the link capacity constraint, it takes multiple time slots for the source to complete the transmission of an update. Therefore, when a new update arrives at the source during the transmission of another update, the source needs to decide whether to skip the new arrival or to switch to it, in order to minimize the expected average age of information (AoI) at the destination. We start with the setting where all updates are of the same size, and prove that within a broadly defined class of online policies, the optimal policy should be a renewal policy, and has a sequential switching property. We then show that the optimal decision of the source in any time slot has threshold structures, and only depends on the age of the update being transmitted and the AoI at the destination. We then consider the setting where updates are of different sizes, and show that the optimal Markovian policy also has a multiple-threshold structure. For each of the settings, we explicitly identify the thresholds by formulating the problem as a Markov Decision Process (MDP), and solve it through value iteration. Special structural properties of the corresponding optimal policy are utilized to reduce the computational complexity of the value iteration algorithm.Index Terms-Age of information, preemptive policies, threshold structure, MDP, structured value iteration.

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Age of information: The gamma awakening

Cited by 181 publications

References 5 publications

Waiting Before Serving: A Companion to Packet Management in Status Update Systems

Waiting Before Serving: A Companion to Packet Management in Status Update Systems

Closed-Form Expression for the Average Age of Information in a Multi-Source M/G/1 Queueing Model

When to preempt? Age of information minimization under link capacity constraint

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