arXiv subjects

Roy D. Yates

Publications and source records attributed to Roy D. Yates.

At least 19 recordsLinked to original sources

arXiv2026

Age Dispersion and Higher-Order AoI in Status Update Systems

We introduce and characterize \emph{age dispersion} as a measure of temporal consistency in status update systems. Age dispersion is defined as the difference between the ages of the two most recently received updates, and its higher-order extension, the {$k$-th} order age dispersion, captures the difference between the ages of the most recent update and the $(k+1)$-th most recent one. We analyze age dispersion in an M/G/1/1 queueing system. Furthermore, we establish connections between the {$k$-th} order age dispersion and the {$k$-th} order age of information (AoI), where the latter quantifies the age of the {$k$-th} most recently received update.

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arXiv2026

Squeezing the Most Out of Preemption for AoI Minimization: Single-source Case

In this work, we study a single-source single-server continuous-time status update system where the updates arrive according to a Poisson process and update service times are generally distributed. In our proposed setting, a preemption policy refers to one where a new update preempts the ongoing one with a probability depending on the age of the update in service. We first propose an analytical method to derive the average age of information (AoI) and average peak AoI (PAoI) for any such preemption policy. This analysis is then utilized to tune two particular preemption policies: (i) probabilistic preemption (PP), in which preemption takes place according to a fixed probability regardless of the update age, (ii) threshold-based preemption (TP), for which preemption is incurred when the update age exceeds a certain threshold, both using one-dimensional line search. The effectiveness of policy tuning for the PP and TP policies is validated using lognormal-distributed update service times.

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arXiv2026

Age and Stability Trade-offs in Remote Monitoring Systems

Timely information is important in a wide variety of Internet of Things (IoT) services in which a shared server must manage two competing tasks: (i) processing a queue of jobs, and (ii) generating status updates to a remote monitor. This creates a fundamental trade-off between queue stability and data freshness. In this work, we model this scheduling decision as a Markov Decision Process (MDP) with the objective of minimizing a weighted sum of the average Age of Information (AoI) and the average queue length. We show that the optimal scheduling strategy is a queue-dependent age threshold which is monotonic. The shape of the switching curve differs according to different priority regimes. Finally, we compare the optimal MDP policy against heuristic policies.

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arXiv2025

Balancing Timeliness and Privacy in Discrete-Time Updating Systems

We study the trade-off between Age of Information (AoI) and maximal leakage (MaxL) in discrete-time status updating systems. A source generates time-stamped update packets that are processed by a server that delivers them to a monitor. An adversary, who eavesdrops on the server-monitor link, wishes to infer the timing of the underlying source update sequence. The server must balance the timeliness of the status information at the monitor against the timing information leaked to the adversary. We consider a model with Bernoulli source updates under two classes of Last-Come-First-Served (LCFS) service policies: (1) Coupled policies that tie the server's deliveries to the update arrival process in a preemptive queue; (2) Decoupled (dumping) policies in which the server transmits its freshest update according to a schedule that is independent of the update arrivals. For each class, we characterize the structure of the optimal policy that minimizes AoI for a given MaxL rate. Our analysis reveals that decoupled dumping policies offer a superior age-leakage trade-off to coupled policies. When subject to a MaxL constraint, we prove that the optimal dumping strategy is achieved by dithering between two adjacent deterministic dump periods.

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arXiv2025

Multi-Source M/G/1/1 Queues with Probabilistic Preemption

We consider a multi-source status update system consisting of multiple independent sources, a single server, and a single sink. Each source generates packets according to a Poisson process, and packets are served according to a general service time distribution. The system has a capacity of one packet, i.e., no waiting buffer, and is modeled as a multi-source M/G/1/1 queueing system. We introduce a probabilistically preemptive packet management policy, under which an existing packet from the same source in the system is replaced by an arriving packet with a fixed probability. We derive the moment generating functions (MGFs) of the age of information (AoI) and peak AoI (PAoI) for each source under this policy. Numerical results demonstrate the effectiveness of the proposed packet management policy.

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arXiv2025

Timely CPU Scheduling for Computation-intensive Status Updates

The proliferation of mobile devices and real-time status updating applications has motivated the optimization of data freshness in the context of age of information (AoI). Meanwhile, increasing computational demands have inspired research on CPU scheduling. Since prior CPU scheduling strategies have ignored data freshness and prior age-minimization strategies have considered only constant CPU speed, we formulate the first CPU scheduling problem as a constrained semi-Markov decision process (SMDP) problem with uncountable space, which aims to minimize the long-term average age of information, subject to an average CPU power constraint. We optimize strategies that specify when the CPU sleeps and adapt the CPU speed (clock frequency) during the execution of update-processing tasks. We consider the age-minimal CPU scheduling problem for both predictable task size (PTS) and unpredictable task size (UTS) cases, where the task size is realized at the start (PTS) or at the completion (UTS) of the task, respectively. To address the non-convex objective, we employ Dinkelbach's fractional programming method to transform our problem into an average cost SMDP. We develop a value-iteration-based algorithm and prove its convergence to obtain optimal policies and structural results for both the PTS and UTS systems. Compared to constant CPU speed, numerical results show that our proposed scheme can reduce the AoI by 50\% or more, with increasing benefits under tighter power constraints. Further, for a given AoI target, the age-minimal CPU scheduling policy can reduce the energy consumption by 50\% or more, with greater AoI reductions when the task size distribution exhibits higher variance.

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arXiv2025

AoI in M/G/1/1 Queues with Probabilistic Preemption

We consider a status update system consisting of one source, one server, and one sink. The source generates packets according to a Poisson process and the packets are served according to a generally distributed service time. We consider a system with a capacity of one packet, i.e., there is no waiting buffer in the system, and model it as an M/G/1/1 queueing system. We introduce a probabilistically preemptive packet management policy and calculate the moment generating functions (MGFs) of the age of information (AoI) and peak AoI (PAoI) under the policy. According to the probabilistically preemptive policy, when a packet arrives, the possible packet in the system is replaced by the arriving packet with a fixed probability. Numerical results show the effectiveness of the packet management policy.

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arXiv2024

Lock-based or Lock-less: Which Is Fresh?

We examine status updating systems in which time-stamped status updates are stored/written in shared-memory. Specifically, we compare Read-Copy-Update (RCU) and Readers-Writer lock (RWL) as shared-memory synchronization primitives on the update freshness. To demonstrate the tension between readers and writers accessing shared-memory, we consider a network scenario with a pair of coupled updating processes. Location updates of a mobile terminal are written to a shared-memory Forwarder Information Base (FIB) at a network forwarder. An application server sends ``app updates'' to the mobile terminal via the forwarder. Arriving app updates at forwarder are addressed (by reading the FIB) and forwarded to the mobile terminal. If a FIB read returns an outdated address, the misaddressed app update is lost in transit. We redesign these reader and writer processes using preemption mechanisms that improve the timeliness of updates. We present a Stochastic Hybrid System (SHS) framework to analyze location and app update age processes and show how these two age processes are coupled through synchronization primitives. Our analysis shows that using a lock-based primitive (RWL) can serve fresher app updates to the mobile terminal at higher location update rates while lock-less (RCU) mechanism favors timely delivery of app updates at lower location update rates.

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arXiv2024

Timely and Energy-Efficient Multi-Step Update Processing

This work explores systems where source updates require multiple sequential processing steps. We model and analyze the Age of Information (AoI) performance of various system designs under both parallel and series server setups. In parallel setups, each processor executes all computation steps with multiple processors working in parallel, while in series setups, each processor performs a specific step in sequence. In practice, processing faster is better in terms of age but it also consumes more power. We identify the occurrence of wasted power in these setups, which arises when processing efforts do not lead to a reduction in age. This happens when a fresher update finishes first in parallel servers or when a server preempts processing due to a fresher update from preceding server in series setups. To address this age-power trade-off, we formulate and solve an optimization problem to determine the optimal service rates for each processing step under a given power budget. We focus on a special case where updates require two computational steps.

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arXiv2024

Age and Value of Information Optimization for Systems with Multi-Class Updates

Received samples of a stochastic process are processed by a server for delivery as updates to a monitor. Each sample belongs to a class that specifies a distribution for its processing time and a function that describes how the value of the processed update decays with age at the monitor. The class of a sample is identified when the processed update is delivered. The server implements a form of M/G/1/1 blocking queue; samples arriving at a busy server are discarded and samples arriving at an idle server are subject to an admission policy that depends on the age and class of the prior delivered update. For the delivered updates, we characterize the average age of information (AoI) and average value of information (VoI). We derive the optimal stationary policy that minimizes the convex combination of the AoI and (negative) VoI. It is shown that the policy has a threshold structure, in which a new sample is allowed to arrive to the server only if the previous update's age and value difference surpasses a certain threshold that depends on the specifics of the value function and system statistics.

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arXiv2024

Status Update Control and Analysis under Two-Way Delay

We study status updating under two-way delay in a system consisting of a sampler, a sink, and a controller residing at the sink. The controller controls the sampling process by sending request packets to the sampler. Upon receiving a request, the sampler generates a sample and transmits the status update packet to the sink. Transmissions of both request and status update packets encounter random delays. We develop optimal control policies to minimize the average age of information (AoI) using the tools of Markov decision processes in two scenarios. We begin with the system having at most one active request, i.e., a generated request for which the sink has not yet received a status update packet. Then, as the main distinctive feature of this paper, we initiate pipelining-type status updating by studying a system having at most two active requests. Furthermore, we conduct AoI analysis by deriving the average AoI expressions for the Zero-Wait-1, Zero-Wait-2, and Wait-1 policies. According to the Zero-Wait-1 policy, whenever a status update packet is delivered to the sink, a new request packet is inserted into the system. The Zero-Wait-2 policy operates similarly, except that the system holds two active requests. According to the Wait-1 policy, whenever a status update packet is delivered to the sink, a new request is sent after a waiting time which is a function of the current AoI. Numerical results illustrate the performance of each status updating policy under different system parameter values.

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arXiv2024

Efficient and Timely Memory Access

This paper investigates the optimization of memory sampling in status updating systems, where source updates are published in shared memory, and reader process samples the memory for source updates by paying a sampling cost. We formulate a discrete-time decision problem to find a sampling policy that minimizes average cost comprising age at the client and the cost incurred due to sampling. We establish that an optimal policy is a stationary and deterministic threshold-type policy, and subsequently derive optimal threshold and the corresponding optimal average cost.

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arXiv2024

Timely Offloading in Mobile Edge Cloud Systems

Future real-time applications like smart cities will use complex Machine Learning (ML) models for a variety of tasks. Timely status information is required for these applications to be reliable. Offloading computation to a mobile edge cloud (MEC) can reduce the completion time of these tasks. However, using the MEC may come at a cost such as related to use of a cloud service or privacy. In this paper, we consider a source that generates time-stamped status updates for delivery to a monitor after processing by the mobile device or MEC. We study how a scheduler must forward these updates to achieve timely updates at the monitor but also limit MEC usage. We measure timeliness at the monitor using the age of information (AoI) metric. We formulate this problem as an infinite horizon Markov decision process (MDP) with an average cost criterion. We prove that an optimal scheduling policy has an age-threshold structure that depends on how long an update has been in service.

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arXiv2024

Age-Memory Trade-off in Read-Copy-Update

In the realm of shared memory systems, the challenge of reader-writer synchronization is closely coupled with the potential for readers to access outdated updates. Read-Copy-Update (RCU) is a synchronization primitive that allows for concurrent and non-blocking read access to fresh data. This is achieved through the creation of updated data copies, with each prior version retained until all associated read-locks are released. Given the principle that frequent updating keeps information fresh, the concern is whether we accumulate an infinite number of update copies, leading to excessively large memory usage. This paper analyzes trade-offs between memory usage and update age within real-time status updating systems, focusing specifically on RCU. The analysis demonstrates that with finite read time and read request rate, the average number of updates within the system remains bounded.

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arXiv2023

Timely Processing Of Updates From Multiple Sources

We consider a system where the updates from independent sources are disseminated via a publish-subscribe mechanism. The sources are the publishers and a decision process (DP), acting as a subscriber, derives decision updates from the source data. We derive the stationary expected age of information (AoI) of decision updates delivered to a monitor. We show that a lazy computation policy in which the DP may sit idle before computing its next decision update can reduce the average AoI at the monitor even though the DP exerts no control over the generation of source updates. This AoI reduction is shown to occur because lazy computation can offset the negative effect of high variance in the computation time.

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arXiv2023

Timely Mobile Routing: An Experimental Study

Time-critical cyber-physical applications demand the timely delivery of information. In this work, we employ a high-speed packet processing testbed to quantitatively analyze a packet forwarding application running on a shared memory multi-processor architecture, where efficient synchronization of concurrent access to a Forwarding Information Base is essential for low-latency and timely delivery of information. While modern packet processing frameworks are optimized for maximum packet throughput, their ability to support timely delivery remains an open question. Here we focus on the age of information performance issues induced by throughput-focused packet processing frameworks. Our results underscore the importance of careful selection of offered load parameters and concurrency constructs in such frameworks.

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arXiv2022

ACP+: An Age Control Protocol for the Internet

We present ACP+, an age control protocol, which is a transport layer protocol that regulates the rate at which update packets from a source are sent over the Internet to a monitor. The source would like to keep the average age of sensed information at the monitor to a minimum, given the network conditions. Extensive experimentation helps us shed light on age control over the current Internet and its implications for sources sending updates over a shared wireless access to monitors in the cloud. We also show that many congestion control algorithms proposed over the years for the Transmission Control Protocol (TCP), including hybrid approaches that achieve higher throughputs at lower delays than traditional loss-based congestion control, are unsuitable for age control.

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arXiv2022

Privacy Leakage in Discrete Time Updating Systems

A source generates time-stamped update packets that are sent to a server and then forwarded to a monitor. This occurs in the presence of an adversary that can infer information about the source by observing the output process of the server. The server wishes to release updates in a timely way to the monitor but also wishes to minimize the information leaked to the adversary. We analyze the trade-off between the age of information (AoI) and the maximal leakage for systems in which the source generates updates as a Bernoulli process. For a time slotted system in which sending an update requires one slot, we consider three server policies: (1) Memoryless with Bernoulli Thinning (MBT): arriving updates are queued with some probability and head-of-line update is released after a geometric holding time; (2) Deterministic Accumulate-and-Dump (DAD): the most recently generated update (if any) is released after a fixed time; (3) Random Accumulate-and-Dump (RAD): the most recently generated update (if any) is released after a geometric waiting time. We show that for the same maximal leakage rate, the DAD policy achieves lower age compared to the other two policies but is restricted to discrete age-leakage operating points.

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