Analytical Evaluation of Age of Information in Networks of Correlated Sources

Crosara, Laura; Zancanaro, Alberto; Cisotto, Giulia; Laurenti, Nicola; Badia, Leonardo

doi:10.1109/metroagrifor55389.2022.9964724

Cited by 9 publications

(21 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The sensed information may be correlated at different locations. We aim to take advantage of this correlation to decrease the number of useless transmissions but keep the average AoI as low as possible [ 15 , 16 , 27 ]. Particularly, in each time slot, we consider either of the following two possibilities: a sensor, e.g., sensor 1, senses a new sample of information and transmits the fresh sample to the central server, and this event is assumed to happen with a probability equal to p .…”

Section: Scenario and Methodologymentioning

confidence: 99%

“…In real world scenarios, the information coming from sensors can be multi-structured and data can have different importance levels for the end user [ 19 , 27 ]. The application of ML offers a powerful tool to integrate this aspect and extend the concept of AoI in the more general concept of ”value of information” where the semantic aspects of the data become important to decide whether to transmit them, or not.…”

Section: Ml-based Sensor Transmission Optimization Using Aoimentioning

confidence: 99%

See 1 more Smart Citation

Tackling Age of Information in Access Policies for Sensing Ecosystems

Zancanaro

Cisotto

Badia

2023

Sensors

Self Cite

View full text Add to dashboard Cite

Recent technological advancements such as the Internet of Things (IoT) and machine learning (ML) can lead to a massive data generation in smart environments, where multiple sensors can be used to monitor a large number of processes through a wireless sensor network (WSN). This poses new challenges for the extraction and interpretation of meaningful data. In this spirit, age of information (AoI) represents an important metric to quantify the freshness of the data monitored to check for anomalies and operate adaptive control. However, AoI typically assumes a binary representation of the information, which is actually multi-structured. Thus, deep semantic aspects may be lost. In addition, the ambient correlation of multiple sensors may not be taken into account and exploited. To analyze these issues, we study how correlation affects AoI for multiple sensors under two scenarios of (i) concurrent and (ii) time-division multiple access. We show that correlation among sensors improves AoI if concurrent transmissions are allowed, whereas the benefits are much more limited in a time-division scenario. Furthermore, we discuss how ML can be applied to extract relevant information from data and show how it can further optimize the transmission policy with savings of resources. Specifically, we demonstrate, through simulations, that ML techniques can be used to reduce the number of transmissions and that classification errors have no influence on the AoI of the system.

show abstract

Section: Scenario and Methodologymentioning

confidence: 99%

Section: Ml-based Sensor Transmission Optimization Using Aoimentioning

confidence: 99%

Tackling Age of Information in Access Policies for Sensing Ecosystems

Zancanaro

Cisotto

Badia

2023

Sensors

Self Cite

View full text Add to dashboard Cite

show abstract

“…Many studies evaluate the AoI in queuing systems, for various settings but especially based on classic memory-less systems with different disciplines [13]- [15].…”

Section: Related Workmentioning

confidence: 99%

“…inter-generation times, with tunable rate λ, and the service of the queue, also a memoryless process, has rate µ, so that the offered load is ρ = λ/µ, the lowest AoI is achieved at a certain intermediate value, which is less straightforward than the delay-or throughput-optimizing conditions that are ρ → 0 + and ρ → 1 − , respectively. This reasoning can be extended to more complex systems by changing the queue policy [6], [7] or explicitly including other aspects such as medium access control [8]- [10].…”

Section: Introductionmentioning

confidence: 99%

It Is Rude to Ask a Sensor Its Age-of-Information: Status Updates Against an Eavesdropping Node

Crosara

Laurenti

Badia

2023

2023 International Balkan Conference on Communications and Networking (BalkanCom)

View full text Add to dashboard Cite

We consider periodical status updates between a transmitter and a legitimate receiver, in the presence of an eavesdropper that is sometimes able to capture pieces of information. We assume that, in the absence of such a threat, the connection between the transmitter and the receiver is controlled by the transmitter with the aim to minimize the age of information at the receiver's side. However, if the presence of an eavesdropper is known, the transmitter may further tune the generation rate of status updates to trade off the age of information values acquired by the eavesdropper and the receiver, respectively. To analyze this problem, we first propose a metric that combines both objectives according to a Bergson social welfare framework, and then we solve the problem of finding the optimal generation rate as a function of the probability of data capture by the eavesdropper. This enables us to derive notable and sometimes counter-intuitive conclusions, and possibly establish an extension of the age of information framework to security aspects from a performance evaluation perspective.

show abstract

“…}, at time t the value of its AoI is δ(t) = t−τ (t) , where (t) = arg max j {τ j ≤ t}. Many evaluations of AoI in the literature pertain to queueing systems with different disciplines [2]- [5].…”

Section: Introductionmentioning

confidence: 99%

Correlation of Multiple Strategic Sources Decreases Their Age of Information Anarchy

Badia,

Crosara

2024

IEEE Trans. Circuits Syst. II

View full text Add to dashboard Cite

We consider a sensor network, where multiple sources send status updates to a common receiver and, due to correlation in the content, transmissions from a given node can also be informative for others. The objective is to minimize the individual information freshness, quantified through age of information, at the receiver's side. We compare a centralized control with a disitributed minimization; in the former, the globally optimal data injection rate is chosen, whereas in the latter, sources behave like players of a non-cooperative game of complete information. We compute Nash equilibrium and quantify the price of anarchy. Even a moderate correlation among sources is shown to make a distributed approach more efficient. For a correlation of 1/3 of the content, the anarchy is set to just 6-7% worse than the optimum.

show abstract

Analytical Evaluation of Age of Information in Networks of Correlated Sources

Cited by 9 publications

References 31 publications

Tackling Age of Information in Access Policies for Sensing Ecosystems

Tackling Age of Information in Access Policies for Sensing Ecosystems

It Is Rude to Ask a Sensor Its Age-of-Information: Status Updates Against an Eavesdropping Node

Correlation of Multiple Strategic Sources Decreases Their Age of Information Anarchy

Contact Info

Product

Resources

About