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Book ChapterDOI

Adaptive Status Arrivals Policy (ASAP) Delivering Fresh Information (Minimise Peak Age) in Real World Scenarios

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TLDR
The proposed Adaptive Status Arrivals Policy (ASAP), adaptively controls the timing between updates to enhance the Peak Age (PA) performance of real-time systems and is able to approach the theoretical optimal PA performance.
Abstract
Real-time systems make their decisions based on information communicated from sensors. Consequently, delivering information in a timely manner is critical to such systems. In this paper, a policy for delivering fresh information (or minimising the Peak Age of the information) is proposed. The proposed policy, i.e., the Adaptive Status Arrivals Policy (ASAP), adaptively controls the timing between updates to enhance the Peak Age (PA) performance of real-time systems. Firstly, an optimal value for the inter-arrival rate is derived. Afterwards, we implemented the policy in three scenarios and measured the ASAP PA performance. The experiments showed that ASAP is able to approach the theoretical optimal PA performance. Moreover, it can deliver fresh information in scenarios where the server is located in the cloud.

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Citations
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Journal ArticleDOI

6G opportunities arising from Internet of Things use cases: a review paper

TL;DR: In this article, the authors present a sample of IoT use cases that are representative of a wide variety of its implementations and identify some of the practical challenges and the lessons learned in the implementation of these use cases.
Journal ArticleDOI

Modelling IoT devices communication employing representative operation modes to reveal traffic generation characteristics

TL;DR: The proposed model is able to capture a wider understanding of device behaviour than existing, state-of-the-art traffic models and has significantly higher accuracy in estimating the number of transmitted packets compared with the current models in the literature.
References
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Proceedings ArticleDOI

Real-time status: How often should one update?

TL;DR: A time-average age metric is employed for the performance evaluation of status update systems and the existence of an optimal rate at which a source must generate its information to keep its status as timely as possible at all its monitors is shown.
Journal ArticleDOI

Update or Wait: How to Keep Your Data Fresh

TL;DR: In this paper, the authors study how to optimally manage the freshness of information updates sent from a source node to a destination via a channel and develop efficient algorithms to find the optimal update policy among all causal policies and establish sufficient and necessary conditions for the optimality of the zero-wait policy.
Journal ArticleDOI

On the Age of Information in Status Update Systems With Packet Management

TL;DR: A communication system in which status updates arrive at a source node, and should be transmitted through a network to the intended destination node, using the queuing theory, and it is assumed that the time it takes to successfully transmit a packet to the destination is an exponentially distributed service time.
Proceedings ArticleDOI

Optimizing age-of-information in a multi-class queueing system

TL;DR: This paper derives the exact peak age-of-Information (PAoI) profile of the system, which measures the “freshness” of the status information, and seeks to optimize the age of information, by formulating the problem using quasiconvex optimization, and obtaining structural properties of the optimal solution.
Proceedings ArticleDOI

A Fleet of Miniature Cars for Experiments in Cooperative Driving

TL;DR: This article elaborates the design of the miniature robotic car, the Cambridge Minicar, as well as the fleet’s control architecture, and introduces a unique experimental testbed that consists of a fleet of 16 miniature Ackermann-steering vehicles.
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