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

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

Barakat, Basel ORCID: 0000-0001-9126-7613, Keates, Simeon ORCID: 0000-0002-2826-672X, Wassell, Ian and Arshad, Kamran (2018) Adaptive Status Arrivals Policy (ASAP) Delivering Fresh Information (Minimise Peak Age) in Real-World Scenarios. In: 21st International Conference on Human-Computer Interaction, 26-31 July 2019, Walt Disney World Swan and Dolphin Resort, Orlando, Florida, USA. (In Press)

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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.

Item Type: Conference or Conference Paper (Paper)
Uncontrolled Keywords: Real Time Systems, Cloud, Adaptive Systems, Information Freshness, Peak Age of Information.
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / Department / Research Group: Faculty of Engineering & Science
Faculty of Engineering & Science > Department of Engineering Science
Faculty of Engineering & Science > Future Technology and the Internet of Things
Related URLs:
Last Modified: 11 Jul 2019 08:29
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
URI: http://gala.gre.ac.uk/id/eprint/24748

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