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Optimal Policies for Status Update Generation in an IoT Device With Heterogeneous Traffic
Fdn Res and Technol Hellas, Greece.
Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0003-4416-7702
Fdn Res and Technol Hellas, Greece.
2020 (English)In: IEEE Internet of Things Journal, ISSN 2327-4662, Vol. 7, no 6, p. 5315-5328Article in journal (Refereed) Published
Abstract [en]

A large body of applications that involve monitoring, decision making, and forecasting require timely status updates for their efficient operation. Age of Information (AoI) is a newly proposed metric that effectively captures this requirement. Recent research on the subject has derived AoI optimal policies for the generation of status updates and AoI optimal packet queueing disciplines. Unlike previous research, we focus on low-end devices that typically support monitoring applications in the context of the Internet of Things. We acknowledge that these devices host a diverse set of applications some of which are AoI sensitive while others are not. Furthermore, due to their limited computational resources, they typically utilize a simple first-in-first-out (FIFO) queueing discipline. We consider the problem of optimally controlling the status update generation process for a system with a source-destination pair that communicates via a wireless link, whereby the source node is composed of a FIFO queue and serves two applications, one that is AoI sensitive and one that is not. We formulate this problem as a dynamic programming problem and utilize the framework of Markov decision processes to derive the optimal policy for the generation of status update packets. Due to the lack of comparable methods in the literature, we compare the derived optimal policies against baseline policies such as the zero-wait policy. Results indicate that the baseline policy fails to capture the complex system dynamics that determine the relationship between the frequency of status update generation and the resulting queueing delay and thus perform poorly. To the best of our knowledge, the derived optimal policy does not exhibit a simple structure; thus, we utilized the baseline policies, whose operation is intuitive, to gain insight into the inner workings of the optimal policy.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC , 2020. Vol. 7, no 6, p. 5315-5328
Keywords [en]
Delays; Internet of Things; Monitoring; Transmitters; Wireless communication; Dynamic programming; Age of information; heterogeneous traffic; Internet of Things (IoT); Markov decision process
National Category
Communication Systems
Identifiers
URN: urn:nbn:se:liu:diva-167682DOI: 10.1109/JIOT.2020.2976690ISI: 000543157700050OAI: oai:DiVA.org:liu-167682DiVA, id: diva2:1454709
Note

Funding Agencies|CENIIT; ELLIIT

Available from: 2020-07-20 Created: 2020-07-20 Last updated: 2020-09-22

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