On the Age of Information in Multi-Source Multi-Hop Wireless Status Update Networks

Farazi, Shahab; Klein, Andrew G.; McNeill, John; Brown, Donald R.

doi:10.1109/spawc.2018.8445981

Cited by 45 publications

(50 citation statements)

References 23 publications

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“…This makes the interaction between the aggregator and transmitter more complicated than that between relay nodes purely for data retransmission. In this light, our concerned problem, formulated mathematical model, derived analysis results and proposed optimizing algorithm are all different from those presented in existing researches [36]- [40].…”

Section: Related Workmentioning

confidence: 86%

Optimizing Information Freshness in Computing-Enabled IoT Networks

Yang

Wang

et al. 2020

IEEE Internet Things J.

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Internet of Things (IoT) has emerged as one of the key features of the next generation wireless networks, where timely delivery of status update packets is essential for many realtime IoT applications. To provide users with context-aware services and lighten the transmission burden, the raw data usually needs to be preprocessed before being transmitted to the destination. However, the effect of computing on the overall information freshness is not well understood. In this work, we first develop an analytical framework to investigate the information freshness, in terms of peak age of information (PAoI), of a computing enabled IoT system with multiple sensors. Specifically, we model the procedure of computing and transmission as a tandem queue, and derive the analytical expressions of the average PAoI for different sensors. Based on the theoretical results, we formulate a minmax optimization problem to minimize the maximum average PAoI of different sensors. We further design a derivative-free algorithm to find the optimal updating frequency, with which the complexity for checking the convexity of the formulated problem or obtaining the derivatives of the object function can be largely reduced. The accuracy of our analysis and effectiveness of the proposed algorithm are verified with extensive simulation results.Index Terms-Internet of things, information freshness, peak age of information, data preprocessing, derivative-free optimization.

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Section: Related Workmentioning

confidence: 86%

Optimizing Information Freshness in Computing-Enabled IoT Networks

Yang

Wang

et al. 2020

IEEE Internet Things J.

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“…AoI, upon reception of a new update packet, drops to the time elapsed since generation of the packet, and grows linearly otherwise. Over the past few years, there has been a rapidly growing body of work on analyzing AoI for queuing systems [1]- [6], and using AoI as a metric for scheduling policies in networks [7]- [14].…”

Section: Introductionmentioning

confidence: 99%

A Whittle Index Approach to Minimizing Functions of Age of Information

Tripathi

Modiano

2019

2019 57th Annual Allerton Conference on Communication, Control, and Computing (Allerton)

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We consider a setting where multiple active sources send real-time updates over a single-hop wireless broadcast network to a monitoring station. Our goal is to design a scheduling policy that minimizes the time-average of general nondecreasing cost functions of Age of Information. We use a Whittle index based approach to find low complexity scheduling policies that have good performance, for reliable as well as unreliable channels. We prove that for a system with two sources, having possibly different cost functions and reliable channels, the Whittle index policy is exactly optimal. For reliable channels, we also derive structural properties of an optimal policy, that suggest that the performance of the Whittle index policy may be close to optimal in general. These results might also be of independent interest in the study of restless multi-armed bandit problems with similar underlying structure. Finally, we provide simulations comparing the Whittle index policy with optimal scheduling policies found using dynamic programming, which support our results.

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“…1) Nd ≤ T < (N + 1)d: We first note that Nd is the least value that T can have for problem (18) to admit a feasible solution. In this case, the following theorem shows that the optimal solution is achieved by sending all updates back-to-back with the minimal inter-update time possible to allow the reception of all of them by the end of the relatively small session time T .…”

Section: A Solution Building Block: the Single-user Channelmentioning

confidence: 99%

Timely Updates in Energy Harvesting Two-Hop Networks: Offline and Online Policies

Arafa

Ulukuş

2019

IEEE Trans. Wireless Commun.

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A two-hop energy harvesting communication network is considered, in which measurement updates are transmitted by a source to a destination through an intermediate relay. Updates are to be sent in a timely fashion that minimizes the age of information, defined as the time elapsed since the most recent update at the destination was generated at the source. The source and the relay communicate using energy harvested from nature, which is stored in infinite-sized batteries. Both nodes use fixed transmission rates, and hence updates incur fixed delays (service times). Two problems are formulated:an offline problem, in which the energy arrival information is known a priori, and an online problem, in which such information is revealed causally over time. In both problems, it is shown that it is optimal to transmit updates from the source just in time as the relay is ready to forward them to the destination, making the source and the relay act as one combined node. A recurring theme in the optimal policy is that updates should be as uniformly spread out over time as possible, subject to energy causality and service time constraints. This is perfectly achieved in the offline setting, and is achieved almost surely in the online setting by a best effort policy. I. INTRODUCTIONDeveloping low-latency communication policies is a crucial requirement for next generation communication networks, especially in applications pertaining to real-time status monitoring where information needs to be kept as fresh as possible at interested destinations. The age of information (AoI) metric has been recently introduced in the literature as a suitable performance

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On the Age of Information in Multi-Source Multi-Hop Wireless Status Update Networks

Cited by 45 publications

References 23 publications

Optimizing Information Freshness in Computing-Enabled IoT Networks

Optimizing Information Freshness in Computing-Enabled IoT Networks

A Whittle Index Approach to Minimizing Functions of Age of Information

Timely Updates in Energy Harvesting Two-Hop Networks: Offline and Online Policies

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