Active Status Update Packet Drop Control in an Energy Harvesting Node

Rafiee, Parisa; Özel, Ömur

doi:10.48550/arxiv.1911.01407

Cited by 2 publications

(3 citation statements)

References 17 publications

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“…In [110], a setting was considered in which a sensor node must decide when to sleep to save energy but miss updates or wake to receive updates and use energy. An age-threshold based power ON-OFF scheme was developed to minimize age subject to energy harvesting and battery capacity constraints.…”

Section: E Advanced Energy Harvesting Settingsmentioning

confidence: 99%

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Age of Information: An Introduction and Survey

Yates¹,

Yin²,

Brown³

et al. 2020

Preprint

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We summarize recent contributions in the broad area of age of information (AoI). In particular, we describe the current state of the art in the design and optimization of low-latency cyberphysical systems and applications in which sources send time-stamped status updates to interested recipients. These applications desire status updates at the recipients to be as timely as possible; however, this is typically constrained by limited system resources. We describe AoI timeliness metrics and present general methods of AoI evaluation analysis that are applicable to a wide variety of sources and systems. Starting from elementary single-server queues, we apply these AoI methods to a range of increasingly complex systems, including energy harvesting sensors transmitting over noisy channels, parallel server systems, queueing networks, and various single-hop and multi-hop wireless networks. We also explore how update age is related to MMSE methods of sampling, estimation and control of stochastic processes. The paper concludes with a review of efforts to employ age optimization in cyberphysical applications.

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Section: E Advanced Energy Harvesting Settingsmentioning

confidence: 99%

“…Other frameworks that combine AoI with energy harvesting include wireless power transfer [106], multiple access channels [107], cognitive radio systems [108], monitoring with priority [109], operational and sensing costs [110], [111], and tradeoffs between AoI and distortion [112].…”

Section: A Overviewmentioning

confidence: 99%

Age of Information: An Introduction and Survey

Yates¹,

Yin²,

Brown³

et al. 2020

Preprint

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show abstract

“…In [6], [7] waiting is used as a mechanism to regulate the traffic while in [8] tandem computation-transmission operations and queue management are combined. We also refer the reader to [9]- [24] for other work closely related to this paper.…”

Section: Introductionmentioning

confidence: 99%

Maintaining Information Freshness in Power-Efficient Status Update Systems

Rafiee¹,

Zou²,

Özel³

et al. 2020

Preprint

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This paper is motivated by emerging edge computing systems which consist of sensor nodes that acquire and process information and then transmit status updates to an edge receiver for possible further processing. As power is a scarce resource at the sensor nodes, the system is modeled as a tandem computation-transmission queue with power-efficient computing. Jobs arrive at the computation server with rate λ as a Poisson process with no available data buffer. The computation server can be in one of three states: (i) OFF: the server is turned off and no jobs are observed or processed, (ii) ON-Idle: the server is turned on but there is no job in the server, (iii) ON-Busy: the server is turned on and a job is processed in the server. These states cost zero, one and pc > 1 units of power, respectively. Under a longterm power constraint, the computation server switches from one state to another in sequence: first a deterministic To time units in OFF state, then waiting for a job arrival in ON-Idle state and then in ON-Busy state for an independent identically distributed compute time duration. The transmission server has a single unit data buffer to save incoming packets and applies last come first serve with discarding as well as a packet deadline to discard a sitting packet for maintaining information freshness, which is measured by the Age of Information (AoI). Additionally, there is a monotonic functional relation between the mean time spent in ON-Busy state and the mean transmission time. We obtain closed-form expressions for average AoI and average peak AoI. Our numerical results illustrate various regimes of operation for best AoI performances optimized over packet deadlines with relation to power efficiency.

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Active Status Update Packet Drop Control in an Energy Harvesting Node

Cited by 2 publications

References 17 publications

Age of Information: An Introduction and Survey

Age of Information: An Introduction and Survey

Maintaining Information Freshness in Power-Efficient Status Update Systems

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