Age-of-Information Minimization in Two-User Multiple Access Channel with Energy Harvesting

Hirosawa, Naoya; Iimori, Hiroki; Abreu, Giuseppe; Ishibashi, Koji

doi:10.1109/camsap45676.2019.9022506

Cited by 6 publications

(3 citation statements)

References 16 publications

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“…Unlike the above works, the works investigated the EH wireless sensor networks in terms of average AoI and PAoI by considering the case where one new update packet would be generated only when the one update packet was successfully received. [25][26][27] With this consideration, after an update packet is successfully received, the age is reset to one. As a result, the instantaneous PAoI is the interdeparture time.…”

Section: Related Workmentioning

confidence: 99%

“…Pappas et al 27 have investigated the average AoI of cache‐assisted AoI system where the destination can receive status update from sensor source or cache. In the work of Hirosawa et al, 26 they considered a multi‐access scenario with two sensor nodes, one of which is connected with power grid and the other of which harvests energy from its environment. Stamatakis et al 36 have considered the case where the server harvests the random arrival energy process and the destination monitors a stochastic process, which has two states, i.e., normal state and alarm state.…”

Section: Introductionmentioning

confidence: 99%

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Age of information analysis for internet of things information status update system with cellular backhaul and dedicated energy harvesting beacons

Hao

Jia

2022

Int J Communication

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SummaryThe Internet of Things (IoT) that is usually deployed with the assistance of cellular backhaul and energy harvesting (EH) is characterized by the status update freshness. However, the traditional nature EH results in the loss of information freshness due to the randomness of nature energy process. Although using wireless energy transferring (WET) to charge sensors can overcome this problem, this method has low‐energy efficiency. With these considerations, this paper proposes a novel IoT system under cellular communication scenario by simultaneously exploiting the nature EH and WET. The proposed IoT system is consisted of a cellular backhaul subsystem, a wireless EH and transferring (WEHT) subsystem, and a wireless sensor status update subsystem. The WEHT subsystem employs the dedicated power beacons harvesting energy from natural energy source and transferring the harvested energy to sensor. For the proposed IoT system, this paper first investigates the WEHT subsystem and constructs the Markov Chain (MC) of discrete energy states as well as the MC state transition matrix. Second, the average AoI and peak AoI (PAoI) are formulated by separately considering cellular backhaul and EHTBs. The AoI (PAoI) comparison shows that the proposed EHTB‐based IoT system can outperform the conventional non‐EHTB one where the sensor directly harvests energy from natural source. At the same time, the numerical results exploit the impact of system parameters on AoI and PAoI, respectively. It is found that there exists a trade‐off between the nature energy arrival and EHTB energy transfer so that the average minimum AoI and PAoI are achieved.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Age of information analysis for internet of things information status update system with cellular backhaul and dedicated energy harvesting beacons

Hao

Jia

2022

Int J Communication

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“…The references [ 11 , 12 ] address varying source update frequency and [ 13 , 14 ] address service rate in various queuing models. In the wireless network scenario, the scheduling algorithms for optimizing AoI is studied extensively, such as those considering the channel state [ 15 , 16 ], throughput [ 17 , 18 , 19 ], energy harvesting [ 20 , 21 , 22 ], and average resource constraints [ 23 , 24 ], multiple sources [ 25 , 26 , 27 , 28 ], and multiple channels [ 29 , 30 , 31 , 32 ] to name a few. Ref.…”

Section: Introductionmentioning

confidence: 99%

Optimizing Urgency of Information through Resource Constrained Joint Sensing and Transmission

Rafiee

Özel

2022

Entropy

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Applications requiring services from modern wireless networks, such as those involving remote control and supervision, call for maintaining the timeliness of information flows. Current research and development efforts for 5G, Internet of things, and artificial intelligence technologies will benefit from new notions of timeliness in designing novel sensing, computing, and transmission strategies. The age of information (AoI) metric and a recent related urgency of information (UoI) metric enable promising frameworks in this direction. In this paper, we consider UoI optimization in an interactive point-to-point system when the updating terminal is resource constrained to send updates and receive/sense the feedback of the status information at the receiver. We first propose a new system model that involves Gaussian distributed time increments at the receiving end to design interactive transmission and feedback sensing functions and develop a new notion of UoI suitable for this system. We then formulate the UoI optimization with a new objective function involving a weighted combination of urgency levels at the transmitting and receiving ends. By using a Lyapunov optimization framework, we obtain a decision strategy under energy resource constraints at both transmission and receiving/sensing and show that it can get arbitrarily close to the optimal solution. We numerically study performance comparisons and observe significant improvements with respect to benchmarks.

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Maintaining Data Freshness in Multi-channel Multi-hop Wireless Networks

Xie,

Li,

Chai

et al. 2024

Lecture Notes in Computer Science

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Age-of-Information Minimization in Two-User Multiple Access Channel with Energy Harvesting

Cited by 6 publications

References 16 publications

Age of information analysis for internet of things information status update system with cellular backhaul and dedicated energy harvesting beacons

Age of information analysis for internet of things information status update system with cellular backhaul and dedicated energy harvesting beacons

Optimizing Urgency of Information through Resource Constrained Joint Sensing and Transmission

Maintaining Data Freshness in Multi-channel Multi-hop Wireless Networks

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